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PubMed2026

CRISPR-Cas and Infectious Diseases: A Decade of Translational Advances in Molecular Biotechnology.

CRISPR-Cas systems have emerged as a versatile tool for diagnosing, treating, and preventing infectious diseases. This review highlights translational advancements in CRISPR-Cas-based applications, concentrating on the past decades in diagnostics, therapeutic genome editing, and vaccine development. The article highlights key platforms like DETECTR and SHERLOCK, which enable rapid, sensitive pathogen detection, and explores CRISPR-Cas9 systems in therapeutic strategies for directly targeting viral genomes and combating antimicrobial resistance. It also examines the role of CRISPR-Cas9 in engineering live-attenuated and personalized neoantigen vaccines. Principal findings demonstrate a clear progression from experimental proof-of-concept to preclinical applications primarily in CRISPR-based diagnostics and the engineering of live-attenuated vaccine candidates, whereas translation in CRISPR-based therapeutics and personalized neoantigen vaccines for infectious diseases remains at earlier, more exploratory stages. CRISPR-based diagnostics have progressed further toward clinical evaluation than therapeutics due to delivery and safety constraints, while personalized neoantigen vaccines are included mainly as an emerging, comparative concept for infectious diseases rather than a mature application. This review uniquely integrates CRISPR-based diagnostics, therapeutics, and vaccine development within a single infectious disease framework, critically assesses their current maturity, and systematically highlights technical, regulatory, and ethical barriers alongside realistic future priorities. The review concludes that while CRISPR-Cas holds transformative potential for infectious disease management, significant challenges in delivery efficiency, off-target effects, and ethical regulation must be addressed to ensure safe and equitable clinical translation.

Humans↗

PubMed2026

Mitigating pH-induced instability in deruxtecan-based ADCs: an onboard-mixing icIEF approach for robust charge heterogeneity characterization.

Accurate charge variant analysis of antibody-drug conjugates (ADCs) is essential for understanding product heterogeneity and ensuring quality control. However, Deruxtecan (DXd)-based ADCs present a unique analytical challenge due to the intrinsic instability of the payload, where the lactone ring readily undergoes hydrolysis under alkaline conditions, resulting in time-dependent shifts in charge distribution during imaged capillary isoelectric focusing (icIEF). In this study, we describe the development of an onboard-mixing icIEF method designed to minimize pH-induced degradation during sample preparation. By separating ADC samples from carrier ampholytes (CAs) prior to injection and enabling real-time mixing within the instrument, this approach effectively suppresses premature lactone ring opening and stabilizes charge variant profiles. Comparative studies between conventional premixing and onboard-mixing approach demonstrated that the latter significantly enhances reproducibility, particularly for acidic variants that are highly sensitive to structural conversion. Comprehensive method validation confirmed excellent precision, linearity, and sensitivity, with consistent performance across run-to-run and intra-day analyses. The results underscore the importance of controlling microenvironmental pH exposure in the analysis of chemically instable ADCs. The proposed onboard-mixing strategy provides a robust and efficient solution for icIEF-based characterization, reducing analytical artifacts while simplifying method development. This approach is broadly applicable to ADCs and other biotherapeutics containing pH-sensitive functional groups.

Hydrogen-Ion Concentration↗

PubMed2026

The gonadal matrisome and its correlation with sex change in the ricefield eel Monopterus albus.

The matrisome is a comprehensive list of genes in the genome of an organism, which encodes proteins constituting or interacting with the extracellular matrix (ECM). The gonadal ECM is important for folliculogenesis and spermatogenesis. This study characterized the composition of the matrisome and the expression of matrisome genes in the gonad of ricefield eel, a protogynous sex-changing teleost, during sex change. A total of 838 matrisome genes were identified in the genome of ricefield eel through an in-silico orthology-based approach, of which 482, 443, 429, and 570 matrisome genes were shown to be expressed in the gonads of female (F), early intersexual (EI), mid-intersexual (MI), and late intersexual (LI) fish, respectively. Differentially expressed matrisome genes (DEMGs) were observed across all the sexual stages as well as in each category of ECM components. Analysis of DEMGs in the comparison between EI and F revealed dramatic upregulation of adam8a, mmp9, and s100a11 while downregulation of col4a5, col15a1b, clec3ba, f13a1, and ccl44, which were further confirmed by qPCR analysis. Together, these findings revealed significant changes in the expression of many matrisome genes, particularly three regulator genes, adam8a, mmp9 and f13a1, as female ricefield eels initiate sex change, suggesting that gonadal tissues undergo dramatic remodeling involving the regression of ovarian tissues and the development of testicular tissues to facilitate this process. These data provide valuable resources for further unraveling the roles of matrisome genes in gonadal development of ricefield eel and other vertebrates.

Animals↗

PubMed2026

A streamlined workflow for high throughput metaproteomic analysis of the rumen microbiome.

Metaproteomics can provide direct functional insights into complex microbial communities, yet its application in rumen research remains limited due to labor-intensive and low-throughput sample preparation workflows before the MS analysis. This work aimed to develop and characterize a streamlined, high throughput metaproteomic workflow optimized for rumen samples. Key steps, including microbial cell extraction, cell lysis, protein digestion, and LC-MS/MS acquisition, were systematically assessed and optimized to reduce hands-on time while maintaining deep proteome coverage. The optimized workflow integrates a minimized cell extraction protocol using 0.5 g starting material and in-solution tryptic digestion. Application of the final workflow to 72 samples from in vitro fermentation revealed that biological variability between inocula dominated technical variability, which remained moderate (median CV of 21-24% across batches). Overall, the optimized workflow supports robust taxonomic and functional characterization of the rumen microbiome with improved scalability. These advances provide a foundation for applying metaproteomics to larger experimental designs, including nutritional trials and cohort studies, thereby enabling broader functional interrogation of rumen microbial ecosystems. SIGNIFICANCE: This study addresses current limitations in the application of metaproteomics to rumen microbiome research by developing a streamlined and scalable sample preparation workflow. By optimizing key steps and reducing sample input while maintaining reproducibility and proteome coverage, this work enables more efficient processing of larger sample sets. These advances support the broader use of metaproteomics in rumen studies and facilitate functional investigations relevant to animal nutrition and sustainable livestock production.

Animals↗

PubMed2026

Bacteroides cellulosilyticus-derived 2-hydroxyphenylacetic acid rectifies hepatic lipid homeostasis in MASLD by targeting the PPARγ-CD36 axis.

The gut microbiota plays an important role in the occurrence and development of metabolic dysfunction-associated steatotic liver disease (MASLD), but the specific molecular mechanisms involved have not been fully elucidated. In this study, human cohort studies were performed to identify that the relative abundance of Bacteroides cellulosilyticus (B. cellulosilyticus) was significantly decreased in patients with MASLD. Through the integration of metagenomic and metabolomic analyses, it was confirmed that B. cellulosilyticus and its metabolite 2-hydroxyphenylacetic acid (2HPAA) are key factors regulating the occurrence and development of MASLD. Single-cell sequencing and lipidomic analyses revealed that 2HPAA can enter the liver through the enterohepatic circulation to exert regulatory effects. Specifically, 2HPAA inhibits the peroxisome proliferator-activated receptor γ (PPARγ) signaling pathway, thereby suppressing the expression of the fatty acid transporter CD36. Meanwhile, 2HPAA regulates lipid metabolism in hepatocytes by significantly enhancing palmitate conversion efficiency and inhibiting CD36 palmitoylation. This dual regulatory effect on CD36 expression and palmitoylation can reduce lipid accumulation in hepatocytes and ultimately alleviate MASLD progression. These findings reveal the mechanism by which B. cellulosilyticus and 2HPAA alleviate MASLD by targeting the PPARγ-CD36 pathway. This work provides a new perspective for the study of gut microbiota-host interactions in regulating liver diseases.

PPAR gamma↗

PubMed2026

Muscular fiber properties and multi-omics investigation of larval and adult locomotor muscle in Microhyla fissipes.

During metamorphosis, Microhyla fissipes undergoes a critical transition from an aquatic to a terrestrial lifestyle, accompanied by significant remodeling of skeletal muscle. Notably, larval tail muscle degenerates, while adult hindlimb muscle develops. However, the molecular mechanisms that orchestrate these muscle type-specific adaptations to the changing environment remain unclear. In this study, histological observation, transcriptomics, and metabolomics were integrated to compare locomotor muscles from two stages: larval muscle from tail versus adult muscle from hindlimb. Our results revealed that adult muscle fibers exhibited reduced diameter and shorter sarcomere length compared to those of tadpoles. Transcriptomic analysis identified 4103 differentially expressed genes (DEGs), including 2182 up-regulated and 1921 down-regulated genes. Up-regulated genes were mainly involved in energy metabolism and cellular homeostasis pathways, including PPAR signaling and oxidative phosphorylation, whereas down-regulated genes were associated with carbohydrate metabolism and cell proliferation pathways, such as glycolysis/gluconeogenesis and PI3K-Akt signaling. Metabolic profiling indicated a metabolic shift from anaerobic to aerobic energy production, with 57 differential metabolites identified, mainly involved in protein metabolism and insulin-related pathways. Integrated multi-omics analysis further highlighted the AMPK and FoxO signaling pathways play key roles in this process. In conclusion, our findings demonstrate that the metabolic and structural differences between larval and adult skeletal muscles are mediated by AMPK- and FoxO-dependent signaling pathways, providing novel insights into the molecular mechanisms underlying adaptive development and locomotor transition in anuran amphibians.

Animals↗

PubMed2026

An AI-assisted Clinical Decision Support System for Green Classification of Cystocele on Dynamic Transperineal Ultrasound.

Green classification of cystocele on dynamic transperineal ultrasound (TPUS) remains operator-dependent because it requires manual frame selection and landmark-based assessment of the Valsalva maneuver. We developed a workflow-oriented AI-assisted clinical decision support system for automated urethrovesical junction localization and dynamic Green classification and prospectively evaluated its standalone and reader-support performance. This diagnostic accuracy and reader study included 881 patients from a tertiary referral hospital, comprising a retrospective development cohort (n = 688) and an independent prospective test cohort (n = 193). A nested subset of 67 prospective patients was used for a reader study involving two junior and two intermediate radiologists under unaided and AI-assisted conditions. In the complete prospective test cohort, Green-AttGRU achieved a macro-averaged AUC of 0.939 (95% CI, 0.897-0.971) and an overall accuracy of 0.902 (95% CI, 0.860-0.943). In the reader study, overall accuracy increased from 0.761 to 0.821 without AI to 0.851-0.881 with AI, while macro-F1 increased from 0.660 to 0.777 to 0.820-0.860. Overall inter-reader agreement increased from a Fleiss' κ of 0.453 to 0.786, and pooled median interpretation time decreased from 26.7 s to 9.9 s. These findings support the preliminary feasibility of the system as a workflow-oriented decision-support tool for dynamic TPUS interpretation.

Humans↗

PubMed2026

An allograft inflammatory factor enhances sperm viability by modulating intracellular calcium in oyster Crassostrea gigas.

As an important aquaculture bivalve, the Pacific oyster Crassostrea gigas faces severe constraints in artificial reproduction, where low sperm motility often leads to fertilization failure and limits the sustainable development of the oyster aquaculture industry. In the present study, the variation of sperm from different oyster individuals was observed, and high-quality sperm possessed intact, elongated flagella with no structural abnormalities, while low-quality sperm showed shortened flagella with frequent tangling or coiling defects. Transcriptomic analysis comparing high- and low-quality sperm revealed significantly reduced expression of genes associated with sperm motility and release (CgAIF1, CgAchR, CgSEX), sperm quality and development (CgEP4, CgIFi2b), and cryoprotection (CgISPs) in low-quality sperm. Notably, an allograft inflammatory factor (designed as CgAIF1) encoding EF-hand domain, known as Ca2+ binding activity, was among the most significantly downregulated in low-motility sperm. CgAIF1 is highly expressed in haemocytes, ganglia, and gonads of oysters. Incubation with the recombinant AIF1 protein (rCgAIF1) significantly improved sperm curvilinear velocity, thereby enhancing the overall motility of C. gigas sperm. Furthermore, rCgAIF1 incubation increased intracellular Ca2+ levels (2.13-fold at 30 min, 2.71-fold at 60 min) and superoxide dismutase (SOD) activity (1.44-fold at 30 min, 1.24-fold at 60 min) in sperm, suggesting potential roles in calcium homeostasis regulation and antioxidant defense. In conclusion, this study demonstrates that CgAIF1 significantly enhances motility of oyster sperm, providing a scientific basis for artificial breeding and seed production in oyster aquaculture.

Animals↗

PubMed2026

Rational design of high-productivity perfusion processes for CHO Cells: From growth inhibitory strategies to model-driven optimization.

While perfusion culture for Chinese hamster ovary (CHO) cells offers advantages such as continuous operation and flexibility, it suffers from product loss through cell bleeding and difficulties in reaching high productivity due to sustained rapid cell growth. Growth inhibitory strategies are widely used to enhance productivity in fed‑batch processes; however, their practical implementation and comparative effectiveness in perfusion processes remain insufficiently explored. Meanwhile, process development often relies on costly trial‑and‑error approaches. Here, we systematically compared three growth inhibitory strategies in perfusion culture-low cell‑specific perfusion rate (CSPR), sodium butyrate, and mild hypothermia-with respect to cell growth, metabolism, productivity, and product quality. Genome‑scale metabolic flux sampling analysis revealed that low‑CSPR and sodium butyrate induce a convergent up‑regulation of energy metabolism, correlating with greater gains in specific productivity (qp). Building on this insight, we developed a growth‑kinetic model for the combined low‑CSPR + butyrate strategy, incorporating parameter uncertainty. This model‑guided framework enabled the rational design of two distinct high‑productivity perfusion processes: a sustained mode that achieved robust long‑term stability alongside substantial productivity gains, and a high‑intensity mode that pushed qp and daily volumetric titer to their maxima, with increases of up to 108.94% and 190.36%, respectively, in a model CHO cell line with a moderate baseline productivity. Our study provides a proof‑of‑concept framework for perfusion intensification, from strategy selection to rational process design.

Animals↗

PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗

PubMed2026

Comprehensive identification of carboxylic acids by using bromine isotope-based chemical isotope labelling and structure-guided molecular network.

Carboxylic acids (CAs) are important contributors to the flavor quality of sauce-flavor Chinese Baijiu, yet their comprehensive analysis remains challenging due to poor ionization efficiency, weak chromatographic retention, and limited annotation capability. Herein, we developed a workflow for the high-coverage discovery and annotation of CAs in Baijiu by coupling chemical isotope labeling-liquid chromatography-mass spectrometry with a structure-guided molecular network strategy (SGMNS). A bromine-containing derivatization reagent, 1-(3-aminopropyl)-3-bromoquinolin-1-ium bromide (APBQ), was designed and synthesized to exploit the natural isotope distribution of bromine and characteristic MS/MS fragmentation behavior. Following APBQ derivatization, the target CAs showed superior chromatographic retention and favorable analytical performance. Based on isotopic peak pairing in MS1 and diagnostic fragment validation in MS2, 372 potential CA derivatives were discovered from pooled Baijiu samples and 355 of them were validated by diagnostic fragments in MS2 spectra. To address the scarcity of derivatized spectral libraries, SGMNS was employed for annotation using a background network constructed from APBQ-labeled candidates derived from the Expanded Chinese Baijiu Compound Database. The developed method was further applied to profile Baijiu samples, revealing pronounced differences in CA composition across the seven fermentation rounds. Notably, rounds 3 to 5 exhibited the largest numbers of differential CAs. This study provided an effective analytical strategy for large-scale CA profiling, offering new insight into the chemical basis of flavor formation during multi-round fermentation of sauce-flavor Baijiu.

Isotope Labeling↗

PubMed2026

Cloning of two Hsp70 genes and association analysis between SNP haplotypes and high temperature tolerance trait in red swamp crayfish (Procambarus clarkii).

Aquaculture is suffering the challenge from high temperature climate. Two Hsp70 genes, PcHsp70-1 and PcHsp70-2, as key genes involved in the high temperature tolerance of red swamp crayfish (Procambarus clarkii) were identified and cloned in this study. Their molecular features and expression patterns were characterized, revealing the distinct tissue-specific upregulation expression under high temperature stress (33 °C). Two SNPs, PcHsp70-1 (SNP258) and PcHsp70-2 (SNP555) were examined to associate with high temperature tolerance in three populations (n = 675). The genotypes of PcHsp70-1-SNP258 (GA) and PcHsp70-2-SNP555 (TT) were significantly associated with stronger high temperature tolerance. Notably, individuals carrying the haplotype of Hap I (GG + TT) showed a survival rate exceeding 70% under high temperature stress, whereas, the Hap VIII (AA + CT) showed it at 5.2%. RNA interference of PcHsp70-1 resulted in a significant decrease expression of the gene GSH-Px and its encoding protein (glutathione peroxidase) activity, and damage in intestinal tissue under high temperature stress. The transcriptome result revealed that PcHsp70-1 participates in regulation of the pathways related to cytoskeletal construction, immune response, apoptosis, and antioxidant defense. These findings indicate that PcHsp70 genes are crucial for the cellular stress response under high temperature stress. The developed Kompetitive Allele Specific PCR (KASP) markers provide valuable tools for the marker-assisted selection of high temperature tolerant crayfish varieties, supporting the sustainable development of aquaculture under the challenge of global warming.

Animals↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2026

Psychometric Evaluation of the Breast Inflammatory Symptom Severity Index Versions 2 and 3 Among Lactating Women.

OBJECTIVE: To evaluate the psychometric properties of Versions 2 and 3 of the Breast Inflammatory Symptom Severity Index (BISSI). DESIGN: Secondary data analysis of clinical trial data. SETTING: Private physiotherapy practices, a public tertiary hospital, and a community in Melbourne, Australia. PARTICIPANTS: Women more than 7 days after birth with inflammatory conditions of the lactating breast (N = 43). METHODS: We performed confirmatory factor analysis of the BISSI Version 2 to examine item loading, which informed development of the BISSI Version 3 (V3). We assessed convergent validity by comparing total BISSI V3 scores with human milk sodium to potassium ratio (Na+:K+) at Trial Days 1, 3, and 10 using Bland-Altman plots. We compared item-level scores for size of affected area with objective receiver operating characteristic curve analysis to assess discriminant validity for symptom severity and Cronbach's alpha for internal reliability. RESULTS: After confirmatory factor analysis, we removed two items, resulting in a six-item BISSI V3. All retained items demonstrated comparable loading on the overall scale. Limits of agreement for total BISSI V3 scores and item-level scores for size of affected area were acceptable at all time points, with more than 90% of observations falling within 2 standard deviations of the mean difference, supporting convergent validity. Discriminant validity of the BISSI V3 was supported. We found high internal reliability at both time points CONCLUSION: Our findings provide evidence for the validity and reliability of the BISSI V3 and support its continued development and for clinical use of the BISSI V3 and human milk Na+:K+ analysis to enhance management of inflammatory conditions of the lactating breast.

breastfeeding↗

PubMed2026

Delayed maturation of the milk microbiome in women with type 1 diabetes.

AIMS/HYPOTHESIS: The breastmilk microbiome plays a crucial role in gut microbial colonisation and immune development, but little is known about how it is influenced by type 1 diabetes. METHODS: We conducted a longitudinal 16S rRNA gene sequencing study of milk from women with type 1 diabetes (n=69 pregnancies; 174 samples) and women who did not have type 1 diabetes (n=49 pregnancies; 123 samples), collected at seven timepoints from birth to 15 months postpartum. Alpha diversity (richness, inverse Simpson evenness) was analysed by generalised linear mixed models, beta diversity was analysed by Bray-Curtis dissimilarities and PERMANOVA, and differential abundance was analysed by limma. Additionally, we examined associations with maternal genetic risk score (GRS), maternal HLA type, glycaemic management (HbA1c) and breastmilk secretory IgA (sIgA), and performed a parallel analysis for the infant stool microbiome. RESULTS: A significant interaction between type 1 diabetes status and timepoint was observed for alpha diversity, both richness (p=0.01) and inverse Simpson diversity (p=0.003), indicating distinct temporal trajectories between women with and without type 1 diabetes. In those without type 1 diabetes, richness increased significantly between birth and 1 week postpartum, but this early increase was delayed in women with type 1 diabetes to between 1 week and 3 months postpartum (p=0.002). Beta diversity analysis revealed earlier and more extensive compositional shifts in women without type 1 diabetes compared to those with type 1 diabetes. These differences persisted after adjusting for Caesarean delivery, BMI, parity and infant sex, and were not attributable to a delay in initiating breastfeeding. Taxa with delayed enrichment in women with type 1 diabetes included Streptococcus spp. and Rothia mucilaginosa, which metabolise human milk oligosaccharides to short-chain fatty acids to promote development of the infant's gut barrier and immune system. Maternal GRS, HLA, HbA1c or sIgA were not associated with milk microbiota diversity trajectories. In infant stool samples, alpha diversity did not differ between exposure groups, and showed no evidence of delayed maturation. Beta diversity revealed an early compositional shift between birth and 1 week postpartum only in infants born to women without type 1 diabetes. Similarly, significant taxonomic changes between birth and 1 week postpartum were detected only in infants born to women without type 1 diabetes, but with some taxa differing between exposure groups at 1 week. CONCLUSIONS/INTERPRETATION: Maternal type 1 diabetes is associated with delayed early maturation of the breastmilk microbiome. Early compositional differences in microbiota restructuring were also observed in the infant gut, partially mirroring the pattern in the milk microbiome; however, sustained differences in infant gut microbiota diversity were not detected. Further investigation could determine whether these changes affect development of the infant's gut and immune system.

Humans↗

PubMed2026

Safety of early discharge and abbreviated nimodipine course in patients with good-grade aneurysmal subarachnoid hemorrhage.

Aneurysmal subarachnoid hemorrhage (aSAH) remains a devastating cerebrovascular emergency associated with substantial morbidity and mortality. Current guidelines recommend 14-21 days of inpatient monitoring and a 21-day course of nimodipine following aSAH. This retrospective study evaluates early outcomes early discharge (≤14 days post-ictus) and an abbreviated nimodipine course in highly selected patients with good-grade aSAH managed under a standardized institutional protocol. Consecutive patients enrolled in the Vancouver Ruptured Aneurysm Database (VRAD) at Vancouver General Hospital between 2022 and 2025 were included. Inclusion criteria were good-grade aSAH (WFNS Grade I-III) and discharge home within 14 days of ictus. The primary outcome was re-presentation to emergency care within 30 days of discharge; secondary outcomes included hospital readmission and need for additional treatment. Of 333 total patients in VRAD, 49 patients met inclusion criteria. All patients received ≤ 14 days of nimodipine therapy. Forty-two patients (85.7%) were WFNS Grade I on presentation, 3 (6.1%) were WFNS Grade II, and 4 (8.2%) were WFNS Grade III. Radiographic vasospasm was reported in 18 cases (36.7%). No patients developed DCI or clinical vasospasm. Four patients (8.2%) re-presented to emergency care within 30 days of discharge, and only one patient (2%) required hospital re-admission within 30 days. While radiographic vasospasm was seen in over one third of patients, none developed clinical sequelae, supporting the premise that radiographic vasospasm alone may be insufficient to preclude early discharge in select good-grade patients.

Humans↗

PubMed2026

A versatile reversed-phase liquid chromatography charged aerosol detection method for streamlined monitoring of QS-21 content and stability in liposomal adjuvant formulations.

Identifying and quantifying an active adjuvant along with its degradants in drug formulations is essential for ensuring the safety and efficacy of the drug product. QS-21 is a potent adjuvant that is being evaluated in several clinical trials and is currently formulated in licensed vaccines that protect against shingles, malaria, and RSV. In aqueous environments, QS-21 is subject to hydrolytic degradation that is influenced by pH and temperature, resulting in the formation of a degradant known as QS-21 Hydrolyzed Product, QS-21 HP, which can occur during manufacturing and/or prolonged storage. The intact QS-21 and QS-21 HP induce distinct immune response profiles, making it critical to monitor the degradation of QS-21 in vaccine adjuvant formulations. To date, there has been a paucity of reliable assays for QS-21, its isomers, and degradant QS-21 HP in liposomal adjuvant formulations available that can be transferred seamlessly in quality control (QC) environments. Herein, we introduce a simple and QC-friendly liquid chromatography coupled to a charged aerosol detector (LC-CAD) enabled by stationary phase screening combined with in silico method development optimization. The method exploits 2.7 μm fused-core phenyl hexyl particles, ensuring its versatility in standard and ultra-high pressure LC systems. This approach demonstrates a high correlation between predicted retention time (RT) and experimental outcomes with overall ∆RT < 4%. In addition, this assay shows great linearity, precision, specificity, and accuracy to advance process development characterization of new vaccine formulations.

Liposomes↗