The research team will develop a series of multivalent nanozyme materials (MOF@Arg@His) to construct a sensing platform with dual-mode colorimetric and fluorescent responses, thereby markedly improving the sensitivity and selectivity for aluminum ion detection. By incorporating machine-learning algorithms, a signal-correction model will be established to enable highly accurate quantification of aluminum ions in complex matrices. Based on a clinical observational cohort, samples of PN raw materials, compounded admixtures, and infant biospecimens will be collected to systematically quantify aluminum exposure levels in preterm infants and to assess the associated risks of relevant complications. Integrating cutting-edge technological innovation with strong clinical applicability, this project aims to build a full-chain "formulation-exposure-outcome" evaluation framework, providing an intelligent detection tool and risk early-warning evidence base to enhance medication safety in neonates.
Study Type
OBSERVATIONAL
Enrollment
250
Aluminum exposure level
Cumulative aluminum exposure from parenteral nutrition will be calculated for each infant based on the measured aluminum concentration in each PN component and the daily administered volume or dose. Exposure will be expressed as μg/kg/day and cumulative μg/kg over the first 4 weeks of postnatal life. Aluminum concentrations will be measured using inductively coupled plasma mass spectrometry, or the actual validated assay used in the study.
Time frame: From birth to 4 weeks postnatal age.
Complications in preterm infants
Incidences of prematurity-related complications such as feeding intolerance, necrotizing enterocolitis, bronchopulmonary dysplasia
Time frame: From birth to 4 weeks postnatal age
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.