Biology subjects

van Dam, T. J.

Publications and source records attributed to van Dam, T. J..

3 recordsLinked to original sources

bioRxiv2026

Real-time heart rate in the wild: remote collection of cardiac data in baboons using a low-power Bluetooth and LoRaWAN system

O_LICardiac rate and rhythm reveal how animals adapt physiologically to day-to-day challenges, with consequences for health and fitness. However, these data remain difficult to collect in wild animals, despite their relevance for individual health and fitness. C_LIO_LIHere, we present a system for collecting and transmitting long-term, fine-scaled physiological data in wild animals. We implanted Bluetooth-enabled cardiac and physiological monitor devices in three wild adult female baboons in the Amboseli ecosystem in Kenya and paired these devices with collars that enabled remote data downloads over long-range wide area network (LoRaWAN). C_LIO_LIThe system performed well over >10 months, providing the first long-term cardiac data in wild primates. The baboons showed strong circadian patterns in heart rate, heart rate variability, and activity. We also present data on one female who left her social group for unknown reasons; while alone she exhibited higher heart rate variability, lower activity, and evidence of disrupted sleep. C_LIO_LIIn sum, physiologgers paired with low-energy methods of remote data retrieval are powerful tools for investigating physiology in wild animals on timescales that extend over many months, with minimal disruption to their behavior. C_LI

zoology↗

bioRxiv2025

Identifying pyrogenic contaminants using transcriptomic profiling of monocyte activation test with machine learning

The monocyte activation test is an in vitro pyrogenicity assessment method that can utilise human peripheral blood mononuclear cells to detect pyrogens in injectable drugs, providing a binary outcome that indicates the presence or absence of a pyrogen. The added ability to distinguish between different types of pyrogens would greatly expand the applicability of the test, for example, by allowing to pinpoint the source of a contaminating pyrogen in pharmaceutical products. Pyrogens activate a unique set of pattern recognition receptors (PRRs), which contribute to inflammation, yielding distinct transcriptomic activation signatures. In this paper, we capture the unique expression signatures of activated monocytes through bulk RNA sequencing and introduce a data preprocessing pipeline that allows the training of a machine-learning model to classify pyrogenic contaminants. Using a dataset of 108 samples stimulated with five classes of PRR agonists, we could differentiate between these classes with more than 97% F1 on test data. We further demonstrate the models capacity to generalise on the previously unseen data using different ligands for the same PRRs as well as heat-killed Escherichia coli and Staphylococcus aureus.

bioinformatics↗

bioRxiv2017

Probabilistic data integration identifies reliable gametocyte-specific proteins and transcripts in malaria parasites

Plasmodium gametocytes are the sexual forms of the malaria parasite essential for transmission to mosquitoes. To better understand how gametocytes differ from asexual blood-stage parasites, we performed a systematic analysis of available omics data for P. falciparum and other Plasmodium species. 18 transcriptomic and proteomic data sets were evaluated for the presence of curated \"gold standards\" of 41 gametocyte-specific versus 46 non-gametocyte genes and integrated using Bayesian probabilities, resulting in gametocyte-specificity scores for all P. falciparum genes.\n\nTo illustrate the utility of the gametocyte score, we explored newly predicted gametocyte-specific genes as potential biomarkers of gametocyte carriage and exposure. We analyzed the humoral immune response in field samples against 30 novel gametocyte-specific antigens and found five antigens to be differentially recognized by gametocyte carriers as compared to malaria-infected individuals without detectable gametocytes. We also validated the gametocyte-specificity of 15 identified gametocyte transcripts on culture material and samples from naturally infected individuals, resulting in eight transcripts that were >1000-fold higher expressed in gametocytes compared to asexual parasites and whose transcript abundance allowed gametocyte detection in naturally infected individuals. Our integrated genome-wide gametocyte-specificity scores provide a comprehensive resource to identify targets and monitor P. falciparum gametocytemia.

microbiology↗