The research, led by Ruizhe Huang, Zhiyi Liu and Yawei Zhao under the correspondence of Siyu Chen at the Department of Medical Oncology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, was built on a strikingly broad computational foundation. The team integrated seven single-cell RNA-sequencing cohorts, two spatial transcriptomic cohorts, bulk RNA sequencing linked to patient survival data, CRISPR-based gene essentiality screens, and three independent immunotherapy cohorts. Rather than relying on any single analytical method, the investigators assembled a machine learning framework in which different algorithms handled different parts of the problem, each feeding its output into the next stage of analysis.

The first step involved unsupervised consensus non-negative matrix factorization, a mathematical technique that decomposes gene expression data into coherent transcriptional programs without any prior labeling. Applied to malignant cells across the cohorts, this approach resolved four distinct malignant meta-programs. One of these, designated MP3, carried a mixed mesenchymal and interferon signaling signature, suggesting tumor cells that had partially undergone epithelial–mesenchymal transition while simultaneously mounting inflammatory responses. Crucially, the researchers found that MP3 carried prognostic information only in the context of the other three programs. When considered in isolation, its signal was misleading; when modeled jointly, patients with higher MP3 activity relative to the other programs fared significantly worse, with a hazard ratio of 1.43 per standard deviation and a p-value of 0.0045.

That context-dependence led the team to construct a composite score, essentially the difference between standardized MP3 activity and the activity of a fourth program, MP4, which resembled healthy alveolar cells and was independently protective. This single composite metric, z(MP3) minus z(MP4), proved prognostic on its own, with a hazard ratio of 1.40 and a p-value of 3.4 multiplied by ten to the negative sixth power. The reciprocal balance between an aggressive, plastic mesenchymal state and a differentiated, alveolar-like state thus encoded clinically meaningful information that neither program revealed alone. It is a technical but important lesson: in tumors defined by cellular plasticity, the relative composition of transcriptional states, not the abundance of any one state, appears to determine patient outcomes.

Having established the malignant programs, the researchers turned to the immune microenvironment and deployed deep generative models to interrogate neutrophils. Using scVI and its supervised extension scANVI, probabilistic models designed to denoise single-cell data and transfer cell type labels across datasets, the team resolved distinct neutrophil states within the tumor microenvironment. What emerged was an OSM-primed neutrophil axis. OSM, or oncostatin M, is an inflammatory cytokine, and neutrophils primed with it appeared to participate in a signaling circuit alongside SPP1-positive macrophages, the very cell population that had dominated prior studies of mesenchymal transition in this cancer. The two cell types formed what the authors describe as a partitioned dual circuit, with neutrophils and macrophages occupying complementary roles in sustaining the mesenchymal niche.

What made this finding particularly compelling was its spatial validation. Single-cell data strips away geography, telling researchers which cells exist but not where they sit within the tumor. To recover that geometry, the team applied cell2location, a probabilistic deep learning method for spatial deconvolution that estimates which cell types and states occupy each spot in a spatial transcriptomics slide. They coupled this with random forest multi-view modeling to map communication fluxes between cell populations. The results showed that OSM signaling flux was directed primarily toward macrophages and fibroblasts rather than toward the malignant cells themselves, which means that any influence of the neutrophil circuit on tumor cells is likely indirect, mediated through the stromal and macrophage compartments. The two-compartment niche, pairing OSM-primed neutrophils with their macrophage and fibroblast partners, was reproducible across both spatial cohorts, strengthening confidence that it reflects genuine tumor architecture rather than computational artifact.

The final and perhaps most ambitious stage of the pipeline used Geneformer, a transformer-based single-cell foundation model pretrained on large corpora of gene expression data, to perform in silico gene deletion perturbations. In effect, the model simulates what happens to a cell’s transcriptional state when a particular gene is removed, allowing researchers to computationally screen candidate dependencies across the three coupled state transitions identified in the study: from alveolar-like to mesenchymal malignant states, and through the associated neutrophil and macrophage circuits. The screen converged on SEC61G, a gene encoding a component of the SEC61 translocon, the protein channel in the endoplasmic reticulum membrane through which secreted and membrane proteins pass as they are synthesized. Because mesenchymal tumor cells and inflammatory immune cells both rely heavily on protein secretion, a translocon dependency is biologically plausible.

The authors are notably careful about how they frame this nomination. SEC61G already had independent published support in lung adenocarcinoma, so the team treats it as a positive control re-derived de novo rather than a wholly new drug target. What they report as genuinely new is that SEC61G’s prognostic signal is independent of 7p11.2 copy number, the chromosomal region in which the gene resides and a region frequently amplified in this cancer. In other words, the poor outcomes associated with high SEC61G expression are not simply a reflection of having more copies of the gene, hinting at regulatory or functional dependencies that copy number analysis alone would miss. The overall survival hazard ratio for SEC61G was 1.64 with a p-value of 1.3 multiplied by ten to the negative sixth, and the gene showed higher expression in immunotherapy non-responders in two of the three checkpoint inhibitor cohorts examined, reaching statistical significance in one.

What elevates this study above a typical bioinformatics exercise is its insistence on orthogonal validation. The four-endpoint validation cascade required convergent evidence from survival analysis, immunotherapy response data, CRISPR essentiality screens, and the perturbation modeling itself before any candidate dependency was accepted. This design directly addresses one of the most persistent criticisms of single-cell oncology research: that computational nominations of drug targets often evaporate under experimental scrutiny. By demanding agreement across data types that share no common analytical machinery, the framework filters out candidates whose signals are artifacts of any single method or dataset. The result is a shorter but far more defensible list of candidate targets than a typical computational screen would produce.

The broader significance lies in the generalizability of the approach. The authors explicitly position their strategy, foundation model perturbation followed by multi-endpoint orthogonal validation, as a reusable template for nominating therapeutic targets in plasticity-driven solid tumors, a category that includes many of the hardest cancers to treat. As foundation models like Geneformer mature and spatial transcriptomic datasets accumulate, pipelines of this kind could compress the path from observational single-cell atlases to testable therapeutic hypotheses. For lung adenocarcinoma patients, the immediate deliverables are a newly mapped neutrophil-associated mesenchymal niche that reframes how the tumor microenvironment sustains aggressive cell states, and a candidate translocon dependency whose vulnerability can now be pursued with experimental tools. The work was funded by the National Natural Science Foundation of China and the Shanghai Committee of Science and Technology, and relied exclusively on publicly available, de-identified human data, meaning that its findings can be independently reanalyzed and challenged by any laboratory with computational resources and internet access.

Subject of Research: Deep learning integration of single-cell and spatial transcriptomics to map a neutrophil-associated mesenchymal niche and identify candidate tumor dependencies in lung adenocarcinoma.

Article Title: Deep learning integration of single-cell and spatial transcriptomics reveals a neutrophil-associated mesenchymal niche and a candidate translocon dependency in lung adenocarcinoma

Article References: Deep learning integration of single-cell and spatial transcriptomics reveals a neutrophil-associated mesenchymal niche and a candidate translocon dependency in lung adenocarcinoma. (n.d.). https://doi.org/10.1007/s00262-026-04560-3

Image Credits: AI Generated

DOI: 10.1007/s00262-026-04560-3

Keywords: lung adenocarcinoma, single-cell RNA sequencing, spatial transcriptomics, tumor-associated neutrophils, epithelial–mesenchymal transition, SEC61G, deep learning, tumor microenvironment, Geneformer, immunotherapy response, OSM signaling, cancer prognosis

The AMOC is not a single current but a planetary-scale circulation powered by differences in temperature and salinity. Warm, salty surface water flows northward, releasing heat to the atmosphere. In the subpolar North Atlantic, cooling increases the water’s density, allowing it to sink and join a deep southward flow. This overturning helps regulate climate around the North Atlantic, influences rainfall and wind patterns, redistributes carbon and heat, and affects sea level and marine ecosystems. A major weakening would not simply mean a slower Gulf Stream; it would represent a reorganization of the climate system with consequences extending across both hemispheres.

Scientists have long known that the AMOC can, in some models, exist in more than one stable state. Under broadly similar external conditions, the circulation may occupy a vigorous “on” state or a much weaker “off” state. The possibility of these alternative equilibria makes the AMOC a potential climate tipping element: a system that can shift abruptly when a gradual change in forcing pushes it beyond a critical threshold. Freshwater entering the ocean is especially important because it dilutes seawater, reduces density, and can interfere with the formation of deep water in the North Atlantic. The resulting slowdown can itself alter salt transport, creating feedbacks that either stabilize or destabilize the circulation.

The new study, by Amber A. Boot of Utrecht University and the Technical University of Denmark and Henk A. Dijkstra of Utrecht University, tests whether earlier findings from a relatively simple climate model also hold in a more detailed ocean model. The researchers compared simulations from CLIMBER-X, an intermediate-complexity Earth system model with a coarse 5-degree ocean grid, with simulations from the Parallel Ocean Program version 2, or POP2. POP2 represents the ocean at a nominal horizontal resolution of 1 degree, includes 40 vertical layers, and incorporates parameterized processes such as mesoscale mixing and overflow in the North Atlantic and Southern Ocean. It is also used as an ocean component in the Community Earth System Model family.

The comparison was designed to isolate the influence of freshwater errors rather than reproduce a perfect modern climate. The researchers established baseline simulations and then imposed artificial freshwater biases in the Indian Ocean, the Atlantic Ocean, or both basins. The perturbations were deliberately large enough to expose the circulation’s response: a change of 1.50 millimeters per day, equivalent to roughly 0.24 to 0.27 sverdrups over the affected regions. One sverdrup represents one million cubic meters of water flowing every second. The added freshwater was balanced elsewhere so that the overall salt budget remained conserved.

The models were then subjected to a controlled “hosing” experiment, in which freshwater was added to the North Atlantic between 20 and 50 degrees north. This forcing was increased gradually until the AMOC collapsed. In the faster experiments, the model was allowed to adjust for 600 years after the bias was introduced, and the freshwater forcing rose at 0.30 sverdrups per thousand years. The researchers also ran slower CLIMBER-X experiments, allowing 10,000 years for adjustment and increasing the forcing six times more slowly. Such long integrations are necessary because ocean salinity and circulation respond over centuries to millennia, and a simulation that appears settled after a few decades may still be evolving internally.

Despite their different resolutions and physical complexity, POP2 and CLIMBER-X produced the same broad result. A negative freshwater bias in the Indian Ocean—effectively making that ocean saltier—tended to weaken and destabilize the AMOC. A positive Indian Ocean bias, which freshened the region, generally strengthened and stabilized it. The Atlantic response was reversed: adding freshwater to the Atlantic tended to weaken the AMOC, while removing it had a stabilizing effect. The researchers traced these responses to how salinity anomalies move through the connected ocean basins and alter the density contrast that helps drive overturning.

The physical chain is counterintuitive. When the Indian Ocean becomes saltier, the anomaly can influence the South Atlantic, changing the density structure there and reducing the north–south density difference across the Atlantic. A weaker density gradient means less pressure-driven overturning. The weakened circulation then transports less salt northward, leaving the North Atlantic fresher and further reducing the density of water available for sinking. In the Atlantic itself, additional freshwater directly lowers salinity and density, making deep convection more difficult. These processes are reflected in the freshwater transport of the overturning circulation across roughly 34 degrees south, a diagnostic measure tied to the salt-advection feedback.

That feedback is central to the study’s warning. Observational estimates generally indicate freshwater export characteristics associated with a destabilizing salt-advection feedback, whereas many climate models simulate the opposite sign. In those models, the feedback helps restore the AMOC after a disturbance, making the circulation appear more resistant to collapse. The discrepancy is linked partly to salinity errors and surface freshwater forcing, including precipitation patterns. One well-known example is the “double Intertropical Convergence Zone” bias, in which models produce two overly strong tropical precipitation bands. Such errors can redistribute freshwater between ocean basins and alter the large-scale salinity field that controls circulation stability.

The simulations did not show that every freshwater bias causes an immediate or inevitable collapse. Instead, the biases shifted the amount of additional North Atlantic freshwater required to reach the tipping point. In POP2, most experiments collapsed under less freshwater forcing than the baseline case. The main exception was the simulation with positive freshwater biases in the Indian Ocean, which required stronger forcing before collapse. The slower CLIMBER-X experiments showed a similar pattern. Some Atlantic-bias cases collapsed in two stages: first, deep convection in the subpolar gyre weakened, then the system entered a weak, oscillating state before a complete collapse under still stronger forcing.

One especially complex result emerged when opposing biases were applied across both the Indian and Atlantic oceans. In the POP2 simulation with negative biases in both basins, the AMOC became unusually variable and then highly sensitive to additional freshwater near a forcing of about 0.155 sverdrups. The researchers linked the behavior to a reorganization of the South Atlantic circulation, including changes in mixed-layer depth, sea-surface temperature and sea-surface salinity. Rossby waves generated near the Mid-Atlantic Ridge grew in amplitude as freshwater forcing increased, while changes in gyre transport amplified the weakening. This case illustrates why the circulation cannot be understood from a single regional salinity value: basin geometry, waves, gyres and density feedbacks can interact in nonlinear ways.

The team also separated the simulated AMOC decline into several mechanisms, including surface freshwater forcing, gyre transport, northern-boundary freshwater transport and the salt-advection feedback. Before the tipping point, direct surface freshwater forcing produced most of the weakening, with gyre changes contributing several sverdrups of additional decline. The salt-advection feedback played only a minor role at first but became the mechanism that drove the final collapse after the threshold was crossed. POP2 differed from a previous Community Earth System Model analysis mainly in the behavior of the gyre feedback, which was more destabilizing before the tipping point. Yet the gyre response was broadly similar among the different freshwater-bias experiments, suggesting that it did not erase the central effect of the biases.

The researchers caution that POP2 is still not a complete Earth system model. It is an ocean-only simulation driven by prescribed atmospheric conditions, and therefore lacks two-way interactions with a dynamic atmosphere and sea ice. In the real world, a weakening AMOC would reduce northward ocean heat transport, potentially expanding Arctic sea ice. More ice could insulate the ocean from the atmosphere, alter heat loss and suppress deep convection. Atmospheric changes in wind, moisture and heat transport could either reinforce or counteract the circulation’s decline. Southern Ocean winds are also important because they drive upwelling and help shape the pathways that connect the Atlantic to the global ocean.

The study likewise does not calculate a precise date or probability for an AMOC collapse. Its experiments use idealized freshwater forcing under preindustrial conditions, while the actual climate is being pushed away from equilibrium by rising greenhouse-gas concentrations. Real-world tipping could involve several processes at once, including gradual forcing, random fluctuations and changes in the background stability of the circulation. Freshwater variability itself may also contain model biases in its amplitude and distribution. The authors therefore present their results as evidence of a structural vulnerability in current modeling rather than as a forecast of imminent collapse.

To help test that vulnerability in more expensive Earth system models, Boot and Dijkstra propose a streamlined experiment. A model would first be run under baseline conditions, then branched before the tipping point. A freshwater bias would be introduced gradually over several centuries, allowing the ocean to adjust without triggering artificial rate-dependent effects. The simulation would then resume increasing North Atlantic freshwater forcing. In their POP2 proof-of-concept, a negative Indian Ocean bias was added over 400 years after a 500-year equilibration period. The modified simulations tipped within decades of renewed forcing and before the unbiased baseline, supporting the proposed protocol.

The broader implication is that model resolution alone may not solve the AMOC problem. The same qualitative response appeared in a coarse coupled model and a substantially more detailed 1-degree ocean model, indicating that the mechanism survives increased ocean complexity. Yet the authors stress that only experiments in fully coupled Earth system models can establish whether the bias pattern consistently makes the AMOC too stable. Until then, projections showing no complete collapse this century should not be interpreted as proof that the risk is negligible. If models are systematically giving the circulation an overly strong safety margin, correcting freshwater distributions could turn a seemingly remote tipping possibility into a more serious climate risk.

The analysis, published in Breast Cancer Research and Treatment, examined 17,201 women aged 67 and older who were diagnosed with screen-detected, estrogen-receptor-positive and HER2-negative breast cancer between 2015 and 2021. The researchers linked cancer-registry information from the Surveillance, Epidemiology, and End Results program with Medicare claims, creating a large real-world cohort rather than a tightly controlled clinical-trial population. Overall, 60.4 percent of the cancers were detected after DBT screening, while 43.6 percent of the women were at least 75 years old when diagnosed. The investigators compared DBT with conventional digital mammography and used multivariable logistic regression to account for measured differences between patients and screening groups.

Digital mammography produces two-dimensional X-ray images in which normal tissue can overlap, sometimes obscuring a tumor. DBT addresses that problem by acquiring multiple low-dose projections as the X-ray tube moves across the compressed breast. Computer reconstruction converts those projections into a stack of thin virtual slices, allowing radiologists to inspect breast structures layer by layer. The technique can reduce the visual clutter caused by overlapping tissue and has shown benefits in studies of women aged 50 to 74, including increased detection of invasive cancers and tumors diagnosed at smaller sizes. But the breast changes with age: glandular tissue generally becomes less dense and more fatty, potentially making conventional mammography easier to interpret and reducing the incremental value of tomosynthesis.

Among women aged 67 to 74, DBT was associated with several signs of more favorable disease compared with digital mammography. The adjusted odds of a smaller tumor were 18 percent higher with DBT, corresponding to an adjusted odds ratio of 1.18 and a 95 percent confidence interval of 1.08 to 1.29. DBT was also associated with a greater likelihood of grade I disease rather than grade II or III disease, with an adjusted odds ratio of 1.14. The odds of node-negative cancer were 15 percent higher, although the confidence interval reached the boundary of statistical significance. In addition, DBT was associated with a 29 percent higher likelihood of invasive lobular carcinoma, or ILC, being detected rather than other histologic types.

The pattern changed sharply among women aged 75 and older. DBT remained associated with lower-grade tumors, with an adjusted odds ratio of 1.21 for grade I disease, and with node-negative disease, with an adjusted odds ratio of 1.18. However, the technique was not significantly associated with smaller tumors: the adjusted odds ratio was 0.99, with a 95 percent confidence interval from 0.90 to 1.10. Nor was DBT significantly associated with invasive lobular histology in this age group, where the adjusted odds ratio was 1.13 and the confidence interval, 0.98 to 1.32, included the possibility of no difference. In practical terms, the study indicates that tomosynthesis may still identify cancers with less aggressive pathological features in older women, but it may not consistently expose those cancers at an earlier, smaller stage than standard mammography.

Tumor grade and lymph-node status provide different kinds of biological information. Grade describes how abnormal cancer cells look under a microscope and how actively they appear to be dividing; grade I tumors generally resemble normal tissue more closely and tend to grow more slowly than higher-grade tumors. Node-negative disease means that cancer was not found in the sampled regional lymph nodes, a finding often associated with a lower risk of regional or distant spread. Tumor size is a direct measure of how much a cancer has grown before detection. These variables are clinically related but not interchangeable, so the study’s results do not mean that DBT failed to detect early cancers in women over 75. Rather, its association with favorable grade and lymph-node status persisted even when its association with smaller size did not.

The result involving invasive lobular carcinoma is especially notable because ILC can be difficult to see on standard breast imaging. Unlike invasive ductal carcinoma, which often forms a more compact mass, lobular cancer cells typically lose adhesion to one another and infiltrate breast tissue in a dispersed, single-file pattern. This can produce subtle architectural distortion rather than a sharply defined lump. DBT’s reconstructed slices might, in principle, make such distortions easier to recognize by reducing tissue overlap. The association observed in women aged 67 to 74 is consistent with that possibility. Yet the absence of a statistically significant association in women over 75 suggests that age-related tissue composition, tumor biology, screening patterns, or other clinical factors may influence how much additional information DBT contributes.

The researchers caution that their findings should not be interpreted as proof that tomosynthesis itself caused the more favorable tumor characteristics. This was a retrospective observational study based on administrative and registry data, not a randomized trial in which women were assigned to one imaging method or the other. Women receiving DBT may differ from those receiving digital mammography in ways that are difficult to measure, including access to advanced imaging centers, healthcare engagement, geographic location, socioeconomic conditions, overall health, and the frequency or continuity of prior screening. The analysis focused only on screen-detected estrogen-receptor-positive, HER2-negative cancers, so the results may not apply to triple-negative tumors, HER2-positive cancers, symptomatic disease, or cancers diagnosed outside screening.

Age also complicates the balance between screening benefits and harms. A screening program can find cancers earlier, but it can also detect tumors that would never have caused symptoms during a person’s lifetime. This phenomenon, known as overdiagnosis, becomes increasingly important when competing health conditions and life expectancy vary widely among older adults. Finding a small tumor does not automatically mean that screening has improved survival if the tumor is biologically indolent or if treatment would never have become necessary. Conversely, a lack of an observed size advantage with DBT does not establish that the technology is useless after age 75, particularly because the study found associations with lower grade and node-negative disease. Decisions about continuing screening should therefore consider individual health, functional status, personal preferences, prior screening history, and the likely benefits and burdens of follow-up and treatment rather than age alone.

The study’s central message is that the apparent advantage of 3D mammography may be age-dependent. For women in their late 60s and early 70s, DBT was linked to a broader set of favorable findings, including smaller tumors and detection of invasive lobular cancers. For women aged 75 and older, its associations narrowed to tumor grade and lymph-node status, making DBT and digital mammography appear more comparable for some outcomes. The findings do not dictate which test any individual should receive, nor do they resolve when screening should stop. Instead, they point to a more precise future for screening research—one that evaluates not only how many cancers an imaging technology detects, but also which cancers it finds, how dangerous those cancers are, and whether detection changes outcomes that matter to older women.

Subject of Research: Tumor characteristics associated with digital breast tomosynthesis versus digital mammography in older women with screen-detected breast cancer

Article Title: Tumor characteristics associated with tomosynthesis versus digital mammography in older women with screen-detected breast cancer

Article References: Huang S, Westvold SJ, Soulos PR, et al. “Tumor characteristics associated with tomosynthesis versus digital mammography in older women with screen-detected breast cancer.” Breast Cancer Research and Treatment 218, article 4 (2026). Original research article

Image Credits: AI Generated

DOI: 10.1007/s10549-026-08013-4

Keywords: breast cancer, digital breast tomosynthesis, screening mammography, older women, tumor grade, lymph-node status, invasive lobular carcinoma, tumor size, overdiagnosis

The study was conducted by researchers from the University of Cambridge’s El-Erian Institute of Behavioural Economics and Policy and the Cambridge Political Psychology Lab. They surveyed 100 sitting Labour, Conservative and Liberal Democrat MPs during December 2024 and January 2025, asking them to estimate how the British public and other parliamentarians viewed specific carbon-reduction policies. Those estimates were then compared with nationally representative polling of 4,201 UK adults conducted by Ipsos UK between 18 and 24 April 2024. Because the public survey asked about the same policy proposals, rather than broad questions about whether people “support climate action,” the comparison allowed researchers to measure perception gaps with unusual precision.

One of the policies involved making grants or loans available to every household with an energy-efficiency rating of C or below, enabling residents to improve insulation. MPs estimated that approximately 18 per cent of the public opposed the measure. In reality, opposition stood at only 6 per cent—meaning politicians overestimated resistance by three times. The gap was also substantial for a proposed environmental product tax, under which the tax applied to goods would vary according to their environmental damage. MPs believed that around 38 per cent of the public opposed this approach, while the Ipsos polling found opposition at approximately 20 per cent. The figures indicate that parliamentarians were not simply mistaking widespread enthusiasm for mild ambivalence; they were systematically imagining a much larger hostile constituency than the data revealed.

The researchers also found that MPs underestimated support, not merely overestimated opposition. On average, they underestimated public backing for the environmental product tax by 14.9 percentage points and support for the insulation policy by 7.1 points. Across both proposals, MPs’ estimates of public support were about 11 percentage points lower than the actual polling results. This distinction matters politically. A politician who believes that voters are undecided may still see an opportunity to persuade them, whereas a politician who believes voters are actively opposed may expect a direct electoral penalty. “Overestimating opposition is likely to generate greater political risk aversion than assuming the public is merely ambivalent,” said lead author Lisa-Maria Tanase, who carried out the research during her PhD at Cambridge.

The perception gap was particularly pronounced when MPs assessed differences between political groups. Polling showed that Labour and Conservative voters differed by 12 percentage points in their support for the climate policies, yet MPs estimated the divide at roughly 25 points. The gap between Liberal Democrat and Conservative voters was judged by MPs to be about 30 percentage points, despite polling indicating a difference of only 14 points. Even the two-point distinction between Labour and Liberal Democrat voters was estimated by MPs at nearly five points. The most dramatic distortion concerned Conservative voters. Parliamentarians believed Conservative supporters were, on average, 12.6 percentage points less supportive of the policies than the public overall, while the polling showed a difference of just 2.5 points—an exaggeration of roughly fivefold.

This phenomenon is known as “false polarisation,” a cognitive and social bias in which people assume opposing groups are more divided than they actually are. In political systems dominated by highly visible conflict, individuals may infer that partisan identities determine opinions more strongly than they do in everyday life. Media coverage can intensify the effect by giving disproportionate attention to confrontational politicians, campaign groups and highly active online communities. The study’s authors argue that MPs may be exposed to an information environment that acts like a “funhouse mirror,” magnifying the loudest opposition while obscuring the quieter majority. Environmentally supportive Conservative voters, for example, may feel misrepresented if politicians repeatedly portray them as fundamentally hostile to climate policy.

The researchers identified evidence that these beliefs influence how MPs say they would behave. For the environmental product tax, MPs who thought public support was lower were less willing to advocate for the measure in public, even after accounting for their own personal views. The same pattern appeared when MPs estimated how many colleagues across Parliament would support the tax. Those who believed the policy had little backing among fellow parliamentarians were also less willing to champion it in Westminster, regardless of whether they personally supported it. This is the mechanism behind the proposed spiral of silence: people who believe their position is unpopular become less likely to express it, which can make the position appear even less popular to everyone else.

The silencing effect was not found for the insulation policy. The authors suggest that subsidies may be viewed as less controversial and more broadly acceptable than taxes, particularly when they promise to reduce household energy costs. The difference illustrates that political perception is not necessarily uniform across all climate measures. Public support can depend on how a policy distributes costs and benefits, whether it is framed as financial assistance or increased taxation, and how easily its consequences can be understood. Technical policy design therefore matters as much as the general label “climate action.” A measure intended to reduce emissions may be widely supported in principle but become politically vulnerable if MPs believe its financial or social costs will trigger organised resistance.

To test whether better information could correct the distorted perceptions, the researchers randomly provided half of the MPs with the relevant public polling results before asking them to estimate support for another set of climate policies. The intervention produced little change in the accuracy of their subsequent estimates. This finding suggests that perception gaps may not be caused simply by a lack of information. Established beliefs, partisan expectations, repeated exposure to polarised debate and assumptions about what is politically safe may be more resistant to correction than a single piece of polling data. Tanase said the results could not be explained by politicians merely projecting their own opinions onto the public: MPs who personally supported a policy also tended to overestimate public opposition to it.

The authors describe the findings as the first data-led evidence of a possible spiral of silence within the British Parliament concerning climate policy, while emphasising that the study identifies associations rather than proving a complete causal chain. The sample included 80 Labour MPs, 16 Conservatives and four Liberal Democrats, broadly reflecting the composition of the Commons at the time but overrepresenting Labour and underrepresenting the Liberal Democrats. Even with those limitations, the research points to a potentially important barrier to faster emissions reduction. If politicians systematically misread public opinion, they may reject policies that voters would accept, avoid cross-party cooperation and communicate excessive pessimism about democratic support for climate action. “Our study found a systematic pessimism about the public appetite for climate action among the UK’s most influential decision-makers,” Tanase said. “This may be contributing to a silencing effect in Parliament around one of the defining policy challenges of the 21st century.”

Subject of Research: UK MPs’ perceptions of public and parliamentary support for climate policies

Article Title: Perception gaps in the British Parliament reveal a possible pathway to stronger climate policy action

News Publication Date: 19 August 2026

Web References: https://www.nature.com/articles/s44458-026-00097-9

References: Tanase, L.-M., Reisch, L. A., Dewies, M., & De-Wit, L. “Perception gaps in the British Parliament reveal a possible pathway to stronger climate policy action.” Communications Sustainability. DOI: 10.1038/s44458-026-00097-9

Keywords: climate change, climate policy, UK Parliament, MPs, public opinion, false polarisation, spiral of silence, carbon reduction, environmental taxation, home insulation, political psychology, behavioural economics

The study, published in Communications Earth & Environment (published 20-Jun-2026), shows that Black Sea freshwater strengthened surface-water stratification in the Aegean. When the upper ocean became more layered, the formation of deep waters was suppressed—an oceanographic shift that strongly affects how nutrients and organic matter are transported and preserved.

A key outcome of this altered circulation was the development of Sapropel 1, a widespread organic-rich sediment layer deposited across the Eastern Mediterranean during the Early Holocene. The researchers argue that the Black Sea outflow provided a critical mechanism, helping create conditions favorable for organic material to accumulate on the seafloor.

For decades, explanations for Sapropel 1 emphasized increased freshwater delivery from North African rivers and enhanced precipitation over the northern Mediterranean region. The new results challenge that view by demonstrating that the Black Sea drainage basin itself acted as a powerful freshwater source, capable of reorganizing water masses through the Dardanelles Strait.

The researchers connect intensified meltwater input and wetter conditions across the Black Sea basin to stronger export of low-salinity water. This reorganization occurred in the northern and central Aegean Sea, changing the balance between stratification and deep-water convection during a warm climatic interval.

To reconstruct these processes, the team analyzed a marine sediment core from the central Aegean Sea near important deep-water formation areas in the north. The archive spans more than 42,000 years, enabling comparisons of long-term variability with the specific environmental transition linked to the Early Holocene.

They combined multiple advanced techniques—grain-size analysis, X-ray fluorescence scanning, radiogenic isotopes, and stable isotope geochemistry—to distinguish the fingerprint of Black Sea outflow from other climatic and hydrological signals.

Beyond reconstructing the past, the findings provide a “stress test” for future climate scenarios. If large freshwater inputs can disrupt deep-water formation and reorganize circulation in warm periods, similar mechanisms could influence marine ecosystems and carbon burial under ongoing climate change.

Subject of Research: Experimental study
Article Title: Early Holocene vigorous Black Sea outflow and the onset of sluggish Aegean deep-water convection
News Publication Date: 20-Jun-2026
Web References: https://www.nature.com/articles/s43247-026-03730-6 ; http://dx.doi.org/10.1038/s43247-026-03730-6
References: 10.1038/s43247-026-03730-6
Image Credits: Communications Earth & Environment

Keywords: Earth sciences; Black Sea; Aegean Sea; Early Holocene; freshwater outflow; ocean stratification; deep-water convection; Sapropel 1; paleoceanography