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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

Educational interventions to improve medical students' bad news communication skills: A systematic review and meta-analysis.

OBJECTIVES: This systematic review aimed to both determine whether educational interventions improve medical students' ability and/or confidence in Bad News Communication (BNC), as well as assess the relative efficacy of instructional formats. METHODS: Performed according to the PRISMA guidelines, four databases were searched for articles describing education-based interventions to improve medical student's BNC ability and/or confidence, published in English between 2001 and 2024. Data on students' self-reported or observer-assessed level of competence/ability in BNC (primary outcome), and students' self-assessed confidence in BNC skills (secondary outcomes), were analysed. Meta regression explained the influence of several categorical moderators on heterogeneity in relation to intervention effects on competence/ability. RESULTS: 27 studies met the criteria for inclusion in the systematic review and 17 studies for the meta-analysis. Interventions described in controlled studies were associated with a moderate and significant increase in BNC ability (13 data sets; standardized mean difference [SMD] = 1.09, 95% CI = 0.52 - 1.66). Interventions detailed in pre-post design studies were associated with a significant increase in BNC ability (20 data sets; SMD = 0.92, 95% CI = 0.52 - 1.32), and student confidence/comfort in their BNC skills (12 data sets; SMD = 1.16, 95% CI = 0.57 - 1.75). Subgroup analysis demonstrated better skills/competence outcomes in studies that included simulation-based training (SBT). CONCLUSIONS: Educational interventions improve the BNC ability and confidence of medical students. Interventions should include an SBT element as this leads to greater improvements in BNC ability. Further research is needed to determine to what extent these interventions translate to positive patient outcomes. PRACTICE IMPLICATIONS: Diverse educational programme, especially those including simulation-based training, are effective in improving BNC skills, although the longetivity of these improvements is at present unclear. Therefore, we recommend that refresher courses or practice opportunities should be scheduled throughout students' medical education to ensure retention of BNC skills.

Humans↗

PubMed2026

A framework for delivering real-time, instrument-relative navigation in transoral robotic surgery.

Transoral robotic surgery (TORS) is a minimally invasive, inside-out technique that, compared with traditional open approaches, provides fewer post-operative complications, shorter hospital stays, and improved survival for early-stage head and neck cancer. However, TORS is limited by its steep learning curve and poor visualization of deep tumor margins. This randomized crossover study evaluated a surgical navigation system's potential to enhance accuracy and user experience with real-time, instrument-relative feedback. Seven Teflon beads (d = 2.381 mm) were embedded at the tongue base of a porcine pharynx-and-larynx model. Tongue blade compression and retraction were applied to the model to mimic intraoperative tissue deformation, reproducing the anatomical shifts that occur relative to preoperative imaging. Eight participants used the da Vinci Surgical system to localize the beads by placing pins under two conditions: (a) preoperative computed tomography with no navigation; (b) model-based visual navigation with quantitative instrument-to-target metrics. Surgical accuracy was determined by calculating the target localization error (TLE, pin-to-bead Euclidean distance) and the angular error (AE, pin axis trajectory to bead). Accounting for training level and bead depth, surgical navigation reduced TLE by 5.44 mm (95% CI, 4.02-6.86 mm; p = 2.00e-11) and AE by 8.47 degrees (95% CI, 6.21-10.72 degrees; p = 5.17e-11). Impressions of the system were generally favorable using a 5-point Likert survey and task duration (p = 0.26) or cognitive workload via the NASA-Task Load Index (p = 0.22) were not significantly affected. The navigation system demonstrated translational promise, offering improved target localization accuracy and more consistent performance across experience levels, two critical determinants of surgical quality in TORS.

Robotic Surgical Procedures↗

PubMed2025

Oral semaglutide for weight loss and liver fibrosis in overweight and obesity: A randomized controlled trial.

BACKGROUND AND OBJECTIVES: Obesity is a leading risk factor for fatty liver disease and weight loss has been shown to improve liver parameters. This study evaluates the efficacy of oral semaglutide for weight loss in individuals with overweight or obesity, excluding those with diabetes mellitus. METHODS: A randomized, open-label, controlled trial was conducted at the Asian Institute of Gastroenterology, Hyderabad, from June 2022 to December 2023. Adults (≥ 18 years) with a body mass index (BMI) ≥ 30 or ≥ 27 with comorbidities (pre-diabetes, hypertension, dyslipidemia, obstructive sleep apnea or cardiovascular disease) were randomized into two groups. Both groups received counselling on a reduced-calorie diet and increased physical activity. Group 1 also received oral semaglutide, starting at 3 mg/day and titrated to 14 mg/day over two to four weeks. The objectives were to assess the effects of semaglutide on weight loss, non-invasive markers of liver fibrosis and cardiometabolic parameters. (ClinicalTrials.gov ID: NCT05442450). RESULTS: Total 116 participants (58 per group) completed the study. At 28 weeks, the mean percentage weight reduction was -10.47% (SD 5.3) in the Semaglutide group vs. -2.4% (SD 4.5) in the control group (p < 0.001). Semaglutide treatment significantly improved alanine aminotransferase (ALT) (serum glutamic-pyruvic transaminase [SGPT]) levels, along with reductions in the aspartate aminotransferase to platelet ratio index (APRI) score, liver fat content and liver stiffness. However, NFS (NAFLD fibrosis score) and FIB-4 (fibrosis-4 index) did not show significant reductions. Improvements in BMI, waist circumference, HbA1c, fasting insulin and C-reactive protein (CRP) were significantly greater with semaglutide (p < 0.001). Total fat mass decreased by 7.3 kg vs. 1.74 kg (p < 0.0001) in controls, while visceral fat ratings dropped by 3.67 vs. 0.6 (p < 0.0001). CONCLUSIONS: In adults with overweight or obesity without diabetes, oral semaglutide, combined with dietary and lifestyle modifications, led to significant and clinically meaningful weight loss and metabolic improvements compared to lifestyle modifications alone.

Adult↗

PubMed2026

A single session of high-definition transcranial direct current stimulation does not modulate effects of knee two-point discrimination training or sensorimotor function in healthy adults: Double-blind randomised controlled trial.

BACKGROUND: Benefits of sensory-training interventions on sensorimotor outcomes are inconsistent, and it is unclear whether transcranial direct current stimulation (tDCS) can enhance proprioception, which is fundamental to neuromuscular control. Existing evidence is dominated by upper-limb studies, so transferability to the knee is unclear. This study investigated whether a single session of anodal high-definition (HD)-tDCS, alone or combined with brief two-point discrimination (TPD) training, enhances knee sensorimotor function and performance in healthy adults. METHODS: In a double-blind randomised-controlled trial, 57 healthy participants received (1) 20-min, 1 mA anodal HD-tDCS over the knee primary somatosensory (S1) map or sham stimulation, and (2) 15-min knee TPD training or no training. Knee somatosensory, sensorimotor, and functional performance measures were assessed pre- and immediately post-intervention. Three-way mixed-design ANOVAs, equivalence testing (smallest effect size of interest η2 = 0.02), Bayes factors, and linear mixed-effects models quantified effects. RESULTS: HD-tDCS, TPD training, and their sequential combination had no effect on any outcome measure (p ≥ 0.05; η2 ≤ 0.015). Confidence intervals spanned equivalence bounds, and equivalence testing results were non-significant (p ≥ 0.05). Bayes factors (<0.33) showed moderate evidence for the null (no effect). Mixed-effects modelling attributed ≤8% of total variance to intervention fixed effects, with the remainder captured by participant-level random effects. CONCLUSION: A single 20-minute session of 1 mA HD-tDCS, with or without brief TPD training, does not acutely modify knee somatosensory, sensorimotor, or functional performance in healthy adults. Existing evidence at the hand may not translate to the lower limb. Future work should investigate higher-dose, multi-session, task-concurrent, or network-targeted strategies in clinical populations.

Humans↗

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

Longitudinal Repeated Protein Measurements in a Multiethnic Cohort Identify Novel Diabetes Biomarkers That Reveal Unique Disease Pathways.

There is up to a fourfold increase in diabetes biomarkers identified with longitudinal repeated versus single time point proteomic measurements. The increase in biomarkers identified with longitudinal repeated measurements is supported by a similar proportion being nominated as causal for type 2 diabetes with Mendelian randomization. Proteins unique to the longitudinal repeated analyses highlighted biological pathways (e.g., posttranslational protein modification and cellular structure and cycle regulation) that were distinct from pathways enriched among the shared proteins (e.g., small-molecule metabolic and catabolic processes). Longitudinal protein measurements identify additional novel disease biomarkers and disparate biological pathways compared with single measurement analyses.

Journal Article↗

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

Transcription regulation of cell fate plasticity - from embryonic development to tissue regeneration.

Cell fate plasticity refers to the capacity of cells sharing the same genome to alter, reverse, or reconfigure their identity under physiological, pathological, or experimental conditions. This property underlies embryonic development, cellular reprogramming, and tissue regeneration, but becomes progressively restricted as lineage identity is stabilized. Embryonic development represents an intrinsic process of fate transitions, whereas reprogramming and regeneration reveal how differentiated cells can dedifferentiate or transdifferentiate under specific conditions. Across these contexts, plasticity is governed by multilayered regulatory networks involving transcription factors, epigenetic regulators, cofactors, and the core transcription machinery. Robust regulatory programs stabilize cell identity, whereas stochastic fluctuations in gene expression and chromatin state can prime cells for fate transitions, adding a tunable dimension to plasticity control. In this review, we synthesize recent advances in the regulation of cell fate plasticity across development, reprogramming, and regeneration, highlighting how transcription factors, epigenetic modifications, transcriptional cofactors, and core transcription machinery cooperate to control cell fate decisions and plasticity.

Animals↗

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

Stroke risk following BNT162b2 vaccination: a systematic review and meta-analysis of self-controlled case series studies.

INTRODUCTION: Whether BNT162b2 (Pfizer-BioNTech) vaccination increases stroke risk remains a public health concern. This is the first meta-analysis to synthesize self-controlled case series (SCCS)-derived stroke risk estimates specifically for BNT162b2 vaccination. METHODS: PubMed and Embase were searched from inception through 9 May 2026, following PRISMA 2020 guidelines. Eight eligible SCCS studies were pooled using a random-effects model with restricted maximum likelihood (REML) estimation and the Knapp-Hartung adjustment. RESULTS: Eight studies across six countries encompassing several million vaccinated individuals were included. The pooled incidence rate ratio (IRR) was 0.967 (95% CI 0.892-1.049; I2 = 69.2%), indicating no statistically significant increase in stroke risk. Subgroup analyses showed no evidence of effect modification across continent, risk-window length, dose category, SCCS variant, or age group. CONCLUSIONS: These findings provide no evidence of increased short-term stroke risk following BNT162b2 vaccination at the population level. The observed heterogeneity appeared to be partly driven by methodological differences rather than true biological variation in vaccine effect.

Humans↗

PubMed2026

Temporal proteomic analysis reveals a three-phase adaptation strategy in Phytophthora cinnamomi during salinity stress.

Phytophthora cinnamomi, a highly invasive hemibiotrophic oomycete, threatens global agriculture, forestry, and native ecosystems. Although drought and temperature effects on P. cinnamomi-host interactions are well studied, current knowledge of abiotic stress responses in P. cinnamomi remains largely centered on infection and phytopathology, with limited molecular insight into the pathogen's direct response to salinity independent of its host. To address this gap, we combined growth assays, time-resolved proteomics, and network analysis to define how P. cinnamomi responds and adapts to salinity exposure. Growth assays showed that NaCl-modified agar enhanced mycelial expansion in a concentration-dependent manner, with 100 mM NaCl significantly increasing growth at 48, 72, and 96 h compared with controls, while 50 mM NaCl remained comparable to control conditions. Temporal proteomic analysis of 100 mM NaCl treatment at 0, 1, 6, 12, and 24 h post treatment revealed dynamic shifts in protein abundance. Early induction of ROS (Reactive Oxygen Species)-detoxifying enzymes, including glutathione S-transferases and peroxidases, was consistent with ROS-specific staining assays. Network analysis identified modules enriched for redox regulation, ATP generation, ion transport, and translational control, highlighting multi-layered adaptation to elevated NaCl levels. Notably, clusters of conserved hypothetical proteins were strongly upregulated, indicating unexplored stress tolerance components in Phytophthora species. Here, we propose that P. cinnamomi rapidly activates a three-phase strategy involving metabolism readjustments, redox defenses, and cellular structure alterations under salinity conditions. With increasing soil salinization due to climate change, our study provides first mechanistic insights into P. cinnamomi's adaptive plasticity and ecological resilience to abiotic stress. SIGNIFICANCE: This study represents the first temporal proteomic analysis of salinity stress adaptation in Phytophthora cinnamomi, revealing a sophisticated three-phase adaptation strategy. This research fundamentally advances our understanding of how this globally destructive plant pathogen, P. cinnamomi, maintains environmental resilience. Our findings reveal proteome remodelling as a mechanistic framework for understanding stress tolerance in oomycetes, a group of microorganisms responsible for some of the world's most destructive agricultural and forest diseases. Our results show proteins involved in emergency damage control through metabolic recalibration to sustained adaptation. These findings have relevance for predicting pathogen behavior under climate change scenarios, where increasing soil salinity threatens agricultural productivity while simultaneously enhancing pathogen survival and virulence. Understanding how P. cinnamomi responds to prolonged salinity exposure may inform targeted biocontrol strategies and improve predictive models of disease pressure in salt-affected agricultural regions. The temporal analysis framework we present offers a broadly applicable approach for understanding microbial stress adaptation, with implications extending beyond plant pathology to environmental microbiology and biotechnology applications where stress tolerance is paramount.

Phytophthora↗

PubMed2026

Cationic porphyrin covalent organic framework reinforced hydroxypropyl methylcellulose films for photodynamic-photothermal sterilization and food preservation.

Microbial contamination in food necessitates effective antimicrobial packaging. While cellulose-based packaging materials suffer from limited antimicrobial efficacy, lack of active functionality, and susceptibility to inducing microbial resistance. To address these challenges, this study synthesized a cationic porphyrin-based covalent organic framework (Por-ICOF) as a multimodal photosensitizer. Por-ICOF was uniformly dispersed via non-covalent interaction within hydroxypropyl methylcellulose (HPMC), creating an HPMC/Por-ICOF composite film. This integration enhanced mechanical strength (increased by 26%), hydrophobicity (WCA 71°), and gas barrier properties (OP reduced by 42%, WVP reduced by 36%). Under visible light, the HPMC/Por ICOF film superior absorption generated reactive oxygen species (ROS) and photothermal effects, inactivating 99.2% of Escherichia coli and 99.95% of Staphylococcus aureus within 20 min. The composite film exhibited excellent biocompatibility and effectively extended the shelf life of strawberries. This cationic modification strategy for cellulose-based films offers a novel avenue for the design of high-performance antimicrobial food packaging materials.

Food Preservation↗

PubMed2026

Flux rewiring enables native D-glucosamine production in Escherichia coli.

D-Glucosamine is an industrially important amino sugar used in pharmaceuticals, nutraceuticals, and functional materials, yet its production remains dominated by chemical extraction from chitinous biomass, raising sustainability and allergen concerns. Escherichia coli natively synthesizes D-glucosamine directly from D-glucose through endogenous metabolism, revealing an underutilized amino sugar biosynthetic capability. Building on this native pathway, D-glucosamine production was enhanced through targeted genetic modifications and systematic optimization of nitrogen metabolism and cultivation conditions, reaching 9.2 g L-1 under shake-flask conditions. This work extends a phosphorylation-dephosphorylation strategy previously developed for neutral rare sugars to amino sugar biosynthesis, demonstrating the broader applicability of this metabolic design principle. Phosphatase identity emerged as a key control point for product formation: YbiV was the most effective phosphatase for selective D-glucosamine production, whereas alternative phosphatases redirected flux toward D-sedoheptulose. This enzyme-dependent flux partitioning further enabled tunable co-production of D-glucosamine and D-sedoheptulose. Native amino sugar biosynthesis in E. coli provides a controllable framework for producing chemically distinct sugars through endogenous metabolism and establishes a generalizable strategy for engineering amino sugar and other nitrogen-containing metabolite biosynthesis.

Escherichia coli↗

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↗