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Abstract Co-fractionation mass spectrometry (CFMS) enables the discovery of protein complexes and the systems-level analysis of multimer dynamics that facilitate responses to environmental and developmental conditions. A major challenge in CFMS data analysis, and omics approaches in general, is the development of reliable benchmarks for accurate evaluation of prediction methods. CORUM is commonly used as a source of benchmark complexes for protein complex composition predictions; however, its assumption of fully assembled subunit pools often conflicts with size exclusion chromatography (SEC) and interaction predictions from CFMS experiments. To address this, we developed an integrative analysis method that leverages cross-kingdom evolutionary conservation among specific CORUM complexes and high-resolution SEC profile data from cell extracts. The resulting benchmark complexes are supported by statistical significance and consistent sizes between calculated and measured apparent masses. The approach was robust, revealing both conserved and species-specific complexes. Designed specifically for benchmark identification, this method can be applied to any species and used to evaluate protein complex predictions from other studies. 

The lack of a unique user equilibrium (UE) route flow in traffic assignment has posed a significant challenge to many transportation applications. The maximum-entropy principle, which advocates for the consistent selection of the most likely solution, is often used to address the challenge. Built on a recently proposed day-to-day discrete-time dynamical model called cumulative logit (CumLog), this study provides a new behavioral underpinning for the maximum-entropy user equilibrium (MEUE) route flow. It has been proven that CumLog can reach a UE state without presuming that travelers are perfectly rational. Here, we further establish that CumLog always converges to the MEUE route flow if (i) travelers have no prior information about routes and thus, are forced to give all routes an equal initial choice probability or if (ii) all travelers gather information from the same source such that the general proportionality condition is satisfied. Thus, CumLog may be used as a practical solution algorithm for the MEUE problem. To put this idea into practice, we propose to eliminate the route enumeration requirement of the original CumLog model through an iterative route discovery scheme. We also examine the discrete-time versions of four popular continuous-time dynamical models and compare them with CumLog. The analysis shows that the replicator dynamic is the only one that has the potential to reach the MEUE solution with some regularity. The analytical results are confirmed through numerical experiments. History: This paper has been accepted for the Transportation Science Special Issue on ISTTT25 Conference. Funding: This research was funded by the United States National Science Foundation’s Division of Civil, Mechanical and Manufacturing Innovation [Grant 2225087]. The work of J. Xie was funded by the National Natural Science Foundation of China [Grant 72371205]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2024.0525 . 

In ultraviolet (UV) radiation–exposed skin, mutations fuel clonal cell growth. The relationship between UV exposure and the accumulation of clonal mutations (CMs) and the correlation between CMs and skin cancer risk are largely unexplored. We characterized 450 individual-matched sun-exposed (SE) and non-SE (NE) normal human skin samples. The number and relative contribution of CMs were significantly different between SE and NE areas. Furthermore, we identified hotspots in TP53 , NOTCH1 , and GRM3 where mutations were significantly associated with UV exposure. In the normal skin from patients with cutaneous squamous cell carcinoma, we found that the cancer burden was associated with the UV-induced mutations, with the difference mostly conferred by the low-frequency CMs. These findings provide previously unknown information on UV’s carcinogenic effect and pave the road for future development of quantitative assessment of subclinical UV damage and skin cancer risk.