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    DNA methylation-based forensic framework for age prediction and body fluid identification using nanopore sequencing

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    Forensic DNA phenotyping applies genetic and epigenetic markers to infer biogeographical ancestry, physical appearance traits, and biological age, particularly when conventional methods fail to identify a suspect or victim. DNA methylation, a key epigenetic modification, is especially valuable for age estimation and due to its tissue-specific patterns also for body fluid identification, with the latter aiding in crime scene reconstruction. Current MPS-based methylation sample analyses require time-consuming, multi-step processing, while Nanopore sequencing offers a promising alternative by enabling real-time, direct detection of methylation without DNA conversion. This study evaluates the potential of Nanopore’s PromethION 2 platform for comprehensive, single-assay forensic epigenetic analysis of biological age estimators (epigenetic clocks) and body fluid markers, focusing on relatively low DNA samples (<100 ng.) Our results showed that low read depth coverage can invoke the occurrence of beta values equal to zero and one for the methylation status (whilst methylation has a continuous nature), provide challenges for accurate age estimation and body fluid identification. Our study demonstrates that both the age prediction models tended to estimated older ages than expected; however, applying a proof-of-concept linear correction model significantly enhanced age estimation accuracy. Body fluid identification of blood and saliva was highly accurate in conditions with high and low read depth coverage, correctly identifying 4/4 sample in each experiment. This explorative study highlights the potential of adaptive sampling on PromethION for forensic age prediction and body fluid identification, while future studies should focus on validating analysis thresholds, improving lower-quantity sample performance, advancing body fluid identification models for an extended tissue set, and mixture analysis

    Thiolated hyaluronic acid : a gateway for targeted killing of <i>staphylococcus aureus</i> on the race for surface colonization

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    Hyaluronic acid (HA) is degraded by Staphylococcal hyaluronate lyase (Hysa) and mammalian hyaluronidase (Hyal). Thiolated HA (HAMS) is used as a targeted gateway for Staphylococcus aureus killing while enhancing the previous M23 endolysin–polyphosphate (M23-PP NPs) enzyme-responsive nanoparticle formulation. Synthesis of HAMS and characterization for nuclear magnetic resonance, solubility, thiol content, pKa, and degradation by Hysa and Hyal are presented. Nanoparticles prepared via ionotropic gelation between M23-PP NPs and either HAMS or HA yield M23-PP/HAMS or M23-PP/HA NPs, respectively. Their characterization includes size, zeta potential, morphology, release profiles, safety, targeted release, and efficacy. HAMS with a thiol content of 250.18 ± 90.32 µmol g1g^{−1}, solubility of 50.99 ± 0.02 mg mL1mL^{−1}, exhibits pKa values of 3.2, 4.2, and 8.8. This thiolated polymer irreversibly inhibits Hyal activity, without affecting Hysa. M23-PP/HAMS NPs (265 ± 47 nm, −25 mV) maintain their integrity for seven days at 37 °C, and HAMS coating prevents nonspecific degradation by Hyal, as confirmed by release studies. In a co-culture ‘race for the surface’ experiment with MC3T3 osteoblasts and S. aureus ATCC 25923, M23-PP/HAMS NPs produce 8-log bacterial killing while promoting in vitro wound healing. These findings are pivotal to the development of new enzyme-responsive excipients switchable by S. aureus

    Quasi-fixed points of substitutive systems

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    We study automatic sequences and automatic systems generated by general constant length (nonprimitive) substitutions. While an automatic system is typically uncountable, the set of automatic sequences is countable, implying that most sequences within an automatic system are not themselves automatic. We provide a complete and succinct classification of automatic sequences that lie in a given automatic system in terms of the quasi-fixed points of the substitution defining the system. Our result extends to factor maps between automatic systems and highlights arithmetic properties underpinning these systems. We conjecture that a similar statement holds for general nonconstant length substitutions

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