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PubMed2026

Closed-loop vasopressor systems for hemodynamic control in perioperative and critical care settings: a systematic review and meta-analysis.

Maintaining mean arterial pressure (MAP) within a predefined target is central to haemodynamic management in surgical and critically ill adults receiving vasopressors. Closed-loop vasopressor (CLV) systems automate titration to optimise blood pressure control, but their clinical effectiveness remains uncertain. We performed a systematic review and meta-analysis comparing CLV with manual titration. This PRISMA 2020-compliant review was prospectively registered in PROSPERO (CRD420250655697). MEDLINE, Embase, Scopus, Web of Science, CENTRAL, and the Cochrane Library were searched (January 2000-June 2025). Randomised controlled trials enrolling adults receiving vasopressors in perioperative or intensive care settings were included. Primary outcomes were time within the MAP target range and time spent in hypotension or hypertension. Risk of bias was assessed using RoB 2.0 and certainty of evidence using GRADE. Random- or fixed-effects models were selected according to heterogeneity. Six randomized controlled trials (215 patients) were included in the systematic review, whereas five perioperative trials contributed to the meta-analysis of haemodynamic control outcomes, and one ICU-based study was summarized narratively because it did not report comparable MAP control endpoints. CLV increased time within the MAP target range (mean difference [MD] 33.94%, 95% CI 20.41-47.46; I2 = 77%) and reduced time in hypotension (MD - 18.24%, 95% CI - 28.95 to - 7.53; I2 = 73%). There was no significant difference in time in hypertension, cumulative norepinephrine dose, or major/minor adverse events. ICU length of stay was not pooled because of clinical and methodological heterogeneity. Certainty of evidence ranged from low to high (moderate for haemodynamic control outcomes). CLV systems improved haemodynamic control, primarily in perioperative settings, but heterogeneity and small samples limit confidence in effect size and generalisability. Evidence in critically ill populations remains limited, and larger trials are needed to determine whether improvements in these physiological surrogate endpoints translate into meaningful patient-centred outcomes.

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

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

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↗
PubMed2026

LitCTL1: A novel C-type lectin involved in the mucosal and cellular immunity of the common periwinkle Littorinalittorea.

C-type lectins (CTLs) are vital pattern-recognition receptors (PRRs) that mediate innate immune responses in mollusks, yet their characterization in Caenogastropoda, the largest gastropod group, remains limited. This study characterizes LitCTL1, a novel secreted single-domain C-type lectin from the common periwinkle, Littorina littorea. The 199-amino acid polypeptide contains a conserved carbohydrate recognition domain with canonical QPD and WND motifs and is predicted to form a homodimer. Uniquely, LitCTL1 was localized in both circulating hemocytes and mucus-secreting epithelial cells of the foot, mantle, and hypobranchial gland - the first report of such dual localization for a molluscan lectin, linking systemic and mucosal defense. Expression analysis revealed that LitCTL1 is constitutively expressed in hemocytes. Functional assays with recombinant LitCTL1 demonstrated its role as a potent opsonin with hemagglutinating activity, significantly enhancing hemocyte spreading and the phagocytosis of zymosan. Genomic analysis reveals that LitCTL1 belongs to a rapidly diversifying, genus-specific expansion distinct from conserved perlucin-like lineages. These results identify LitCTL1 as a key effector molecule in both systemic and mucosal innate immunity, likely reflecting an evolutionary adaptation to the microbial challenges of the intertidal environment.

Animals↗
PubMed2026

Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.

BACKGROUND: Psychological interventions for patients with breast cancer often overlook the critical role of maladaptive attributional style in shaping their adjustment. Therefore, the need for theory-driven, scalable interventions that target cognitive restructuring, particularly during the vulnerable post-diagnosis period, is clear. OBJECTIVE: To evaluate the effectiveness of a nurse-led attribution remodeling training intervention grounded in the Neuman systems model for improving resilience, adaptive coping, and attributional style among women newly diagnosed with breast cancer. DESIGN: A randomized controlled trial. SETTING: A tertiary general hospital. PARTICIPANTS: A total of 130 eligible women newly diagnosed with breast cancer were recruited between March and November 2024. METHODS: A two-arm parallel-group randomized controlled trial was conducted. Participants were randomly assigned to receive either attribution remodeling training plus routine nursing (n = 65) or routine nursing only (n = 65). The nurse-led attribution remodeling training intervention, delivered via a blended model of in-person sessions and continued support through the WeChat mobile platform, was designed to systematically reshape maladaptive attributions into more adaptive ones. Resilience (primary indicator), coping strategy (i.e., confrontation, avoidance, resignation), and attributional style (secondary indicators) were assessed at baseline and at 1, 3, and 6 months post-baseline. A linear mixed model was used to analyze the effects of group, time, and group-by-time interactions. Effect sizes (Cohen's D) were calculated based on the means and standard deviations. RESULTS: At the 6-month follow-up, the intervention group had better outcomes than the control group in terms of resilience (mean difference: 1.49, 95% confidence interval: 0.37, 2.61), confrontation coping (3.35 [2.33, 4.37]), and adaptive attributional style (4.16 [3.87, 4.45]). Avoidance coping showed a small increase (0.82 [0.22, 1.42]), whereas resignation coping decreased (-1.66 [-2.49, -0.83]). Group effects and group-by-time interactions were statistically significant for all outcomes. Effect sizes at 6 months ranged from small for resilience (D = 0.28) and avoidance coping (D = 0.26) to moderate for confrontation coping (D = 0.60) and resignation coping reduction (D = -0.51), and large for attributional style (D = 0.94). CONCLUSIONS: Attribution remodeling training is a promising and effective theory-based intervention that can enhance psychological adaptation in women newly diagnosed with breast cancer. By strengthening key defense mechanisms, as conceptualized by the Neuman systems model, the program is effective, scalable, and nurse-deliverable for psycho-oncology care, bridging a critical gap in supportive cancer care and empowering nurses as primary psychological support providers. REGISTRATION: ChiCTR2000031827, registered prospectively on April 11, 2020, www.Chictr.or.cn.

Humans↗
PubMed2026

Systemic biomarkers of treatment response to methotrexate in people with painful knee osteoarthritis: A biological substudy of the PROMOTE randomised controlled clinical trial.

OBJECTIVE: Stratification of therapeutic responses may help identify efficacious therapies for osteoarthritis (OA). In the PROMOTE randomised trial, participants with elevated baseline high-sensitivity C-reactive protein (hs-CRP) showed greater pain reduction after methotrexate treatment. We set out to interrogate a broader panel of serum/plasma inflammatory response markers relevant to methotrexate actions as potential biomarkers of therapeutic effect. Our objectives were to: (i) characterize changes in these systemic markers during methotrexate treatment; determine whether (ii) baseline levels or (iii) changes in any marker during treatment were associated with treatment response; and (iv) compare these findings with the more established clinical inflammatory marker, hs-CRP. DESIGN: Plasma/serum samples from participants in PROMOTE's biological substudy were analysed for 35 inflammatory markers at baseline (pre-treatment) and at 6-months (post-treatment), by MesoScale V-plex multiplex assay. Those with paired biological and clinical data at both baseline and 6-months were included in the substudy analysis set. Relationships between markers and overall data structure were assessed by Pearson correlation and Principal Component analysis. Associations between markers (baseline levels or change over time) and change in average knee pain severity in past week (numerical rating scale, NRS) were evaluated by univariable linear regression, adjusting for baseline age, sex, and body mass index. Least Absolute Shrinkage and Selection Operator (LASSO) regression with bootstrap resampling enabled marker selection. Benjamini-Hochberg correction adjusted for multiple testing (Padj). RESULTS: 87 participants with paired blood marker and clinical data were eligible for substudy analysis. 18/35 markers were quantifiable and analysed. Systemic IL-8 and TNF-α levels decreased (Padj=0.015, 0.048 respectively) while IL-15 increased (Padj=0.033) with methotrexate treatment over 6-months. Analysing within this active treatment randomised arm, higher baseline IFN-γ was associated with greater reduction in NRS pain change (0.66 [0.01, 1.31], P=0.047), as was decreasing TNF-α over 6-months (2.25 [0.00, 4.5], P=0.049). LASSO identified higher IFN-γ, lower plasma IL-15 and IL-16, and younger age as the most important baseline predictors of pain improvement. hs-CRP was highly selected by LASSO for treatment response in both arms. In a secondary univariate treatment arm-by-biomarker interaction analysis, of the 19 markers, only hs-CRP showed consistent effects in adjusted models (at baseline, coeffic. 2.34 [0.53, 4.15], P=0.001; change over 6-months, (0.36 [0.06, 0.66], P=0.018). CONCLUSIONS: Blood measurement of IFN-γ, TNF-α, IL-15 and IL-16 as well as hs-CRP could act as potential markers to stratify the treatment response by average knee pain to methotrexate in knee osteoarthritis.

Humans↗
PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

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

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

A Letter Matters: ADRB2 rs1042713 c.46A Modulates Anti-osteogenic Effect of Epinephrine in Human Mesenchymal Stem Cells.

Osteoporosis (OP) is a systemic bone disease affecting millions worldwide, characterized by long-term asymptomatic development that manifests in low-energy fractures. Due to their high stability, genetic markers represent a promising strategy for early diagnostics. The ADRB2 rs1042713 polymorphism is one such marker, considered as a potential predictor for OP. Although the anti-osteogenic role of the β2-adrenergic receptor is well-established, debate continues on which allele (G or A) of this polymorphism drives bone deterioration. In this study, we examined the influence of the ADRB2 rs1042713 G/G and A/A variants on osteogenic differentiation in patient-derived mesenchymal stem cells (MSCs) under treatment with the endogenous agonist epinephrine. We show that epinephrine (whose levels are often elevated in comorbid conditions) drastically impairs osteogenic differentiation, specifically at the matrix mineralization stage in MSCs A/A. Epinephrine fails to activate the canonical β2-adrenergic receptor pathway and promotes receptor perinuclear and nuclear localization in MSCs A/A. Crucially, metformin, a common anti-diabetic drug, rescues this anti-osteogenic effect. These results open new perspectives for early diagnostics by identifying epinephrine sensitivity as a critical factor, while also suggesting a potential therapeutic strategy to counteract epinephrine detrimental effect in individuals carrying the ADRB2 rs1042713 A-allele.

Humans↗
PubMed2026

Epigenetic Gene Networks Governing Immune State Transitions Across the Lifespan.

Immune function across development, tissue repair, aging, and disease depends not only on signaling pathways but also on epigenetic architectures that determine whether coordinated transcriptional programs can be accessed and resolved. Increasing evidence indicates that epigenetic gene networks regulate the accessibility and reversibility of semi-stable immune states, shaping plastic, homeostatic, reparative, and degenerative configurations. We propose the concept of epigenetic transition windows, defined as temporally and contextually restricted intervals during which epigenetic constraints are relaxed, permitting coordinated and reversible transitions between immune states. During development, these windows are broad and support immune tolerance and adaptive plasticity. In adulthood they become spatially and temporally restricted, preserving stability while enabling conditional adaptation. With aging, they progressively narrow, contributing to chronic inflammation, impaired repair, and increased vulnerability to neurodegeneration. Conversely, pathological persistence of regulatory permissiveness may underlie immune evasion and sustained plasticity in cancer. We outline operational genomic readouts for quantifying transition windows, including chromatin accessibility variance, enhancer switching dynamics, reversibility metrics, and cross-cell coordination indices, and derive experimentally testable predictions that distinguish this model from pathway-centric or damage-centric explanations. By reframing immune dysfunction as a failure of regulated state transition rather than excessive signaling alone, this framework integrates inflammaging, trained immunity, immune resolution failure, and tumor immune escape within a unified regulatory architecture and provides a systems-level perspective on immune adaptability across the lifespan.

Epigenesis, Genetic↗
PubMed2026

Context matters: coordinated transcriptional regulation and root plasticity under multinutrient conditions.

Plants often encounter simultaneous imbalances in multiple nutrients, but the regulatory logic coordinating their responses remains poorly understood. We aimed to uncover shared transcriptional programs and regulatory nodes underpinning multinutrient adaptation in Arabidopsis thaliana roots. We analyzed publicly available RNA-seq datasets spanning 15 nutrient and beneficial element conditions using differential expression, co-expression network (WGCNA), and gene regulatory network analysis. Selected transcription factors (TFs) were validated via root phenotyping, suberin staining, and ionomic profiling under two-nutrient stress conditions. We identified a core set of 2050 genes responsive to multiple nutrient treatments, enriched for suberin biosynthesis, and structured into modular co-expression clusters. Eight prioritized candidate TFs (ARR10, GBF3, HHO5, NAC32, NF-YA3, NF-YB2, SARD1, and WRKY33) were shown to modulate root system architecture under specific nutrient combinations. WRKY33 and NF-YB2, in particular, regulated nutrient-responsive suberin deposition and ionomic plasticity. These findings reveal suberin remodeling as a shared downstream process in multinutrient responses and suggest that plasticity is not a fixed trait but a modular, polygenic, and context-dependent outcome. Repurposed TFs with pleiotropic functions coordinate structural and physiological traits, providing regulatory entry points for improving nutrient resilience.

Plant Roots↗
PubMed2026

Efficacy of a self-guided online resilience intervention for improving mental health among university students: A randomized controlled trial.

Epidemiological data indicates that university students are an at-risk population for the development of mental disorders. Online interventions have been proposed as promising tools for reducing barriers to treatment and establishing easily accessible health-care services promoting mental health and resilience. This study investigated the efficacy of a Learning Management System (LMS)-based self-guided online resilience intervention. 216 university students took part in a randomized controlled trial with an intervention and a waitlist control group and three measurement points (pre, post and follow-up). We conducted per-protocol (PP) and intention-to-treat (ITT) analyses with mental distress as primary outcome, and self-reported resilience and resilience factors as secondary outcomes. Further, attitudes towards online interventions, adherence, satisfaction and possible negative effects were explored. Satisfaction with the intervention was high and PP analyses (n = 150) revealed significant improvements in mental distress and self-compassion at post-test and acceptance at follow-up. No favourable effects were found for self-reported resilience and resilience factors. Adherence was low and ITT analyses revealed no significant effects. Overall, the study provides preliminary evidence for the LMS-based self-guided online intervention as a potentially valuable tool for university mental health services under optimal adherence conditions. Further research into determinants of adherence is needed to improve intervention reach.

Humans↗
PubMed2026

Influence of microplastics on microalgal performance during wastewater polishing.

Microplastics (MPs) are emerging contaminants that are increasingly accumulating in aquatic ecosystems due to excessive anthropogenic activity and insufficient mitigation strategies, posing serious environmental and public health risks. Their impact on wastewater (WW) treatment processes remains poorly understood. This study evaluated the effects of five MPs commonly found in WW - polypropylene, polystyrene, polyamide, low-density polyethylene, and high-density polyethylene - on the physiology and bioremediation performance of the microalga Chlorella vulgaris in synthetic WW (SWW). Metabolic responses were assessed via esterase activity and intracellular reactive oxygen species (ROS), while nitrogen (N), phosphorus (P), and glucose removal were monitored to evaluate bioremediation efficiency. MPs inhibited esterase activity and elevated ROS levels, indicating oxidative stress. Nevertheless, C. vulgaris maintained a high bioremediation capacity (> 75 % N, > 60 % P, and > 70 % for glucose). Environmental conditions modulated microalga response to MPs exposure. Under N-limited conditions, C. vulgaris exhibited enhanced nutrient uptake and biomass production, but a 12 h/12 h light/dark photoperiod reduced N removal but stimulated glucose consumption via heterotrophic metabolism. In contrast, C-limited conditions exacerbated oxidative stress and compromised nutrient removal, resulting in residual concentrations exceeding legal limits. These findings highlight that environmental factors can either mitigate or exacerbate the physiological stress induced by MPs, ultimately affecting WW polishing. This work provides a comprehensive insight into the cellular and metabolic effects of MPs on microalgae and supports C. vulgaris as a resilient and sustainable approach for nutrient and carbon removal in MP-contaminated WW systems.

Microalgae↗
PubMed2026

Overcoming Immunological Barriers in MSC-Derived Insulin-Producing Cells through CRISPR-Based Hypoimmunogenic Engineering and Translational Perspectives for Type 1 Diabetes.

Mesenchymal stromal cell (MSC)-derived insulin-producing cells (IPCs) represent an emerging strategy for β-cell replacement in type 1 diabetes mellitus (T1DM) owing to their differentiation potential, intrinsic immunomodulatory properties, and lower tumorigenic risk compared with pluripotent stem cell-derived platforms. However, accumulating evidence indicates that differentiation-associated immunogenicity, context-dependent immune recognition, and recurrent autoimmune responses may substantially limit long-term graft survival and therapeutic durability following transplantation. This review critically examines the immunological barriers associated with MSC-derived IPCs, including altered MHC expression, susceptibility to alloimmune and autoimmune-mediated rejection, and potential reactivation of autoreactive immune memory. We discuss the application of CRISPR-based hypoimmunogenic engineering strategies targeting antigen presentation pathways, NK-cell activation, and immune checkpoint modulation to generate more immune-evasive MSC-derived IPCs while preserving β-cell functionality. By integrating insights from T1DM immunopathogenesis, MSC biology, genome editing, and translational immunology, we propose a framework linking immune engineering with controlled differentiation, functional maturation, and long-term safety evaluation. In parallel, we comparatively position MSC-derived IPCs alongside clinically advancing iPSC-derived β-cell platforms to highlight their distinct translational niche, including potential advantages related to safety, immunomodulatory capacity, manufacturing accessibility, and scalability, while acknowledging the superior functional maturity and clinical progression currently demonstrated by iPSC-derived systems. Finally, we discuss key translational challenges, including genomic stability, immune-evasion durability, GMP-compliant manufacturing, and the need for rigorous functional and immunological benchmarking prior to clinical application of hypoimmunogenic MSC-derived IPC therapies in T1DM.

Humans↗
PubMed2026

Glycemic and safety outcomes of the insulin-only bionic pancreas in older adults and individuals with impaired awareness of Hypoglycemia: a post hoc analysis of a randomized pivotal trial.

AIMS: Evaluate the efficacy and safety of iLet Bionic Pancreas (BP) in older adults and individuals with impaired awareness of hypoglycemia (IAH). METHODS: This post hoc analysis used individual participant-level data from the Insulin-Only Bionic Pancreas Pivotal Trial (n = 440; NCT04200313). Eligible participants (n = 96) with type 1 diabetes, aged ≥ 60 years and/or had IAH (Clarke score ≥ 4), were randomized to BP with aspart/lispro (BP-Asp/Lis; n = 45), BP with fast-acting aspart configuration (BP-Fiasp; n = 31), or standard care (SC; n = 20) for 13 weeks. RESULTS: Compared with SC, time-in-range (70-180 mg/dL) significantly increased by 7.49 % (95 % CI: 2.61 to 12.38; ∼1.8 h/day) with BP-Asp/Lis and by 8.28 % (95 % CI: 3.15 to 13.41; ∼2.0 h/day) with BP-Fiasp, driven by reduced hyperglycemia. No significant differences were observed in hypoglycemia exposure. Severe hypoglycemia occurred in four participants (four events) on BP-Asp/Lis and one participant (two events) on SC. One diabetic ketoacidosis event occurred on BP-Fiasp due to an infusion set failure. CONCLUSIONS: In high-risk, clinically vulnerable populations, the BP system significantly improved glycemic control while maintaining safety parity with respect to hypoglycemia risk, providing a resilient therapeutic alternative for vulnerable cohorts.

Humans↗
PubMed2026

The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures: A Systematic Review and Meta-analysis.

BACKGROUND: Current endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopic-based diagnostic sampling for indeterminant biliary strictures remain suboptimal. Artificial intelligence (AI)-based algorithms by means of computer vision in machine learning have been applied to cholangioscopy in an effort to improve diagnostic yield. The aim of this study was to perform a systematic review and meta-analysis to evaluate the diagnostic performance of AI-based diagnostic performance of AI-associated cholangioscopic diagnosis of indeterminant or malignant biliary strictures. METHODS: Individualized searches were developed in accordance with PRISMA and MOOSE guidelines, and meta-analysis according to Cochrane Diagnostic Test Accuracy working group methodology. A bivariate model was used to compute pooled sensitivity and specificity, likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristics curve (SROC). RESULTS: Five studies (n=675 lesions; a total of 2,685,674 cholangioscopic images) were included. All but one study analyzed a deep learning AI-based system using a convoluted neural network (CNN) with an average image processing speed of 30 to 60 frames per second. The pooled sensitivity and specificity were 95% (95% CI: 85-98) and 88% (95% CI: 76-94), with a diagnostic accuracy (SROC) of 97% (95% CI: 95-98). Sensitivity analysis of CNN studies (4 studies, 538 patients) demonstrated a pooled sensitivity, specificity, and accuracy (SROC) of 95% (95% CI: 82-99), 88% (95% CI: 72-95), and 97% (95% CI: 95-98), respectively. CONCLUSIONS: Artificial intelligence-based machine learning of cholangioscopy images appears to be a promising modality for the diagnosis of indeterminant and malignant biliary strictures.

Humans↗