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PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗

PubMed2026

Self-healing materials for food packaging: Design principles, activation mechanisms and implications for food safety.

Self-healing materials (SHMs), originally developed to restore mechanical integrity, have recently attracted growing interest in food packaging. By autonomously repairing physical damage, SHMs help preserve packaging integrity, barrier performance, food safety, and shelf-life during storage and transportation. This review summarizes recent advances in the design principles, activation mechanisms, material systems and food packaging applications of SHMs. Key healing strategies, including microencapsulation, dynamic covalent bond exchange, reversible non-covalent interactions and responsiveness to external stimuli such as temperature, pH, and humidity, are discussed. Representative material systems, including biopolymer-based films, hydrogels, nanocomposites, and stimuli-responsive polymers are evaluated with respect to their relevance to packaging animal-derived foods, fruits, and vegetables. Performance evaluation methods, sustainability implications, and food-contact safety concerns are addressed. Despite promising healing efficiency and mechanical resilience, challenges remain regarding production cost, food-grade safety, migration risks, trigger compatibility and stability under fluctuating environmental conditions. Future research should focus on scalable manufacturing, standardized evaluation protocols, repeated damage-healing safety assessment, regulatory compliance, and integration with intelligent packaging technologies.

Food Packaging↗

PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Systematic modular engineering of genome-integrated Escherichia coli MG1655 for high-level 2'-fucosyllactose production.

2'-Fucosyllactose (2'-FL), the most abundant human milk oligosaccharide (HMO), has attracted considerable interest for its prebiotic and immunomodulatory functions, with broad applications in infant nutrition. In this study, we report the development of a high-yield, genome-integrated 2'-FL-producing strain based on Escherichia coli MG1655 through systematic modular optimization. Starting from a single-copy BKHT strain (MGC06), we first optimized the copy number of the α-1,2-fucosyltransferase (α-1,2-FT) gene BKHT. Subsequently, the GDP-L-fucose supply was enhanced through coordinated genomic integration of the gene clusters cpsG-cpsB and gmd-fcl, while the multidrug efflux transporter gene mdfA was integrated to improve product export and strain robustness. BKHT copy number was then re-evaluated in the optimized background, with four copies yielding the highest production. The final engineered strain, harboring all genetic modifications stably integrated into the chromosome, produced 17.18 g/L 2'-FL in shake-flask culture. In fed-batch fermentation using a 5-L bioreactor, this strain achieved a titer of 154.12 g/L after 60 h, with a productivity of 2.57 g/L/h. Notably, throughout the entire fermentation process, no antibiotics or inducers were supplemented, underscoring the genetic stability and regulatory compliance of this plasmid-free system. To our knowledge, this represents the highest 2'-FL titer reported to date, positioning our engineered strain as a promising candidate for commercial 2'-FL production.

Escherichia coli↗

PubMed2026

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

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

Animals↗

PubMed2026

An individualized nomogram for predicting progression-free survival in systemic anaplastic large cell lymphoma: a multicenter, retrospective, and internally validated study.

OBJECTIVES: To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL). METHODS: Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). These were incorporated into a three-factor nomogram, evaluated via bootstrapped internal validation (1000 resamples), ROC analysis, C-index, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: A total of 29 PFS events occurred during a median follow-up of 31 months. Multivariable modelling selected serum β2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice (CHOP versus CHOPE or BV+CHP) as autonomous progression drivers. Upon internal bootstrap validation, the nomogram yielded strong prognostic accuracy, achieving AUCs of 0.81, 0.85 and 0.87 for 1-, 3- and 5-year progression-free survival, alongside a corrected C-index of 0.779 (95% CI: 0.699 - 0.861). Calibration plots showed close agreement between predicted and observed outcomes, while DCA confirmed superior net clinical benefit versus conventional IPI or Ann Arbor stratification across multiple decision thresholds. CONCLUSION: This first sALCL-specific nomogram integrates clinical and treatment variables to provide personalized PFS risk estimation. While internally validated, this exploratory, observation-based tool requires external validation and recalibration in prospective cohorts before clinical implementation.

Humans↗

PubMed2026

Multi‑omics approaches to decipher the molecular mechanisms of exercise‑mediated bone protection: From mechanistic insights to personalized exercise prescription (Review).

The global burden of bone metabolic disorders necessitates a shift from generic exercise recommendations toward personalized prescription strategies. Exercise confers skeletal protection through mechanotransduction, yet the underlying molecular networks remain incompletely understood. Multi‑omics technologies, including transcriptomics, proteomics, metabolomics and single‑cell spatial approaches, have revolutionized the capacity to decode exercise‑mediated bone adaptation at the systems level. The present review synthesizes current single‑omics landscapes and integrative multi‑omics analyses that elucidate the core regulatory networks, mechanobiological coupling mechanisms and multiorgan crosstalk that are implicated in the bone response to mechanical loading. Translational applications across clinical scenarios such as osteoporosis, osteoarthritis and disuse bone loss are evaluated, and the technical, analytical and translational challenges limiting clinical implementation are addressed. Finally, the present review provides a framework for translating multi‑omics molecular signatures into personalized exercise prescriptions for optimized skeletal health.

Humans↗

PubMed2026

Cross-tissue multi-omics integration highlights BPHL and mitochondrial targets in Alzheimer's disease.

BACKGROUND: Mitochondrial dysfunction is a hallmark of Alzheimer's disease (AD), yet specific molecular targets remain to be fully characterized. METHODS: A summary-data-based Mendelian randomization (SMR) framework integrated AD genome-wide association study (GWAS) statistics (39,918 cases) with blood DNA methylation quantitative trait loci (mQTL), gene expression (eQTL), and protein (pQTL) data for 1136 mitochondria-related genes. Associations were assessed using Bayesian colocalization and HEIDI testing. Tissue relevance was evaluated in four brain regions (hippocampus, amygdala, cortex, frontal cortex) using GTEx and external transcriptomic datasets. RESULTS: Screening identified eight candidates supported across blood mQTL and eQTL layers. Stepwise central nervous system (CNS) evaluation singled out biphenyl hydrolase-like (BPHL) as the consistent candidate. Higher genetically predicted BPHL expression was associated with reduced AD risk across the hippocampus (OR=0.920, 95% CI 0.873-0.970), amygdala (OR=0.925, 95%CI 0.880-0.973), cortex (OR=0.943, 95% CI 0.908-0.978), and frontal cortex (OR=0.938, 95%CI 0.901-0.976). These findings aligned with protein-protein interactions connecting BPHL to respiratory complexes and lower BPHL expression in independent AD brains. Functional enrichment converged on oxidative phosphorylation pathways. CONCLUSIONS: By integrating multi-omics data with tissue-specific validation, this study nominates BPHL as a consistent protective candidate in the brain. These findings provide genetic support for mitochondrial molecular perturbations in AD, offering insights for future validation.

Alzheimer Disease↗

PubMed2026

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3↗

PubMed2026

Variants in the interferon regulatory factor 5 gene confer genetic risk for systemic lupus erythematosus in a Han Chinese population.

BACKGROUND: Interferon regulatory factor 5 (IRF5), integral to interferon signaling pathways, has been identified as a susceptibility locus for systemic lupus erythematosus (SLE). Nevertheless, the relationship between IRF5 variants and SLE risk within the Han Chinese demographic remains inadequately characterized. MATERIALS AND METHODS: Genotyping of two functional single nucleotide variants (SNVs) in IRF5 was conducted in 167 individuals with SLE and 246 healthy controls utilizing sequence-specific primer polymerase chain reaction (PCR-SSP). Chi-square and Fisher's exact tests were employed to assess associations. RESULTS: The rs10954213 variant demonstrated a significant association with SLE susceptibility under the recessive model (GG vs. AG+AA, OR = 2.20, 95% CI: 1.30-3.75, p = 0.003, adjusted p [pc] = 0.030) and homozygous model (GG vs. AA, OR = 2.43, 95% CI: 1.36-4.42, p = 0.003, pc = 0.032). Similarly, the rs2004640 variant was associated with an increased risk of SLE across allelic (T vs. G, OR = 1.66, 95% CI: 1.22-2.26, p = 0.001, pc = 0.011), dominant (TG+TT vs. GG, OR = 1.77, 95% CI: 1.19-2.63, p = 0.005, pc = 0.047), and homozygous models (TT vs. GG, OR = 3.72, 95% CI: 1.58-8.78, p = 0.002, pc = 0.016). Haplotype analysis identified protective haplotype HT1 (A/G, OR = 0.54, 95% CI: 0.41-0.73, p < 0.001) and risk haplotype HT4 (G/T, OR = 2.51, 95% CI: 1.42-4.42, p = 0.001). CONCLUSIONS: These findings indicate that IRF5 gene variants substantially modulate susceptibility to SLE in the Han Chinese population. They hold potential as biomarkers for evaluating SLE risk and offer valuable perspectives into disease pathogenesis.

Adult↗

PubMed2026

Association of time-averaged systemic immune-inflammation indices with in-hospital mortality after intracerebral hemorrhage: a retrospective study.

BACKGROUND: Systemic inflammation plays a central role in secondary brain injury following intracerebral hemorrhage (ICH). Although inflammatory indices such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) are linked to poor outcomes, their associations with mortality are commonly assumed to be linear, potentially overlooking nonlinear patterns where mortality risk rises steeply at higher levels. METHODS: We conducted a retrospective study using the MIMIC-IV database, including 440 patients with non-traumatic ICH who were alive and remained in the ICU for at least 72 h after admission. Mean NLR, SII, and SIRI were calculated from measurements obtained during this period. Multivariable logistic regression and restricted cubic spline (RCS) analyses were applied to assess their independent and nonlinear associations with in-hospital mortality. Model discrimination and calibration were internally validated using 1,000 bootstrap resamples. RESULTS: The in-hospital mortality rate was 26.1%. After multivariable adjustment, NLR and SIRI remained independently associated with mortality. Patients in the highest SIRI quartile had the highest risk of death (aOR = 5.12; 95% CI: 2.57-12.24; p < 0.001). RCS analysis revealed a significant nonlinear association between SIRI and mortality (p-nonlinearity < 0.05), showing a steep risk increase at higher SIRI levels. Adding SIRI to the base model provided a modest improvement in discrimination (AUC 0.762 to 0.785, p = 0.045) and significantly improved risk reclassification (cNRI = 0.4778, p < 0.001; IDI = 0.0240, p = 0.0151). CONCLUSIONS: Among patients with ICH who met the 72-hour eligibility criterion, higher 72-hour average SIRI was independently associated with in-hospital mortality. As a time-averaged measure, SIRI should be interpreted as a dynamic marker integrating the initial inflammatory state and the early clinical course rather than as a purely baseline prognostic factor. Although adding SIRI to the base model modestly improved discrimination and risk reclassification, it should be considered a candidate prognostic marker requiring external validation before clinical application.

Humans↗

PubMed2026

Inducible flocculation in Komagataella phaffii enables enhanced biomass separation for biopharmaceutical production.

Biomass separation represents a critical bottleneck in Komagataella phaffii-based biopharmaceutical processes, as typically high cell densities of 40 - 50 % create significant operational, technical and economic challenges for harvest operations. Yeast cell aggregation (flocculation) provides a solution to accelerate cell sedimentation by increasing particle size, thus allowing to improve biomass-supernatant separation efficiency during both natural gravity settling and (continuous) centrifugation operations. This study demonstrates successful engineering of K. phaffii strains with an inducible flocculation phenotype using CRISPR/Cas9-based genome editing to integrate the Saccharomyces cerevisiae FLO1 (ScFLO1) gene under control of various regulatory elements, including methanol-inducible and derepressible promoters. Flocculation strength could be enhanced by implementing transcriptional positive feedback circuits based on the methanol-inducible AOX1 promoter. To address methanol-free production requirements, we developed alternative systems to retrofit PAOX1-based ScFLO1 expression and exploited the derepressible PDF promoter, offering broader compatibility with biopharmaceutical manufacturing facilities. Flocculating cells cultivated in a bioreactor demonstrated significantly improved sedimentation behavior, with considerably lower supernatant turbidity after short low-speed centrifugation or gravity sedimentation compared to non-flocculating controls. Crucially, cell flocculation had no negative impact on product amount and quality when expressing a multivalent NANOBODY® VHH molecule with pharmaceutical relevance. Thus, this work establishes the first genetically engineered flocculation system in K. phaffii compatible with recombinant protein production, providing the basis for an innovative approach to streamline harvest operations in biopharmaceutical processes.

Flocculation↗

PubMed2026

Food-derived extracellular vesicles as delivery platforms for medicine-food homology components in metabolic syndrome.

Diet-induced obesity and associated metabolic syndromes have become major global public health challenge, highlighting the urgent need for safe and effective strategies. Recently, food-derived extracellular vesicles (FDEVs) have garnered increasing attention as natural nanocarriers due to their excellent biocompatibility and specific targeted delivery capabilities. FDEVs can efficiently deliver medicine-food homology components (MFHCs) to precisely regulate lipid metabolism, inflammatory responses, and insulin sensitivity, thereby improving obesity and its metabolic abnormalities. This systematic review summarizes recent advances in the use of FDEVs as delivery vehicles for MFHCs to suppress diet-induced obesity and metabolic syndrome, with a particular focus on the underlying molecular mechanisms, including signaling pathway regulation and cellular metabolic remodeling. In addition, the clinical translational potential and industrial application prospects of FDEVs are evaluated, and key challenges related to preparation techniques, safety assessment, and large-scale production are discussed. By integrating current evidence, this review aims to provide theoretical framework and future perspectives for the development of FDEVs as a novel targeted delivery platform and treatment of metabolic diseases.

Extracellular Vesicles↗

PubMed2026

Feasibility of implementation, diagnostic accuracy, and end-user impact of an electronic health record (EHR)-based ureteral stent tracking tool in a pediatric population.

INTRODUCTION & OBJECTIVES: Ureteral stent tracking systems have reduced stent retention in adults, but their accuracy and impact in pediatrics have been minimally explored. With low event rates in children, such tools may yield high false positives, raising questions on balancing event prevention with provider burden. We aimed to evaluate the feasibility, diagnostic accuracy, and end-user impact of an Electronic Surveillance Tool for Evaluating Nephroureteral stent Tracking (eSTENT) at our institution. STUDY DESIGN: eSTENT, implemented in 1/2024, flags ureteral stents at risk for retention based on implant documentation, expected explant date, and explant documentation. Monthly reports are generated for stents missing explant documentation. We retrospectively evaluated the diagnostic performance of eSTENT from 1/2024-8/2025 at our pediatric hospital. A usability survey including a validated 1-7 implementation score (higher = easier implementation) was distributed to pediatric urologists and operating room nurses. RESULTS: Of 172 cases with ureteral stent placement, eSTENT flagged 28 events (16%) in 24 patients. Of these, 26 represented documentation gaps where explant had been appropriate. Two flags had no documentation of explant, representing near miss events that were identified. No retained stents occurred, consistent with high sensitivity and modest specificity. There were no flags in the last 6 months of the study period. Survey response rate was 100% for surgeons and 55% for nurses. Before eSTENT, stents were not routinely tracked. All surgeons and 93% of nurses reported no added burden, despite occasional misidentification of retained stents. Three surgeons found eSTENT beneficial, four were neutral, and free-text responses generally cited eSTENT's "fail safe" nature as positive. Nurses suggested improvements, including user support and integrated documentation reminders. The average implementation score among both groups was 6/7, indicating easy adoption. DISCUSSION: While the impact of stent tracking tools in adult literature has been positive, our study emphasizes the feasibility of broader adoption at a pediatric hospital. Integration of eSTENT may avoid the potentially devastating consequences of a retained stent. Prioritizing sensitivity over specificity appears acceptable for a "never event" in patient safety. Our study is limited by the retrospective nature of data collection and survey bias. CONCLUSIONS: Though no stents were retained in the study period, eSTENT appropriately flagged two cases without added burden to most end-users. Further optimization is warranted, but adoption in pediatric centers may enhance care reliability.

Humans↗

PubMed2026

Probiotic-derived extracellular vesicles as food-based nanocarriers: Mechanisms, functional applications, and future perspectives in food systems.

Probiotic-derived extracellular vesicles (PDEVs) are a promising type of postbiotic nanoparticle derived by fermentation of probiotics, and have gained growing interest as a potential application in food science and nutrition. These are lipid bilayer vesicles of nanoscale, which are naturally released by probiotic cells and contain a wide variety of bioactive molecules, such as proteins, nucleic acids, and metabolites. Moreover, PDEVs are highly stable, biocompatible, and can be easily engineered to have surfaces with high functionality, which makes them good candidates in functional engineering. In contrast to traditional live probiotics, PDEVs overcome the difficulties of preserving microbial viability during processing and storage, thus providing superior safety, stability, and predictable biological performance. This is a systematic review of the various functions of PDEVs in food systems. We conclude on the processes through which PDEVs control intestinal barrier integrity, alter gut microbiota composition, and alter host immune responses, and their potential to enhance gut health when added to functional foods. In addition to their health-promoting effects, PDEVs have shown significant potential as natural antimicrobial agents to preserve food and as effective nanocarriers of hydrophobic bioactive compounds, including fucoxanthin, to improve their stability, bioavailability, and targeted delivery. Moreover, PDEVs can be used as new regulators of microbial fermentation. However, it should be noted that a lot of the evidence that is available is still preliminary and the effectiveness of these applications in real food-processing and storage conditions has not been fully proven. Although they have potential, there are a number of challenges that still hinder the widespread use of PDEVs in the food industry. These involve the creation of scalable and cost-effective production processes, batch-to-batch consistency, vesicle stability in a variety of food matrices, and regulatory and safety considerations. Other emerging engineering approaches, such as surface functionalization and cargo loading, are also discussed in this review and could further increase the specificity, functionality, and application versatility of PDEVs in food systems. Moving forward, the incorporation of PDEVs into the next generation functional foods, novel food preservation methods, and customized nutrition plans should be prioritized in future studies. Further developments in these fields can make PDEVs useful platforms at the interface of food microbiology, nanotechnology, and human health.

Probiotics↗

PubMed2026

Molecular mechanisms of neuroendocrine regulation of molting in the Chinese mitten crab (Eriocheir sinensis): A transcriptomic analysis based on eyestalk ablation model.

Molting disability severely restricts the sustainable aquaculture of the Chinese mitten crab, yet the neuroendocrine mechanisms coordinating physiological responses remain poorly understood. Using unilateral eyestalk ablation to remove the primary source of molt-inhibiting hormone (MIH), we performed time-resolved transcriptomic profiling of the thoracic ganglion at 24 h (early premolt) and 48 h (ecdysis) post-ablation. We identified 2825 differentially expressed genes and uncovered a biphasic molecular response. At 24 h, the thoracic ganglion activates pathways associated with neuromuscular adaptation, oxidative stress, and cardiac muscle contraction. Notably, the arachidonic acid metabolism pathway is selectively rewired: cytochrome P450 ω-hydroxylases (CYP2J2, CYP4V2) are upregulated, while competing branches (epoxide hydrolase, cyclooxygenase) are suppressed, promoting local synthesis of the potent vasoconstrictor 20-HETE within the thoracic ganglion. This enzymatic switch provides a mechanistic link between MIH withdrawal and the local generation of elevated hemolymph pressure required for molting. By 48 h, the transcriptional program shifts toward chitin-based extracellular matrix remodeling, glycosphingolipid biosynthesis, and synaptic reorganization. Collectively, our findings redefine the thoracic ganglion as an active neuroendocrine integrator that translates reduced MIH signaling into phased physiological outputs, revealing a "neuro-endocrine-hemolymph pressure" regulatory axis. This study provides novel molecular targets (e.g., CYP2J2, CHS1, UGCG) for mitigating molting disability in E. sinensis aquaculture.

Animals↗

PubMed2026

An Update on Inborn Errors of V(D)J Recombination.

V(D)J recombination is the fundamental process by which developing T and B lymphocytes generate diverse antigen receptors, enabling adaptive immunity. This tightly regulated program operates exclusively in lymphoid precursors during G1 phase and depends on the lymphocyte-specific RAG1-RAG2 recombinase to introduce programmed DNA double-strand breaks at recombination signal sequences, followed by repair through the classical nonhomologous end joining (c-NHEJ) pathway. Disruption of any step in this molecular choreography compromises antigen receptor diversity and underlies a spectrum of inborn errors of immunity (IEIs), ranging from severe combined immunodeficiency (SCID) to immune dysregulation with autoimmunity and granulomatous disease. In this review, we place disorders of V(D)J recombination within the broader framework of T-cell development, detailing the temporal waves of recombinase activity, chromatin accessibility, and DNA damage responses that guide thymocyte differentiation. We discuss pathogenic variants affecting the cleavage phase [RAG1, RAG2, and the recently identified RAG cochaperone NudC domain-containing 3 (NUDCD3)], end processing (ARTEMIS), ligation and repair (LIG4, XLF, XRCC4, PRKDC), and genome surveillance pathways (ATM, MRN complex, RNF168), highlighting genotype-phenotype correlations and mechanisms driving immune deficiency and dysregulation. We briefly review recent diagnostic advances, including newborn screening using T-cell receptor excision circles, repertoire sequencing, and functional assays, alongside current therapeutic strategies. Finally, we outline key unanswered questions and argue that continued integration of clinical observation with molecular discovery is essential to improve outcomes and deepen understanding of adaptive immune development.

Humans↗