TY  - JOUR
AB  - Molecular analytics increasingly utilize machine learning (ML) for predictive modeling based on data acquired through molecular profiling technologies. However, developing robust models that accurately capture physiological phenotypes is challenged by the dynamics inherent to biological systems, variability stemming from analytical procedures, and the resource-intensive nature of obtaining sufficiently representative datasets. Here, we propose and evaluate a new method: Contextual Out-of-Distribution Integration (CODI). Based on experimental observations, CODI generates synthetic data that integrate unrepresented sources of variation encountered in real-world applications into a given molecular fingerprint dataset. By augmenting a dataset with out-of-distribution variance, CODI enables an ML model to better generalize to samples beyond the seed training data, reducing the need for extensive experimental data collection. Using three independent longitudinal clinical studies and a case-control study, we demonstrate CODI's application to several classification tasks involving vibrational spectroscopy of human blood. We showcase our approach's ability to enable personalized fingerprinting for multiyear longitudinal molecular monitoring and enhance the robustness of trained ML models for improved disease detection. Our comparative analyses reveal that incorporating CODI into the classification workflow consistently leads to increased robustness against data variability and improved predictive accuracy.
AU  - Eissa, T.*
AU  - Huber, M.*
AU  - Obermayer-Pietsch, B.*
AU  - Linkohr, B.
AU  - Peters, A.
AU  - Fleischmann, F.*
AU  - Zigman, M.*
C1  - 72127
C2  - 56505
CY  - Great Clarendon St, Oxford Ox2 6dp, England
TI  - CODI: Enhancing machine learning-based molecular profiling through contextual out-of-distribution integration.
JO  - PNAS Nexus
VL  - 3
IS  - 10
PB  - Oxford Univ Press
PY  - 2024
SN  - 2752-6542
ER  - 

TY  - JOUR
AB  - The rising humid heat is regarded as a severe threat to human survivability, but the proper integration of humid heat into heat-health alerts is still being explored. Using state-of-the-art epidemiological and climatological datasets, we examined the association between multiple heat stress indicators (HSIs) and daily human mortality in 739 cities worldwide. Notable differences were observed in the long-term trends and timing of heat events detected by HSIs. Air temperature (Tair) predicts heat-related mortality well in cities with a robust negative Tair-relative humidity correlation (CT-RH). However, in cities with near-zero or weak positive CT-RH, HSIs considering humidity provide enhanced predictive power compared to Tair. Furthermore, the magnitude and timing of heat-related mortality measured by HSIs could differ largely from those associated with Tair in many cities. Our findings provide important insights into specific regions where humans are vulnerable to humid heat and can facilitate the further enhancement of heat-health alert systems.
AU  - Guo, Q.*
AU  - Mistry, M.N.*
AU  - Zhou, X.*
AU  - Zhao, G.*
AU  - Kino, K.*
AU  - Wen, B.*
AU  - Yoshimura, K.*
AU  - Satoh, Y.*
AU  - Cvijanovic, I.*
AU  - Kim, Y.*
AU  - Ng, C.F.S.*
AU  - Vicedo-Cabrera, A.M.*
AU  - Armstrong, B.*
AU  - Urban, A.*
AU  - Katsouyanni, K.*
AU  - Masselot, P.*
AU  - Tong, S.*
AU  - Sera, F.*
AU  - Huber, V.
AU  - Bell, M.L.*
AU  - Kyselý, J.*
AU  - Gasparrini, A.*
AU  - Hashizume, M.*
AU  - Oki, T.*
C1  - 71437
C2  - 56163
CY  - Great Clarendon St, Oxford Ox2 6dp, England
TI  - Regional variation in the role of humidity on city-level heat-related mortality.
JO  - PNAS Nexus
VL  - 3
IS  - 8
PB  - Oxford Univ Press
PY  - 2024
SN  - 2752-6542
ER  - 

TY  - JOUR
AB  - In the Arctic, new particle formation (NPF) and subsequent growth processes are the keys to produce Aitken-mode particles, which under certain conditions can act as cloud condensation nuclei (CCNs). The activation of Aitken-mode particles increases the CCN budget of Arctic low-level clouds and, accordingly, affects Arctic climate forcing. However, the growth mechanism of Aitken-mode particles from NPF into CCN range in the summertime Arctic boundary layer remains a subject of current research. In this combined Arctic cruise field and modeling study, we investigated Aitken-mode particle growth to sizes above 80 nm. A mechanism is suggested that explains how Aitken-mode particles can become CCN without requiring high water vapor supersaturation. Model simulations suggest the formation of semivolatile compounds, such as methanesulfonic acid (MSA) in fog droplets. When the fog droplets evaporate, these compounds repartition from CCNs into the gas phase and into the condensed phase of nonactivated Aitken-mode particles. For MSA, a mass increase factor of 18 is modeled. The postfog redistribution mechanism of semivolatile acidic and basic compounds could explain the observed growth of >20 nm h(-1) for 60-nm particles to sizes above 100 nm. Overall, this study implies that the increasing frequency of NPF and fog-related particle processing can affect Arctic cloud properties in the summertime boundary layer.
AU  - Kecorius, S.
AU  - Hoffmann, E.H.*
AU  - Tilgner, A.*
AU  - Barrientos-Velasco, C.*
AU  - van Pinxteren, M.*
AU  - Zeppenfeld, S.*
AU  - Vogl, T.*
AU  - Madueno, L.*
AU  - Lovrić, M.*
AU  - Wiedensohler, A.*
AU  - Kulmala, M.*
AU  - Paasonen, P.*
AU  - Herrmann, H.*
C1  - 69335
C2  - 53855
CY  - Great Clarendon St, Oxford Ox2 6dp, England
TI  - Rapid growth of Aitken-mode particles during Arctic summer by fog chemical processing and its implication.
JO  - PNAS Nexus
VL  - 2
IS  - 5
PB  - Oxford Univ Press
PY  - 2023
SN  - 2752-6542
ER  - 

TY  - JOUR
AB  - Neutralizing antibodies (NAbs), and their concentration in sera of convalescents and vaccinees are a correlate of protection from COVID-19. The antibody concentrations in clinical samples that neutralize SARS-CoV-2 are difficult and very cumbersome to assess with conventional virus neutralization tests (cVNTs), which require work with the infectious virus and biosafety level 3 containment precautions. Alternative virus neutralization tests currently in use are mostly surrogate tests based on direct or competitive enzyme immunoassays or use viral vectors with the spike protein as the single structural component of SARS-CoV-2. To overcome these obstacles, we developed a virus-free, safe and very fast (4.5 h) in vitro diagnostic test based on engineered yet authentic SARS-CoV-2 virus-like-particles (VLPs). They share all features of the original SARS-CoV-2 but lack the viral RNA genome and thus are non-infectious. NAbs induced by infection or vaccination, but also potentially neutralizing monoclonal antibodies can be reliably quantified and assessed with ease and within hours with our test, because they interfere and block the ACE2-mediated uptake of VLPs by recipient cells. Results from the VLP neutralization test (VLPNT) showed excellent specificity and sensitivity and correlated very well with a cVNT using fully infectious SARS-CoV-2. The results also demonstrated the reduced neutralizing capacity of COVID-19 vaccinee sera against variants of concern of SARS-CoV-2 including omicron B.1.1.529, BA.1.
AU  - Rössler, J.
AU  - Pich, D.
AU  - Albanese, M.*
AU  - Wratil, P.R.*
AU  - Krähling, V.*
AU  - Hellmuth, J.C.*
AU  - Scherer, C.*
AU  - von Bergwelt-Baildon, M.*
AU  - Becker, S.*
AU  - Keppler, O.T.*
AU  - Brisson, A.*
AU  - Zeidler, R.
AU  - Hammerschmidt, W.
C1  - 66662
C2  - 53064
TI  - Quantitation of SARS-CoV-2 neutralizing antibodies with a virus-free, authentic test.
JO  - PNAS Nexus
VL  - 1
IS  - 2
PY  - 2022
SN  - 2752-6542
ER  -