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PubMed2026

Adjuvant apatinib therapy following concurrent chemoradiotherapy in patients with high-risk nasopharyngeal carcinoma: A multicenter, prospective phase 2 study.

PURPOSE: To assess the efficacy and safety of concurrent chemoradiotherapy (CCRT) combined with apatinib in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). METHODS: This multicenter, prospective, phase II study enrolled patients with newly histologically confirmed LA-NPC, who were randomly assigned to receive CCRT followed by adjuvant apatinib (investigational arm) or CCRT alone (control arm). The investigational arm received 250 mg/day of oral apatinib administered every 28 days for up to six cycles after CCRT. The primary endpoint was 3-year progression-free survival (PFS) and secondary endpoints of overall survival (OS), distant metastasis-free survival (DMFS) and local recurrence-free survival (LRFS) of 3-year, and safety. RESULTS: From July 2018 to September 2020, 44 and 44 patients were randomized into the CCRT-alone and CCRT and apatinib groups, respectively. The median follow-up duration 56 (range: 40.0-58.6) months. The survival outcomes were the 3-year PFS, OS, and DMFS rates in the adjuvant apatinib following CCRT group were significantly higher than those observed in the CCRT-alone group((PFS, 78.6%vs. 54.5%, p = 0.027; OS, 88.1% vs. 75.0%, p = 0.029; DMFS, 85.4%vs. 59.1%, p = 0.009). The 3-year LRFS was similar between the groups. The grade 3-4 treatment-related adverse events(TRAEs) were higher in the former group than in the latter. The most common grade 3-4 non-hematology-related adverse events were hypertension (14.3%), hand-foot syndrome (9.5%), increased transaminase levels (7.1%), and headache (7.1%). CONCLUSION: Apatinib significantly improved the treatment effects of CCRT for high-risk LA-NPC patients. Therefore, CCRT and adjuvant apatinib may represent a promising option for this patient population.

Adjuvant therapy↗

PubMed2026

A bimodal large language model reduces misalignment in patient education: A double-blinded randomized trial.

BACKGROUND: Effective patient education requires accurate communication aligned with patients' emotional and semantical needs. Text-based large language models (LLMs) lack access to non-verbal cues, which may contribute to misaligned responses. METHODS: We evaluated emotional and semantic misalignment in a text-based LLM using 64,200 utterances from 16,583 patient education cases across six departments and three centers. Dolphin was developed integrating text and audio cues and evaluated through emotion recognition, semantic consistency assessment, branch-level ablations, and a double-blinded randomized trial against a matched text-based LLM comparator (Chinese Clinical Trial Registry: (ChiCTR2500095933). FINDINGS: The text-based LLM showed emotional misalignment in 36.7% of responses and semantic misalignment in 28.3% of cases, with higher misalignment under greater burden. Dolphin outperformed the text-based LLM in emotion recognition accuracy (0.886 vs. 0.713) and semantic consistency (84.9% vs. 82.1%; both adjusted p < 0.001). Ablations supported contribution of audio branches. Dolphin received higher expert ratings than the text-based LLM and human educators (all p < 0.001). In 555 patients, Dolphin was associated with greater patient satisfaction (98.6% vs. 93.8%), suggestion acceptance (76.1% vs. 58.9%; p < 0.001), proactive disclosure (44.6% vs. 26.5%; p < 0.001), and fewer 7-day unplanned recontact (12.9% vs. 22.9%; p = 0.002). No unsafe recommendations or safety events were identified. CONCLUSIONS: Compared with text-based LLM, Dolphin improved emotional-semantic alignment and patient-education outcomes, supporting bimodal alignment as a strategy for reducing misalignment-driven communication failures. FUNDING: National Natural Science Foundation of China, State Key Laboratory Special Fund, and Chinese Academy of Medical Sciences Innovation Fund.

Humans↗

PubMed2026

Ketamine assisted psychotherapy to reduce chronic neuropathic pain: A mixed-methods randomized pilot trial.

BACKGROUND: Intravenous ketamine can provide short-term analgesia in chronic neuropathic pain but benefits often wane after treatment. We conducted a randomized pilot trial to assess the feasibility of combining ketamine infusions with psychotherapy to inform future efficacy trials. METHODS: In this single-center, randomized, outcome-assessor-blinded pilot trial at a Canadian tertiary pain clinic, adults with moderate-to-severe chronic neuropathic pain were randomly assigned in 1:1:1 ratio to the ketamine, psychotherapy, or combined ketamine plus psychotherapy arm. Ketamine was delivered as three intravenous infusions over 16 weeks; psychotherapy consisted of 16 weekly cognitive behavioral therapy and mindfulness-based meditation sessions. The primary outcome was feasibility, assessed using prespecified progression criteria. Exploratory outcomes included changes in pain interference (PROMIS 6a T-score), pain intensity, mood, and qualitative interview findings at week 20 (ClinicalTrials.gov: NCT05639322). FINDINGS: Between October 23, 2023, and March 31, 2025, 30 participants were randomized, and 26 (87%) completed 20-week follow-up. Most feasibility criteria, including consent, retention, data completeness, and absence of study-related serious adverse events, were met; adherence targets were partially met. Exploratory pain outcomes showed numerical improvement across groups, with clinically meaningful reductions observed for pain interference and pain intensity. Sixty-four adverse events were recorded, mostly mild and in ketamine-containing groups; no serious study-related adverse events occurred. CONCLUSIONS: Combined ketamine and psychotherapy was feasible and acceptably safe in this pilot trial, supporting evaluation in a larger efficacy-powered study. FUNDING: The study was funded by the St. Michael's Hospital Innovation Fund, The Canadian Pain Society Early Investigator Award and the Physician Services Incorporation Early Career Researcher Award.

Humans↗

PubMed2026

MET-Aberrant non-small cell lung cancer: from kinase dependence to cell-surface targetability-mechanistic basis and biomarker framework for bispecific antibodies and antibody-drug conjugates.

MET-aberrant non-small cell lung cancer (NSCLC) is not a uniform therapeutic entity. Its biology, diagnostic pathways, and treatment sensitivity differ across MET exon 14 skipping alteration (METex14), MET amplification, and MET overexpression. This heterogeneity cannot be fully explained by conventional event-based classification and is reflected in the distinct clinical activity of MET tyrosine kinase inhibitors (MET-TKIs), bispecific antibodies (BsAbs), and antibody-drug conjugates (ADCs). With the emergence of antibody-based therapies, MET has evolved from a signaling driver to a cell-surface target for receptor modulation and payload delivery. We therefore propose a clinically anchored two-dimensional framework for interpreting therapeutic relevance in MET-aberrant NSCLC: kinase dependence and cell-surface targetability. Neither dimension should be regarded as a directly measurable binary variable. Kinase dependence is inferred from genomic and treatment-contextual proxies, most strongly METex14 and, more conditionally, high-level focal MET amplification. Cell-surface targetability is approximated by drug-specific IHC assessment of assay-defined c-MET protein expression; however, receptor internalization, intracellular trafficking, and payload delivery capacity remain incompletely measurable in routine clinical practice. Within this framework, MET-TKIs have the most evidence-supported established role in tumors with evidence of MET-driven kinase dependence. EGFR × MET BsAbs have demonstrated clinical activity in broad post-osimertinib EGFR-mutant NSCLC, while EGFR/MET co-dependence or MET-mediated bypass activation provides a mechanistic rationale for their use; MET-defined preferential benefit remains to be prospectively established. MET-directed antibody-drug conjugates (MET-ADCs) are supported in drug- and assay-defined populations with high c-MET protein overexpression, although the predictive relevance of delivery-related factors remains hypothesis-generating. Accordingly, MET testing should shift from single-event detection to platform-oriented stratification: next-generation sequencing (NGS) for driver alterations and resistance profiles, fluorescence in situ hybridization (FISH) for high-level focal amplification, and immunohistochemistry (IHC) for surface expression relevant to antibody-based therapies. This framework is intended to organize current biological and clinical evidence rather than to replace drug-specific companion diagnostics, regulatory indications, or prospectively validated treatment-selection algorithms. Precision treatment of MET-aberrant NSCLC is thus moving from event-based drug selection toward mechanism-based therapeutic matching. Future priorities include standardizing biomarkers, defining optimal target populations, and aligning biological subtypes, diagnostic strategies, and therapeutic platforms.

Antibody-drug conjugate↗

PubMed2026

Early and late CTCAE and patient-reported outcomes following lung cancer radiotherapy: A sex-stratified descriptive analysis from the REQUITE cohort.

BACKGROUND: Long-term prospective data on lung cancer patients treated with radiotherapy are limited, restricting understanding of outcomes and sex-specific characteristics. The multicentre REQUITE study provides standardized follow-up data from an international cohort. METHODS: We analysed longitudinal data from 530 lung cancer patients treated with radical radiotherapy (sequential or concurrent chemoradiotherapy, or stereotactic body radiation therapy [SBRT]) between 2014 and 2017 at 16 centres in Europe and the USA. Healthcare professionals prospectively recorded 21 pulmonary, oesophageal, neurological, cardiac, and skin adverse events using CTCAE v4.0. Patient-reported outcomes assessed symptoms, quality-of-life, fatigue, and physical activity. Adverse event incidence was stratified by sex, radiotherapy technique, chemotherapy administration, smoking status, and other clinical factors. RESULTS: At 12 months, 309 patients were evaluable, with 151 having follow-up beyond one year. Pulmonary adverse events were most frequent (40% grade ≥ 2), mainly dyspnoea and cough. Women had higher rates of oesophagitis, and more frequently reported dysphagia, and chest wall pain, while men experienced a higher frequency of cardiac adverse events. Exploratory subgroup analyses identified significant sex-related differences in grade ≥ 3 pulmonary adverse events following SBRT and in overall grade ≥ 2 oesophageal adverse events among patients with clinical stage I-II and those aged >70 years. Patient-reported outcomes showed persistent fatigue and reduced physical activity, particularly in females. Symptom prevalence and severity varied by sex, age, treatment modality, smoking status, and clinical stage. CONCLUSION: The REQUITE-Lung cohort provides prospectively collected real-world data on radiotherapy-related adverse events in lung cancer patients. This study describes patterns of adverse events and patient-reported outcomes according to sex, age, and treatment characteristics. These findings are hypothesis-generating and may support future validation in independent and pooled datasets.

Patient-reported outcomes↗

PubMed2025

Impact of Chewing Behavior Change on Cognition and Cerebral Hemodynamics.

BACKGROUND: Impaired chewing ability is a recognized risk factor for cognitive decline in older adults, potentially due to reduced neural stimulation in cognition-related brain regions. While short-term studies have demonstrated transient increases in neural activity from chewing, the sustained cognitive and neurophysiological effects of encouraging thorough chewing habits in daily life remain unclear. OBJECTIVE: This randomized controlled trial investigated whether promoting thorough chewing during meals could improve cognitive function and cerebral hemodynamics in older adults. METHODS: Fifty participants aged 65 y or older were randomly assigned to either a 1-mo intervention group, which used a wearable device to monitor and increase chewing strokes during meals, or a control group that maintained usual chewing habits. Chewing behavior, cognitive performance (including memory and executive function via the color Stroop test), and cerebral hemodynamics in the dorsolateral prefrontal cortex (DLPFC) were measured at baseline and after 1 mo. Statistical analyses included t tests, chi-square tests, 2-way analysis of variance with post hoc tests, Pearson correlations, and generalized linear models to evaluate group differences and associations between chewing and cognitive outcomes. RESULTS: Significant time-by-group interactions were observed for memory, F(1, 48) = 6.24, P = 0.043, and hemodynamic responses in the left DLPFC, F(1, 48) = 6.19, P = 0.013. The intervention group showed increased chewing frequency (P = 0.017), improved memory performance, and reduced left DLPFC responses compared with controls. Chewing frequency was positively correlated with Stroop test scores (r = 0.53, P = 0.010) and negatively with hemodynamic changes in the left DLPFC (r = -0.30, P = 0.040). Although improvements in other cognitive outcomes and hemodynamic measures favored the intervention group, these differences did not reach statistical significance. CONCLUSIONS: Promoting intentional chewing habits for 1 mo may enhance memory-related cognitive performance and neural efficiency in the DLPFC during working memory tasks in older adults. This nonpharmacologic, low-burden strategy warrants further research with longer interventions to support cognitive health and dementia prevention. TRIAL REGISTRATION ID: UMIN000044280Knowledge Transfer Statement:This study demonstrates that promoting thorough chewing habits in older adults can improve memory and enhance neural efficiency in the brain. Encouraging intentional mastication is a simple, nonpharmacologic approach that may help maintain cognitive health and prevent dementia, providing a practical strategy for clinicians and policymakers to support healthy aging.

Humans↗

PubMed2026

Adjuvant oxaliplatin with S-1 (SOX) versus S-1 for stage II-III gastric cancer (CAPITAL): A randomized, open-label, phase 3 trial.

BACKGROUND: Adjuvant chemotherapy following D2 gastrectomy constitutes the standard-of-care for resectable gastric or gastroesophageal junction (GEJ) carcinoma. The CAPITAL trial is a multicenter, randomized, phase 3 study, aiming to assess the efficacy and safety of adjuvant oxaliplatin plus S-1 (SOX) versus S-1 alone. METHODS: Patients with histologically confirmed pathological stage II-III gastric or GEJ adenocarcinoma after gastrectomy with D2 lymphadenectomy were randomly assigned (1:1) to receive either the SOX regimen (n = 362) or the S-1 regimen (n = 362). The primary endpoint was overall survival. This study is registered with ClinicalTrials.gov (NCT01795027). FINDINGS: The median follow-up was 74.0 months (interquartile range [IQR], 35.5-89.3). The 5-year overall survival rates were 70.9% (95% confidence interval [CI], 66.0-76.1) in the SOX group and 62.9% (95% CI, 57.8-68.5) in the S-1 group (hazard ratio [HR], 0.74; 95% CI, 0.58-0.95; p = 0.018). The 3- and 5-year disease-free survival rates were 71.2% (95% CI, 66.5-76.3) and 66.2% (95% CI, 61.2-71.6) in the SOX group, as compared with 65.1% (95% CI, 60.2-70.5) and 55.6% (95% CI, 50.4-61.3) in the S-1 group (HR, 0.76; 95% CI, 0.61-0.96). Treatment-related adverse events of grade 3-4 occurred in 87 (25%) of 349 patients in the SOX group and 45 (13%) of 347 patients in the S-1 group. The most common grade 3-4 adverse event was neutropenia, occurring in 44 (13%) of 349 patients in the SOX group and 23 (7%) of 347 patients in the S-1 group. CONCLUSIONS: The addition of adjuvant oxaliplatin to S-1 chemotherapy significantly improved overall survival and disease-free survival in patients with gastric cancer. FUNDING: This research was supported by the National Natural Science Foundation of China (82573092 and 82573387).

Humans↗

PubMed2026

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans↗

PubMed2026

Early hepatic protein responses to dietary restriction-refeeding in Japanese quail: A proteomic investigation.

Feed intake and refeeding after nutrient scarcity induce rapid metabolic adaptations in the poultry liver; however, hepatic proteomic recovery pathways in the early hours post-refeeding remain poorly defined. This study aimed to characterize early liver protein signatures in Japanese quail (Coturnix japonica) recovering from nutritional stress under two refeeding conditions. Eighteen 12-week-old male quails (245.20 ± 0.213 g) were assigned to three groups (n = 6): control fed ad libitum (12.13 MJ/kg), 24 h feed deprivation followed by 6 h refeeding, and 24 h low metabolizable energy (6.30 MJ/kg) diet followed by 6 h refeeding. In total, 854 proteins were identified, of which 515 met the filtering criteria. The low metabolizable energy refeeding showed higher abundance of proteins linked to ATP binding and carbohydrate/carboxylic acid metabolism, alongside detoxification-related proteins, while suppressing translation/RNA-binding machinery and antioxidant pathways. Feed-deprived refeeding enriched in oxidative phosphorylation and mitochondrial complex I assembly with reduced cytoplasmic translation, NMD-related components, and sulfur compound metabolism. A direct comparison indicated divergent recovery strategies: low metabolizable energy refeeding mainly reflected oxidoreductase activity and translation initiation, whereas feed-deprived refeeding potentially enriched mitochondrial ATP production and glutathione-based defenses. Our analysis indicate that 6 h of refeeding initiates an early, incomplete recovery toward hepatic homeostasis, with the severity of prior nutritional restriction dictating distinct liver metabolic priorities. Collectively, these findings might provide a preliminary understanding of the hepatic mechanisms involved in recovery from nutrient deprivation and may help in the development of feeding strategies for managing metabolic recovery in poultry. However, these findings should be considered hypothesis-generating pending further validation.

Animals↗

PubMed2026

The present and future of nonviral delivery-based genome editing for hereditary hearing loss.

PURPOSE OF REVIEW: This review summarizes nonviral genome-editing delivery platforms for hereditary hearing loss, focusing on lipid nanoparticles (LNPs) and engineered virus-like particles (eVLPs), and discusses their advantages over adeno-associated virus-based delivery, as well as the barriers to clinical translation. RECENT FINDINGS: Recent advances have established LNPs as a clinically advanced nonviral platform, although challenges related to inner ear biodistribution, cell type specificity, endosomal escape, and immunogenicity remain to be addressed. In parallel, eVLPs have undergone substantial technical evolution, progressing from early low efficiency systems to advanced base editor- and prime editor-eVLP architectures that enhance cargo loading and editing efficiency. Extracellular vesicle-based genome editing has also emerged as an additional platform, although issues related to reproducibility, loading efficiency, and scalability remain major hurdles. SUMMARY: Nonviral genome editing platforms expand the therapeutic toolkit for hereditary hearing loss by enabling transient delivery of genome editors with potential safety advantages. Future efforts should focus on characterizing biodistribution and immunogenicity, refining cell type-specific tropism, and establishing scalable manufacturing processes to enable successful clinical translation.

Humans↗

PubMed2026

Proteomic and phosphoproteomic profiles of time-dependent dynamic changes in LPS-induced macrophage polarization.

The temporal proteomic and phosphoproteomic reprogramming during early M1 macrophage polarization (0-6 h) remains poorly understood. We performed time-resolved proteomic and phosphoproteomic analyses of LPS-stimulated RAW264.7 macrophages at seven time points within 6 h. Time-clustering of differentially expressed molecules revealed two patterns: initial change with partial recovery, and sustained dysregulation. Upregulated proteins and phosphorylation sites were enriched in the Rho GTPase signaling pathway, T-cell receptor signaling pathway, NF-κB cascade, osteoclast differentiation pathway, and antiviral immune pathway. Downregulated pathways were associated with cell cycle regulation, chromatin remodeling, RNA metabolism, and mRNA processing, indicating resource reallocation to prioritize acute inflammatory responses. Kinase-substrate network analysis confirmed the mitogen-activated protein kinase (MAPK), cyclin-dependent kinase (CDK), protein kinase B (AKT), and ribosomal S6 kinase (RSK) families as core upstream phosphorylation regulators. Integrated analysis revealed synergistic and antagonistic relationships between proteomic and phosphoproteomic changes. This study provides a temporal molecular atlas of M1 polarization, delineating inflammatory signaling dynamics and offering a basis for therapeutic target discovery in inflammatory diseases. SIGNIFICANCE: Macrophage M1 polarization is a central event in innate immune defense against pathogenic invasion, yet its dysregulation is a pivotal driver of the onset and progression of a broad spectrum of inflammation-associated disorders, spanning autoimmune diseases, infectious conditions and inflammatory bone diseases, making the dissection of its molecular regulatory mechanisms an urgent research priority in immunology and translational medicine. Dynamic molecular events within 0-6 h after LPS stimulation are critical for initiating and shaping M1 inflammatory activation, yet systematic time-resolved proteomic and phosphoproteomic profiling remains insufficient.In this study, we comprehensively characterized temporal proteome and phosphoproteome changes at seven consecutive time points during macrophage polarization, clarified two distinct dynamic molecular patterns, identified core signaling pathways and key kinase regulators involved in inflammatory reprogramming, and uncovered the leading role of post-translational phosphorylation modifications in initiating polarization. This work delineates the time-series molecular atlas of early macrophage activation, provides novel insights into the temporal regulatory mechanism of inflammatory signaling networks, and lays a solid experimental foundation for exploring new intervention targets and regulatory nodes in clinical translational research.

Lipopolysaccharides↗

PubMed2026

Functional and Nutritional Potential of Chickpea Protein Hydrolysates: A Systematic Review and Plant-protein Network Analysis.

Chickpea is a protein-rich legume increasingly explored as a substrate for functional plant-based ingredients. Chickpea protein hydrolysates (CPHs) and chickpea-derived peptides (CPs), obtained through enzymatic hydrolysis or simulated gastrointestinal digestion, may provide technological and biological properties while supporting the valorization of chickpea fractions and by-products. This review integrates a network analysis of title-abstract terms from 5,728 unique Scopus and PubMed records on plant protein hydrolysates with a systematic review of 72 studies focused on CPH production, peptide characterization, bioactivity, and translational gaps. The evidence indicates that CPHs and CPs show promising antioxidant, antihypertensive, antidiabetic, anti-inflammatory, lipid-lowering, immunomodulatory, antimicrobial, and anticancer-related activities, mainly supported by biochemical assays, cell models, and animal studies. However, heterogeneous hydrolysis protocols, incomplete peptide characterization, inconsistent bioactivity methods, limited scale-up evidence, and the absence of human intervention trials restrict translation. Future studies should prioritize standardized protocols, mechanistic validation, bioavailability, sensory and regulatory assessment, food-matrix validation, and clinical trials.

Cicer↗

PubMed2026

Targeting Gasdermins for Therapeutic Interventions in Central Nervous System Injury.

Central nervous system (CNS) injuries are the leading cause of permanent disability and premature death in adults worldwide, with their incidence continuing to rise amid social development. These injuries not only severely impair the quality of life but also impose a heavy burden on the global public health system. Current clinical interventions, such as decompression and thrombolysis, can alleviate primary injury but fail to effectively reverse the secondary neuroinflammatory damage. Traditional anti-inflammatory therapies, which cannot block the upstream source of the inflammatory cascade, have led to repeated failures in global clinical translation research over the past decades. Gasdermins were first characterized in studies of systemic inflammatory diseases. These proteins form transmembrane pores to drive the release of proinflammatory factors and inflammatory cell death, serving as key mediators of host innate immunity. Recent studies have revealed that gasdermins play critical roles in regulating the initiation and amplification of neuroinflammation following CNS injury. To clarify the therapeutic potential of gasdermins as targets for injury repair, this review systematically summarizes the structure and function of gasdermins, as well as their cell-specific activation and regulatory mechanisms. We further elaborate on their pathological roles in these injuries and the corresponding therapeutic strategies, aiming to provide a theoretical reference for basic research and clinical translation in this field.

Humans↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗

PubMed2026

Efficacy of pharmacological and microbiota-based therapies in preclinical models of autism spectrum disorder: a systematic review.

BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition in which pharmacological and microbiota-targeted interventions are emerging as promising therapeutic avenues. Animal models are the main tool to investigate etiology, molecular mechanisms and screening for pharmacological therapies. Methodological differences, outcome measure variability, incomplete reporting, biological confounders, and overgeneralization of the results made evaluating innovative pharmacological agents challenging. These limitations in the field highlight a need for systematic and standardized research to reliably assess and translate pharmacological interventions from ASD animal models to human clinical relevance. SUBJECTS: This systematic review synthesized efficacy evidence for pharmacological and microbiota-based therapies across established ASD animal models. RESULTS: We identified 52 recent (2010-2025) studies that reported key ASD behavioral outcomes after pharmacological or microbiota-focused treatments. Interventions were grouped into therapeutic classes - including oxytocinergic agents, E/I balance therapeutic targets, metabolic drugs, cannabinoids, purine-based interventions and emerging targets - alongside microbiota-directed strategies such as probiotics, prebiotics, and fecal microbiota transplantation. By integrating effect directions and robustness across models, we identified most potential drug candidates, evaluated the efficacy of novel strategies, and recognized critical translational gaps. The reviewed studies demonstrate that ASD-like behavioral deficits in preclinical models can be modulated through interventions targeting diverse biological systems, including neurotransmission, neuroinflammation, metabolism, and the gut-brain axis. CONCLUSIONS: These findings support the multifactorial nature of ASD pathophysiology which arises from a network of interacting systemic processes rather than a single molecular defect. It could explain the limited success of traditionally narrowly targeted interventions and suggest a paradigm shift into a more systemic approach.

Animals↗

PubMed2026

Effects of acute resistance exercise on prefrontal oxygenation and task-switching performance: Considerations of loading strategies and blood flow restriction.

Although acute resistance exercise (RE) has been proposed to influence cognitive flexibility and underlying neural mechanisms, it remains unclear whether these effects vary across loading strategies and whether exercise-induced prefrontal hemodynamic responses translate into cognitive outcomes. The present study examined (1) prefrontal cortex (PFC) oxygenated hemoglobin (O2Hb) responses across exercise sets and conditions, (2) the effects of low-load (LL), LL with blood flow restriction (BFR), and high-load (HL) RE on task-switching performance, and (3) whether exercise-related PFC O2Hb responses were associated with pre- to post-exercise changes in task-switching performance. Thirty physically active adults completed three randomized, counterbalanced RE conditions consisting of four sets of barbell squats. LL was performed at 30% one-repetition maximum (1RM) with and without BFR, whereas HL was performed at 70% 1RM. Cognitive flexibility was assessed pre- and post-exercise using a modified Stroop task, indexed by switch-cost reaction time (RT) and accuracy. PFC O2Hb was assessed using functional near-infrared spectroscopy during exercise and expressed as changes from the resting baseline for each set (Sets 1-4). PFC O2Hb increased across sets, rising from Set 1 to Set 3 before plateauing, with no differences observed across conditions. Switch cost RT and accuracy did not improve from pre- to post-exercise, and no differences across conditions were detected. PFC O2Hb during the final set was not associated with changes in switch cost. These findings suggest that although acute RE elicits robust increases in prefrontal hemodynamic activity, such responses may not translate into acute improvements in cognitive flexibility.

Humans↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans↗