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Abstract Background DNA replication progression can be affected by the presence of physical barriers like the RNA polymerases, leading to replication stress and DNA damage. Nonetheless, we do not know how transcription influences overall DNA replication progression. Results To characterize sites where DNA replication forks stall and pause, we establish a genome-wide approach to identify them. This approach uses multiple timepoints during S-phase to identify replication fork/stalling hotspots as replication progresses through the genome. These sites are typically associated with increased DNA damage, overlapped with fragile sites and with breakpoints of rearrangements identified in cancers but do not overlap with replication origins. Overlaying these sites with a genome-wide analysis of RNA polymerase II transcription, we find that replication fork stalling/pausing sites inside genes are directly related to transcription progression and activity. Indeed, we find that slowing down transcription elongation slows down directly replication progression through genes. This indicates that transcription and replication can coexist over the same regions. Importantly, rearrangements found in cancers overlapping transcription-replication collision sites are detected in non-transformed cells and increase following treatment with ATM and ATR inhibitors. At the same time, we find instances where transcription activity favors replication progression because it reduces histone density. Conclusions Altogether, our findings highlight how transcription and replication overlap during S-phase, with both positive and negative consequences for replication fork progression and genome stability by the coexistence of these two processes.

Background and objectives: In progressive multiple sclerosis (MS) patients, CNS inflammation trapped behind a closed blood brain barrier drives continuous neuroaxonal degeneration, thus leading to deterioration of neurological function. Therapeutics in progressive MS are limited. High-dose intravenous glucocorticosteroids (HDCS) can cross the blood-brain barrier and may reduce inflammation within the CNS. However, the treatment efficacy of HDCS in progressive MS remains controversial. Serum neurofilament light chains (sNfL) are an established biomarker of neuroaxonal degeneration and are used to monitor treatment responses. We aimed to investigate whether repeated cycles of intravenous HDCS reduce the level of sNfL in progressive MS patients. Methods: We performed a monocentric observational study of 25 patients recruited during ongoing clinical routine care who were treated with repeated cycles of intravenous HDCS as long-term therapy for their progressive MS. sNfL were measured in 103 repeated blood samples (median time interval from baseline 28 weeks, range 2-55 weeks) with the Single Molecular Array (SiMoA) technology. The Expanded Disability Status Score (EDSS) was documented at baseline and follow-up. Results: The median age of patients was 55 years (range 46-77 years) with a median disease duration of 26 years (range 11-42 years). sNfL baseline levels at study inclusion were significantly higher in progressive MS patients compared to age-matched healthy controls (median 16.7 pg/ml vs 11.5 pg/ml, p=0.002). sNfL levels showed a positive correlation with patient age (r=0.2, p=0.003). The majority of patients (72%, 16/23) showed reduced sNfL levels ≥20 weeks after HDCS compared to baseline (median 13.3 pg/ml, p=0.03). sNfL levels correlated negatively with the time interval from baseline HDCS therapy (r=-0.2, p=0.03). This association was also evident after correction for treatment with disease-modifying drugs (adjusted R2=0.10, p=0.001). The EDSS remained stable (median 6.5) within a median treatment duration of 26 weeks (range 13-51 weeks). Conclusion: Although larger studies are needed to confirm our findings, we were able to demonstrate that HDCS treatment reduces sNfL levels and therefore may slow down neuroaxonal damage in a subgroup of patients with progressive MS. Moreover, a stable EDSS was observed during therapy. Findings suggest that HDCS may be beneficial for the treatment of progressive MS.

It is increasingly apparent that cancer cells, in addition to remodelling their metabolism to survive and proliferate, adapt and manipulate the metabolism of other cells. This property may be a telling sign that pre-clinical tumour metabolism studies exclusively utilising in-vitro mono-culture models could prove to be limited for uncovering novel metabolic targets able to translate into clinical therapies. Although this is increasingly recognised, and work towards addressing the issue is becoming routinary much remains poorly understood. For instance, knowledge regarding the biochemical mechanisms through which cancer cells manipulate non-cancerous cell metabolism, and the subsequent impact on their survival and proliferation remains limited. Additionally, the variations in these processes across different cancer types and progression stages, and their implications for therapy, also remain largely unexplored. This study employs an interdisciplinary approach that leverages the predictive power of mathematical modelling to enrich experimental findings. We develop a functional multicellular in-silico model that facilitates the qualitative and quantitative analysis of the metabolic network spawned by an in-vitro co-culture model of bone marrow mesenchymal stem- and myeloma cell lines. To procure this model, we devised a bespoke human genome constraint-based reconstruction workflow that combines aspects from the legacy mCADRE & Metabotools algorithms, the novel redHuman algorithm, along with 13C-metabolic flux analysis. Our workflow transforms the latest human metabolic network matrix (Recon3D) into two cell-specific models coupled with a metabolic network spanning a shared growth medium. When cross-validating our in-silico model against the in-vitro model, we found that the in-silico model successfully reproduces vital metabolic behaviours of its in-vitro counterpart; results include cell growth predictions, respiration rates, as well as support for observations which suggest cross-shuttling of redox-active metabolites between cells.

Gap formation in the vasculature underpins immune and tumour cell infiltration. Here the authors propose a chemo-mechanical model to analyse how feedback between mechanosensitive signalling, active cellular forces and adhesion governs the breakdown, recovery, and integrity of endothelial junctions.

Abstract Cancer cell extravasation, a key step in the metastatic cascade, involves cancer cell arrest on the endothelium, transendothelial migration (TEM), followed by the invasion into the subendothelial extracellular matrix (ECM) of distant tissues. While cancer research has mostly focused on the biomechanical interactions between tumor cells (TCs) and ECM, particularly at the primary tumor site, very little is known about the mechanical properties of endothelial cells and the subendothelial ECM and how they contribute to the extravasation process. Here, an integrated experimental and theoretical framework is developed to investigate the mechanical crosstalk between TCs, endothelium and subendothelial ECM during in vitro cancer cell extravasation. It is found that cancer cell actin‐rich protrusions generate complex push–pull forces to initiate and drive TEM, while transmigration success also relies on the forces generated by the endothelium. Consequently, mechanical properties of the subendothelial ECM and endothelial actomyosin contractility that mediate the endothelial forces also impact the endothelium's resistance to cancer cell transmigration. These results indicate that mechanical features of distant tissues, including force interactions between the endothelium and the subendothelial ECM, are key determinants of metastatic organotropism.

The model-simulated response of environmental conditions to aerosol perturbations in shallow and deep convective clouds is strongly affected by boundary conditions of the simulation, suggest analyses of idealised and realistic simulations of aerosol-cloud interactions.

Abstract Background Aberrant DNA methylation is a hallmark of cancer cells. However, the mechanisms underlying changes in DNA methylation remain elusive. Transcription factors initially thought to be repressed from binding by DNA methylation, have recently emerged as being able to shape DNA methylation patterns. Results Here, we integrated the massive amount of data available from The Cancer Genome Atlas to predict transcription factors driving aberrant DNA methylation in 13 cancer types. We identified differentially methylated regions between cancer and matching healthy samples, searched for transcription factor motifs enriched in those regions and selected transcription factors with corresponding changes in gene expression. We predict transcription factors known to be involved in cancer as well as novel candidates to drive hypo-methylated regions such as FOXA1 and GATA3 in breast cancer, FOXA1 and TWIST1 in prostate cancer and NFE2L2 in lung cancer. We also predict transcription factors that lead to hyper-methylated regions upon transcription factor loss such as EGR1 in several cancer types. Finally, we validate that FOXA1 and GATA3 mediate hypo-methylated regions in breast cancer cells. Conclusion Our work highlights the importance of some transcription factors as upstream regulators shaping DNA methylation patterns in cancer.

Hydrochemical signatures are often traced back to their original sources using data collected at catchment outlets. However, this approach introduces uncertainties, as signals may add up, cancel each other out, or be subject to transformation processes. Specifically rural point sources, such as communal wastewater treatment plants (WWTPs), are often overlooked and remain poorly understood in terms of their (local) impact, on water quality and quantity dynamics. We equipped a point source‐influenced headwater catchment with a comprehensive measurement setup, to directly trace the different hydrochemical signals. Statistical approaches were used to address c‐Q relationships and hydrochemical drivers for nutrient export upstream, downstream and within the WWTP during baseflow conditions. Groundwater infiltration into the old and leaky sewer system as well as rainwater collected via the combined sewer system were found to significantly alter processes within the WWTP, resulting in highly variable effluent nutrient concentrations. Ammonium introduced by the WWTP is rapidly transformed in the stream, leading to increasing nitrate concentrations further downstream. The combination of processes introduced by the WWTP overlap the dilution and (non‐significant) chemostatic patterns of the upstream nitrate‐discharge relationship, leading to enrichment patterns shortly after, and mainly diluting patterns 290 m downstream of the WWTP. Regarding maximum nutrient concentrations, dry periods during autumn were particularly critical, as the WWTP introduced high ammonium concentrations, which coincided with high nitrate concentrations from the catchment and a minimal dilution potential of the stream. Our study demonstrates the importance of incorporating all nutrient sources into catchment analyses, to facilitate successful management decisions. Plain Language Summary: Monitoring of point sources in rural areas, such as communal wastewater treatment plants, is often not very detailed. This makes it difficult to understand how they affect the water in streams. To fill that research gap, we installed a monitoring system in a rural catchment were a point source is located. We assessed water quality and quantity upstream, downstream and in the effluent. Leaky sewers and infiltrating groundwater probably influence the cleaning processes in the treatment plant, leading to varying nitrogen concentrations throughout the year. The mix of wastewater and upstream water creates a new chemical signal downstream of the wastewater treatment plant. This signal is additionally altered by ammonium, which is quickly transformed into nitrate as soon as it reaches the stream. In the fall, when stream water levels are low and can't dilute the effluent, the highest nitrogen concentration can be measured in the stream. Key Points: The point source alters the dynamics of the nitrate‐c‐Q relationship observed upstream of the WWTP, especially during low flow conditionsGroundwater infiltration into sewer system accounts for >60% of sewer water and can lead to variable water quality of the WWTP effluentHighest catchment NO3‐N concentrations and highest effluent NH4‐N concentrations coincide when stream dilution potential is minimal [ABSTRACT FROM AUTHOR]