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A multiplex DNA microarray chip was developed for simultaneous identification of nine genetically modified organisms (GMOs), five plant species and three GMO screening elements, i.e. the 35S promoter, the nos terminator and the nptII gene. The chips also include several controls, such as that for the possible presence of CaMV. The on-chip detection was performed directly with PCR amplified products. Particular emphasis was placed on the reduction of the number of PCR reactions required and on the number of primers present per amplification tube. The targets were biotin labelled and the arrays were detected using a colorimetric methodology. Specificity was provided by specific capture probes designed for each GMO and for the common screening elements. The sensitivity of the assay was tested by experiments carried out in five different laboratories. The limit of detection was lower than 0.3% GMO for all tests and in general around 0.1% for most GMOs. The chip detection system complies with the requirements of current EU regulations and other countries where thresholds are established for the labelling of GMO.
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http://dx.doi.org/10.1007/s11103-005-6173-4 | DOI Listing |
BMC Glob Public Health
September 2025
Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya.
Background: Between November 2023 and March 2024, coastal Kenya experienced another wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections detected through our continued genomic surveillance. Herein, we report the clinical and genomic epidemiology of SARS-CoV-2 infections from 179 individuals (a total of 185 positive samples) residing in the Kilifi Health and Demographic Surveillance System (KHDSS) area (~ 900 km).
Methods: We analyzed genetic, clinical, and epidemiological data from SARS-CoV-2 positive cases across pediatric inpatient, health facility outpatient, and homestead community surveillance platforms.
BMC Musculoskelet Disord
September 2025
Department of Clinical Sciences at Danderyds Hospital, Department of Orthopedic Surgery, Karolinska Institutet, Stockholm, 182 88, Sweden.
Background: This study evaluates the accuracy of an Artificial Intelligence (AI) system, specifically a convolutional neural network (CNN), in classifying elbow fractures using the detailed 2018 AO/OTA fracture classification system.
Methods: A retrospective analysis of 5,367 radiograph exams visualizing the elbow from adult patients (2002-2016) was conducted using a deep neural network. Radiographs were manually categorized according to the 2018 AO/OTA system by orthopedic surgeons.
Matern Child Health J
September 2025
Maven Clinic, New York, NY, USA.
Background: While it is well established that trying to conceive while experiencing infertility and undergoing fertility treatment is associated with anxiety, little is known about the mental health toll of trying to conceive without fertility treatment. Minimal contact with the healthcare system while trying to conceive without treatment contributes to low rates of detection and support for this population.
Objective: This research aims to provide formative insights into the prevalence of mental health distress and desire for emotional support among people who are trying to conceive without treatment, and how this compares to people who are considering or using fertility treatment.
Metabolomics
September 2025
Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, Toulouse, France.
Introduction: Initially developed for transcriptomics data, pathway analysis (PA) methods can introduce biases when applied to metabolomics data, especially if input parameters are not chosen with care. This is particularly true for exometabolomics data, where there can be many metabolic steps between the measured exported metabolites in the profile and internal disruptions in the organism. However, evaluating PA methods experimentally is practically impossible when the sample's "true" metabolic disruption is unknown.
View Article and Find Full Text PDFNat Aging
September 2025
Aging Biomarker Consortium (ABC), Beijing, China.
The global surge in the population of people 60 years and older, including that in China, challenges healthcare systems with rising age-related diseases. To address this demographic change, the Aging Biomarker Consortium (ABC) has launched the X-Age Project to develop a comprehensive aging evaluation system tailored to the Chinese population. Our goal is to identify robust biomarkers and construct composite aging clocks that capture biological age, defined as an individual's physiological and molecular state, across diverse Chinese cohorts.
View Article and Find Full Text PDF