Macrophages are immune cells that can adopt different functional states within the tumor microenvironment. The review describes a balance between pro-inflammatory M1 macrophages and pro-tumorigenic M2 macrophages. M2 polarization can favor processes associated with tumor progression, whereas M1 polarization is linked in the reviewed evidence to inhibition of tumor growth.

Several non-coding RNAs are linked with M2 polarization in the review. miR-934, lncRNA RPPH1 and circPLCE1 are associated with M2 polarization and metastasis through signaling involving PI3K/AKT, NF-κB and STAT3. Their effects are presented as part of the molecular communication networks that connect colorectal cancer cells with tumor-associated macrophages. The review places these molecules within the broader biological context of tumor progression and metastatic behavior.

Other non-coding RNAs are associated with the M1 state. miR-195-5p and lncRNA GAS5 are described in the reviewed literature as favoring M1 polarization and suppressing tumor growth. The contrast between these molecules illustrates that non-coding RNA activity can be associated with different macrophage states and opposing effects on tumor-related processes. The mechanisms summarized in the review include exosomal transfer, competing endogenous RNA interactions and transcriptional regulation.

Transcriptional regulation provides another level at which these signals can affect cellular behavior. Together, these mechanisms form intricate communication networks between colorectal cancer cells and immune components, including tumor-associated macrophages. The review also discusses the possible translational applications of this biology.

Circulating exosomal non-coding RNAs are presented as candidate biomarkers that could improve diagnostic precision, and ncRNA-regulated macrophage polarization is identified as a possible target for immunomodulatory and precision-treatment strategies. These are research opportunities rather than established clinical benefits. Colorectal cancer remains a major global health burden, with incidence and mortality rates continuing to rise worldwide, according to the review.

The article cites a projection of 3.2 million colorectal cancer cases by 2040 and attributes this expected burden to complex interactions among genetic, environmental and lifestyle factors. The review positions ncRNA signaling within this wider disease context because these molecules may influence tumor-cell behavior, immune evasion, therapeutic resistance and the states of macrophages in the tumor microenvironment. Its central conclusion is that targeting ncRNA-regulated macrophage polarization holds promise for developing next-generation precision therapies and advancing immunomodulatory strategies in colorectal cancer.

That conclusion is a direction for research, not evidence of clinical efficacy. The review’s contribution is to assemble current knowledge about how microRNAs, long non-coding RNAs and circular RNAs relate to macrophage polarization and cancer progression, providing a framework for further investigation of these molecular connections.

Subject of Research: Non-coding RNA regulation of tumor-associated macrophage polarization in colorectal cancer

Article Title: Macrophage polarization and non-coding RNAs in colorectal cancer progression and metastasis

Article References: Nami, M. T., Fattahiyan, I., Eini, P., Eramian, M., & Vanan, A. G. (2026). Macrophage polarization and non-coding RNAs in colorectal cancer progression and metastasis. Medical Oncology, 43(11), Article 350. https://doi.org/10.1007/s12032-026-03482-5

Image Credits: AI Generated

DOI: 10.1007/s12032-026-03482-5

Keywords: colorectal cancer, non-coding RNAs, tumor-associated macrophages, macrophage polarization, microRNAs, long non-coding RNAs, circular RNAs, cancer metastasis, tumor microenvironment, exosomal biomarkers, Macrophage, polarization

The article, published on 19 October 2026 by Mesut Yavuz, Alexandra Roth and Nicolai Savaskan, is explicitly conceptual rather than a report of new causal findings. The authors combined elements of a scoping review, citation mapping and thematic analysis of scientific and grey literature. Their preliminary scoping review began with World Health Organization strategic and policy documents, and the inclusion criteria covered public health services, governmental and policy papers, and published interviews with senior figures in German public administration. The article does not present a systematic estimate of polarization’s effect on any specified health outcome.

Germany’s PHS is structurally different from the country’s predominantly self-governing outpatient and inpatient healthcare sectors. Public health authorities are embedded in governmental administration at federal, state and municipal levels, with local authorities responsible for tasks including enforcement of federal and state rules, health protection and prevention. The authors describe this arrangement as both a basis for democratic accountability and a source of institutional dependency, particularly during crises when scientific assessments must be translated into action under intense political scrutiny.

The perspective identifies three principal mechanisms through which polarization can amplify existing vulnerabilities. First, distrust of institutions and expertise can weaken the perceived authority of public health guidance. Second, acting under uncertainty can carry greater political costs because decision-makers may need to anticipate partisan reactions, with consequences for the clarity of scientific advice. Third, compliance may decline when recommendations are understood as politically influenced. Evidence cited from the pandemic period includes a 2021 German survey that associated vaccination willingness with the views of a person’s social network and found lower trust in the Robert Koch Institute among vaccine sceptics; the article notes that nationwide German spatial vaccination data were unavailable because the country had no vaccination registry.

The COVID-19 pandemic exposed pre-existing constraints in the PHS, according to the article. These included workforce shortages, a comparatively low share of medically trained personnel, fragmented digital infrastructure and limited integration with academic research institutions. The authors also refer to observations that, in certain documented cases during the pandemic, scientific assessments were shaped, delayed or filtered by administrative and political hierarchies. They frame such episodes as consequences of institutional arrangements, but do not provide a new causal analysis of their frequency or population-level health effects.

Historical experience adds weight to the governance argument. The authors note that medical and public health institutions were instrumentalized under the National Socialist regime for racial and political classification, forced sterilization and genocidal violence. They argue that Germany’s postwar healthcare system subsequently developed stronger self-governance arrangements in inpatient and outpatient care, while public health authorities did not receive equivalent structural protection. Within the PHS, practitioners must balance professional and scientific obligations against formal accountability to government hierarchies; during crises, career vulnerability, reputational risk and organizational pressure may narrow independent judgment, according to the perspective.

The article also identifies workforce and knowledge-exchange weaknesses that could not be resolved by emergency recruitment alone. Public health remains less attractive than other health careers because of limited career pathways, lower physician remuneration and a perception that the work is mainly administrative. Weak links between public health practice and universities can impede the application of current research and the translation of operational problems into research questions. These conditions limit the service’s capacity to innovate and maintain analytical rigor as threats and evidence change rapidly.

Rather than treating political polarization solely as a communication problem, the authors recommend examining it as part of public health governance. They propose several possible reforms: statutory and professional safeguards for independence, closer medical and academic integration of public health authorities, clearly defined leadership and qualification profiles, agency-based arrangements, and, over the longer term, self-governing public corporations. Such models would not eliminate democratic oversight, but could rebalance it with professional self-regulation and protect scientific integrity through institutional design. The authors acknowledge trade-offs involving legal oversight, financing and federal coordination.

The perspective’s main limitation is its explicitly non-causal, conceptually oriented approach. It synthesizes existing literature and institutional experience but does not estimate how much political polarization changes trust, compliance, public health outcomes or resilience in Germany or elsewhere. The proposed reforms are therefore presented as pathways for further consideration, not reforms whose effects have been demonstrated. The central conclusion is that preparedness, infrastructure and funding are necessary components of public health resilience, while the governance conditions surrounding evidence-based decision-making also warrant attention.

Subject of Research: Political polarization and governance of Germany’s public health service

Article Title: Political polarization and public health in Germany

Article References: Yavuz, M., Roth, A., & Savaskan, N. (2026). Political polarization and public health in Germany. Frontiers in Public Health, 14, Article 1925598. https://doi.org/10.3389/fpubh.2026.1925598

Image Credits: AI Generated

DOI: 10.3389/fpubh.2026.1925598

Keywords: political polarization, public health, public health governance, Germany, Öffentlicher Gesundheitsdienst, health system resilience, institutional trust, scientific evidence, COVID-19, health policy reform, Political, polarization

This materials study combined atomic-resolution microscopy, non-linear optical characterization and first-principles calculations to connect atomic arrangement with polarization. The microscopy and optical measurements were used alongside calculations rather than relying on a single type of observation, allowing the investigators to examine how the 2H and 3R configurations differ in their structural and ferroelectric properties. The reported transitions also show that the effect is polymorph-dependent. For β′-In2Se3, the stacking change altered the material from antiferroelectric to paraelectric; for α-In2Se3, the relevant structural change removed in-plane ferroelectric polarization. The work therefore addresses the largely unexplored role of stacking order in intrinsic two-dimensional ferroelectric systems.

The team subsequently combined the stacking configurations to create controlled 2H/3R ferroelectric homojunctions made from In2Se3. Differential phase-contrast scanning transmission electron microscopy directly visualized polarization-dependent potential barriers at the interfaces. These junctions also exhibited switchable band alignment and tunable carrier transport, linking the local polarization arrangement to the behavior of charge carriers across the engineered boundary. The results do not establish that such interfacial properties are inherently difficult to control in single-stacking material; rather, they show that the homojunctions possess switchable band alignment and tunable transport as directly observed and measured in the study.

Stacking-engineered homojunctions translated those structural effects into improved laboratory memristor behavior. Devices incorporating the junctions had significantly reduced switching voltages compared with devices based on single-stacking α-In2Se3. Their on/off ratio reached approximately 2.6 × 10^4, about one order of magnitude higher than that of the single-stacking α-In2Se3 devices used for comparison. These are measured device results rather than predictions: the report identifies lower switching voltage and a larger separation between resistance states in the homojunction devices. It does not establish performance beyond the tested laboratory configurations or demonstrate a commercial memory application.

Taken together, the experiments identify stacking order as a way to alter ferroelectricity without changing the chemical identity of the material and as a basis for constructing polymorphic homojunctions. The synthesis strategy provided large-area β′- and α-In2Se3 films with selectable 2H or 3R structures, while microscopy, optical measurements and calculations established how those structures govern polarization. The junctions then provided a route to switchable band alignment, tunable carrier transport and memristors with reduced switching voltages and an on/off ratio of approximately 2.6 × 10^4. The authors describe the resulting stacking-engineered polymorphic heterogeneity as a platform for two-dimensional ferroelectronics and memory technologies, although the reported evidence remains at the material-and-device research stage.

Subject of Research: Stacking-controlled ferroelectricity and memristor behavior in two-dimensional In2Se3

Article Title: Stacking-specific two-dimensional In2Se3 for ferroelectric homojunctions

Article References: Zheng, X., Yang, T., He, X., Zhang, W., Tsang, C. S., Li, Y., Wong, L. W., Yan, Z., Zhang, J., Chen, T., Chen, H., Jia, R., Lee, C.-S., Lau, S. P., Zheng, S., Zhao, J., Yang, M., & Ly, T. H. (2026). Stacking-specific two-dimensional In2Se3 for ferroelectric homojunctions. Nature Nanotechnology. https://doi.org/10.1038/s41565-026-02309-8

Image Credits: AI Generated

DOI: 10.1038/s41565-026-02309-8

Keywords: two-dimensional materials, indium selenide, ferroelectricity, stacking order, homojunctions, memristors, chemical vapour deposition, band alignment, polarization, atomic-resolution microscopy, Stacking-specific, two-dimensional

The investigation began with a systematic characterization of the fecal microbiome in mice with surgically induced endometriosis. Using 16S rDNA sequencing of the V3–V4 hypervariable region on an Illumina NovaSeq 6000 platform, the researchers profiled the gut microbiota of endometriosis and control mice during diestrus at day 42 post-model establishment. After quality filtering, 700 amplicon sequence variants were shared between groups, with 583 unique to controls and 536 unique to endometriosis mice. Alpha-diversity indices, including Chao1, Shannon, Pielou’s evenness, and Good’s coverage, did not differ significantly between groups, suggesting that overall species richness and evenness remained intact. However, beta-diversity analysis revealed clear structural separation between groups, confirmed by unweighted UniFrac-based principal coordinates analysis, hierarchical clustering, and analysis of similarities. At the phylum level, endometriosis mice showed reduced Firmicutes abundance and increased Bacteroidota, with a significantly altered Firmicutes-to-Bacteroidota ratio compared to controls. Linear discriminant analysis effect size analysis further delineated taxon-level compositional differences, and indicator species analysis nominated g_Ruminococcus, g_Coprococcus, g_Muribaculum, and g_Duncaniella as candidate endometriosis-associated biomarkers. Functional prediction using PICRUSt2 against the KEGG database identified enrichment of sphingolipid biosynthesis and metabolism pathways in endometriosis mice, hinting that lipid metabolism might be a key functional consequence of the dysbiosis.

To translate these compositional shifts into metabolic consequences, the team performed non-targeted liquid chromatography-mass spectrometry metabolomics on peritoneal lavage fluid from endometriosis and control mice. Partial least-squares discriminant analysis revealed clear separation between the metabolic profiles of the two groups, and a 200-permutation test confirmed model robustness without overfitting. Applying thresholds of fold change greater than or equal to 1.2 or less than or equal to 1/1.2, p less than 0.05, and variable importance in projection greater than or equal to 1, the researchers identified 26 upregulated and 2 downregulated metabolites in the endometriosis group. Among these, LysoPC(16:0) exhibited one of the largest fold-changes, highlighted in a heatmap of the top 28 differential metabolites. KEGG pathway enrichment of the full differential metabolite set identified glycerophospholipid metabolism, choline metabolism, linoleic acid metabolism, and unsaturated fatty acid biosynthesis among the top 20 enriched pathways, placing LysoPC(16:0) within a broader lipid metabolic reprogramming of the peritoneal cavity. Spearman’s correlation analysis between significantly altered genera and differential metabolites revealed that multiple genera, including g_Muribaculum, g_Mucispirillum, g_Ruminococcus, and g_Lactiplantibacillus, showed significant positive correlations with peritoneal LysoPC(16:0), suggesting a potential microbiota-metabolite link that demanded causal testing.

The researchers then turned to fecal microbiota transplantation to establish causality. Mice were rendered pseudo-germ-free by a seven-day antibiotic cocktail regimen containing vancomycin, ampicillin, metronidazole, and neomycin sulfate before endometriosis model establishment. Beginning on day 1 after model establishment and repeated every three days, mice were gavaged with sterile phosphate-buffered saline, fecal suspension from control mice, or fecal suspension from endometriosis mice. Peritoneal LysoPC(16:0) was significantly higher in recipients of endometriosis-donor feces than in either control group. These mice also developed heavier lesions and showed a greater proportion of CD206-positive macrophages, a canonical M2 marker, in peritoneal lavage fluid compared with control recipients. These results demonstrated that endometriosis-associated gut microbiota is sufficient to elevate peritoneal LysoPC(16:0) and promote peritoneal M2 macrophage accumulation, thereby facilitating lesion growth. The finding represents a critical advance because it moves beyond correlation to demonstrate that the altered microbiota itself carries the pro-endometriotic signal, with the lipid metabolite serving as the functional mediator between gut dysbiosis and pelvic immune remodeling.

To dissect the cellular mechanism, the team isolated bone marrow-derived macrophages from the femurs and tibias of eight-week-old C57BL/6N mice, cultured them with macrophage colony-stimulating factor for seven days, and stimulated them under multiple conditions. Flow cytometry showed that 50 micromolar LysoPC(16:0) significantly augmented IL-4-induced CD206 expression, confirming that the metabolite promotes M2 polarization in vitro. In a Transwell co-culture assay, mouse endometrial stromal cells placed in the upper chamber migrated significantly more when co-cultured with IL-4 plus LysoPC(16:0)-stimulated macrophages in the lower chamber than with either negative control or IL-4-alone conditions. Additionally, a phagocytosis assay using phycoerythrin-conjugated microspheres demonstrated that LysoPC(16:0)-treated macrophages exhibited enhanced particle uptake over two hours, consistent with prior reports that lysophosphatidylcholine promotes macrophage phagocytic activity. These in vitro findings established that LysoPC(16:0) directly reshapes macrophage phenotype and function, with downstream consequences for endometrial stromal cell migration, a pivotal step in ectopic lesion formation.

In vivo, the researchers administered daily intraperitoneal injections of LysoPC(16:0) to endometriosis mice for two weeks. Mice treated with the metabolite developed larger lesions than vehicle controls, whereas mice treated with AACOCF3, a phospholipase A2 inhibitor that suppresses endogenous LysoPC(16:0) production, showed smaller lesions and a lower proportion of peritoneal CD206-positive macrophages relative to endometriosis controls. To determine whether PPARγ signaling underlies the M2-polarizing activity of LysoPC(16:0), the team used GW9662, a selective PPARγ antagonist. In bone marrow-derived macrophages, LysoPC(16:0) significantly augmented IL-4-induced CD206-positive polarization, and this was substantially reduced by GW9662 pretreatment. In vivo, LysoPC(16:0)-t mice developed heavier lesions and showed a higher proportion of peritoneal CD206-positive macrophages than vehicle controls, and GW9662 co-administration significantly reduced both parameters. To assess whether these findings extend beyond a single genetic background, the researchers repeated the experiment in BALB/c mice using a four-group design, and the directional results were consistent with those in C57BL/6N mice across all outcome measures, confirming that the LysoPC(16:0)–PPARγ–M2 axis is not strain-specific but operates across genetically distinct backgrounds.

A key mechanistic advance of the study is the identification of IL-10 as the downstream effector through which LysoPC(16:0)-polarized M2 macrophages promote lesion progression. Reverse transcription quantitative polymerase chain reaction demonstrated that LysoPC(16:0) significantly upregulated Il10 messenger RNA in IL-4-primed macrophages in a PPARγ-dependent manner, placing IL-10 transcription within the LysoPC(16:0)–PPARγ cascade. The functional importance of IL-10 was confirmed in vivo: neutralizing IL-10 in LysoPC(16:0)-supplemented endometriosis mice with an anti-mouse IL-10 neutralizing antibody significantly reduced lesion weight compared with isotype controls. To formally establish that peritoneal macrophages are causally required rather than incidental bystanders, the researchers co-administered clodronate liposomes to deplete macrophages in LysoPC(16:0)-treated endometriosis mice. At day 14, clodronate-treated mice showed markedly fewer F4/80-positive cells in peritoneal lavage fluid and significantly lower lesion weights than empty liposome controls, despite equivalent LysoPC(16:0) exposure. Macrophage depletion therefore abolished the pro-endometriotic effect of LysoPC(16:0), demonstrating that peritoneal macrophages are required mediators of the metabolite-driven lesion growth.

To provide preliminary cell-based evidence relevant to human endometriosis, the researchers employed two complementary human models. THP-1 monocytes were differentiated into macrophages by phorbol 12-myristate 13-acetate treatment, rested for 24 hours, and stimulated under four conditions: negative control, IL-4/IL-13, IL-4/IL-13 plus LysoPC(16:0), and IL-4/IL-13 plus LysoPC(16:0) plus GW9662. LysoPC(16:0) significantly increased the proportion of CD206-positive cells compared with IL-4/IL-13 alone, and GW9662 reversed this effect, recapitulating the PPARγ-dependent polarization observed in murine macrophages. Conditioned medium was then collected from THP-1 macrophages stimulated under six conditions, including IL-10 neutralization with an anti-human IL-10 antibody or a human IgG1 isotype control. Primary endometrial stromal cells were isolated from ectopic lesions of five patients with surgically and histologically confirmed endometriosis, aged 26 to 37 years with a median age of 33, all with rAFS stage III–IV disease. Conditioned medium from LysoPC(16:0)-stimulated macrophages promoted significantly greater stromal cell migration than conditioned medium from IL-4/IL-13-alone conditions across all five patient samples, and this enhancement was substantially reduced by GW9662 or IL-10 neutralization but not by the isotype control. The consistency of the conditioned medium effect across five independent patient specimens, each tested under all six conditions in parallel, provides preliminary evidence that the axis identified in murine models is also operative in human cells.

The researchers acknowledge several limitations that place practical bounds on these conclusions. The bacterial taxa ultimately responsible for LysoPC(16:0) production were not isolated at the species level, as several candidate genera are obligate anaerobes whose cultivation requires dedicated infrastructure. Confirming a direct strain-metabolite relationship will require single-strain gnotobiotic colonization. The link between LysoPC(16:0) and PPARγ was established pharmacologically with GW9662, consistent with earlier reports that structurally related lysophospholipids can act as PPARγ ligands, but direct biophysical evidence of binding, such as co-crystallography or surface plasmon resonance, was not obtained. Likewise, IL-10 was identified as the principal downstream effector, but transforming growth factor beta and other M2-associated cytokines were not systematically profiled, and how IL-10 signaling drives endometrial stromal cell migration, whether through JAK-STAT3, PI3K-AKT, or another route, remains to be worked out. The translational component relied on a monocyte-derived cell line and primary stromal cells from five patients, a cohort that cannot capture the clinical heterogeneity of endometriosis across disease stage, lesion subtype, or symptom severity. Despite these limitations, the findings carry potential clinical relevance that warrants further exploration. Elevated peritoneal LysoPC(16:0) and altered microbiota composition could be evaluated as candidate biomarkers for endometriosis in future clinical studies, and the phospholipase A2–LysoPC(16:0)–PPARγ–IL-10 cascade offers multiple candidate intervention points for preclinical exploration. As the work is primarily based on murine models and cell-based human systems, its findings should be interpreted as preclinical mechanistic evidence, with clinical applicability to be established in future patient studies.

Subject of Research: Intestinal microbiota-associated LysoPC(16:0) promotes endometriosis via PPARγ-mediated M2 macrophage polarization and IL-10 secretion

Article Title: Intestinal microbiota-associated LysoPC(16:0) promotes endometriosis via PPARγ-mediated M2 macrophage polarization and IL-10 secretion

Article References: Li, N., Yuan, M., Jin, X., Jiao, X., Wang, S., Zhong, Z., Guan, H., Le, X., Ren, Q., Liu, Y., Dong, X., Li, Q., Wang, M., & Wang, G. (2026). Intestinal microbiota-associated LysoPC(16:0) promotes endometriosis via PPARγ-mediated M2 macrophage polarization and IL-10 secretion. iScience, 29(11), Article 117917. https://doi.org/10.1016/j.isci.2026.117917

Image Credits: AI Generated

DOI: 10.1016/j.isci.2026.117917

Keywords: Intestinal, microbiota-associated, LysoPC, promotes, endometriosis, PPAR, mediated, macrophage, polarization, IL-10, secretion, scientific research

The difficulty lies in two competing traditions. Classical opinion dynamics models, such as the DeGroot model of 1974, the Friedkin-Johnsen model, and the Hegselmann-Krause bounded-confidence framework, describe how individuals update their views through explicit interaction rules. These models elegantly explain group-level phenomena like consensus formation and polarization, but they rest on simplifying assumptions: global interactions, homogeneous influence weights, or fixed neighborhoods. Real social networks, by contrast, are sparse and locally connected, and different neighbors exert very different degrees of influence on any given user. When the goal shifts from describing aggregate trends to predicting what a specific individual will believe next month, those idealized assumptions begin to crack.

Purely data-driven methods have the opposite problem. Continuous-time stochastic models such as SLANT and SLANT+ can process irregular event streams, while deep sequence models like LSTM and Transformers capture nonlinear patterns in individual histories, and graph neural networks incorporate network topology through neighborhood aggregation. Yet these approaches learn statistical correlations without any explicit formulation of social influence mechanisms. The authors point out that under observational noise, this lack of structural grounding causes substantial error accumulation over long prediction horizons, causing predicted trajectories to drift away from the actual dynamics of opinion change.

GA-ODE, short for graph attention with ordinary differential equations, belongs to an emerging middle ground sometimes called socially informed neural networks, which borrows ideas from physics-informed neural networks and Neural ODEs. The architecture has four cooperating components. First, each user receives a learnable embedding vector concatenated with their initially observed opinion, and a multilayer perceptron converts timestamps into continuous-time feature vectors. Second, a graph attention network computes unnormalized attention scores between a target user and each neighbor, normalizes them through a softmax function, and aggregates neighborhood information using a multi-head mechanism. This allows the model to learn differentiated aggregation weights, reflecting the fact that not all neighbors matter equally.

Third, inspired by the gating machinery of LSTM networks, the model employs a gated evolution unit to balance two opposing forces: individual opinion persistence and neighborhood assimilation. A forget gate, computed jointly from the temporal features and the user’s previous hidden state, determines how much of the historical cognitive state to retain. An input gate and a candidate cell state then control how much aggregated neighborhood information flows into the update, while an output gate regulates the contribution of the cell state to the final hidden representation. A self-attention module subsequently fuses the user’s hidden state with the temporal embedding, capturing the dynamic correlation between who a user is and when the prediction is being made.

The fourth and most distinctive component is a structure-aware ODE consistency constraint rooted in the Stochastic Bounded Confidence Model. Instead of a hard confidence threshold that forbids interaction between people holding divergent views, this probabilistic formulation assigns interaction probabilities inversely related to opinion distance, so individuals are more likely to engage like-minded peers but occasionally interact with those who disagree. The authors derive a continuous-time dynamical system from the discrete interaction rule, and because sampling discrete interaction partners is not differentiable, they apply the Gumbel-Softmax reparameterization trick to create a smooth, differentiable relaxation. The training loss then penalizes the squared difference between the time derivative of the predicted opinion trajectory, computed via automatic differentiation at randomly sampled collocation points, and the expected social influence term restricted to each user’s immediate neighborhood by an adjacency matrix mask.

The team evaluated GA-ODE against ten baselines, ranging from the classical Voter and DeGroot models to spatiotemporal graph networks like STGCN and T-GCN and socially informed rivals such as SINN, NPBC, and TT-SBCM. On three synthetic datasets engineered to produce consensus, polarization, and clustering dynamics, GA-ODE achieved accuracies of 0.892, 0.948, and 0.977 respectively. On a real-world dataset of political interactions gathered from the X platform between December 2023 and March 2024, containing roughly 10,883 messages from 526 users across 384 time steps, it reached an accuracy of 0.655. Compared with the strongest baseline, TT-SBCM, the improvements ranged from 1.5 to 3.7 percentage points, and two-tailed Welch’s t-tests across five random seeds confirmed the gains were statistically significant on every dataset.

Ablation experiments revealed why each piece matters. Replacing graph attention with uniform average-pooling aggregation dropped the macro-F1 score on the consensus dataset from 0.806 to 0.608, confirming that differentiated neighbor influence is essential. Removing the gating mechanism caused similar degradation, showing that opinion inertia cannot be captured by simply concatenating features. Perhaps most intriguingly, the topology-aware mask provided only limited benefits on clean graphs, where the graph attention encoder could already extract sufficient neighborhood information, but proved decisive under structural degradation. When 30 percent of edges were corrupted with spurious connections, GA-ODE maintained an accuracy of 0.621 while the mask-free variant fell to 0.551, and similar advantages appeared under missing edges and isolated nodes.

The robustness tests extended beyond network damage to the dynamics themselves. Real opinion change rarely follows smooth assimilation: sharp disagreement can trigger repulsive interactions driven by cognitive dissonance or the backfire effect, and sudden external events can jolt entire populations at once. When the team injected opinion-repulsion effects into the simulation, baseline models lost 4.6 to 7.3 percentage points of accuracy while GA-ODE lost only 2.3 to 2.8. Under external shocks delivered at specific time points, baselines dropped 3.2 to 5.2 points against GA-ODE’s 1.5 to 1.7. A t-SNE visualization further showed that the model’s latent representations form clearer, more discriminative clusters than those of the SINN baseline on the election data.

The authors are candid about the model’s limits. It assumes that social interactions remain static within the observation window, an idealization that real platforms routinely violate, and it is sensitive to sparsely represented opinion classes, which explains the gap between its accuracy and macro-F1 score on the imbalanced election dataset. Real-world validation also rested on a single platform and topic. Future work, they write, will pursue scalable graph learning and efficient ODE solving for large networks, dynamic graph modeling to capture the co-evolution of relationships and opinions, and broader evaluation across platforms and domains. Even so, GA-ODE offers a compelling demonstration that the century-old mathematics of social influence, when welded carefully onto graph attention networks and continuous-time dynamics, can make the messy evolution of human belief measurably more predictable.

Subject of Research: A hybrid machine learning model combining graph attention and neural ordinary differential equations to predict opinion dynamics on social networks

Article Title: An opinion evolution prediction model based on graph attention and ordinary differential equations

Article References: Liu, Q., Duan, L., Jia, M., & Li, Y. (2026). An opinion evolution prediction model based on graph attention and ordinary differential equations. Discover Artificial Intelligence, 6(1), Article 1474. https://doi.org/10.1007/s44163-026-02445-z

Image Credits: AI Generated

DOI: 10.1007/s44163-026-02445-z

Keywords: opinion dynamics, graph attention networks, neural ordinary differential equations, social media, bounded confidence model, prediction, social networks, polarization, machine learning, computational social science, robustness, socially informed neural networks

Optical encryption exploits properties of light waves that electronic systems struggle to replicate, including amplitude, phase, polarization, and orbital angular momentum, along with the inherently parallel, high-speed nature of optical processing. These multidimensional attributes allow engineers to encode information in physical channels that are difficult to intercept, measure, or counterfeit. Yet most existing optical encryption architectures share a common weakness: they are built on a global Fourier transform coupling mechanism. In such systems, the information encoded across the optical field is interdependent, meaning that a perturbation at one point in the field can affect the whole. This global coupling makes traditional schemes vulnerable to iterative retrieval algorithms, a family of cryptanalytic attacks that progressively reconstruct hidden information by exploiting the mathematical structure of the transform. It also constrains the encryption key space, limiting the number of distinct keys an attacker would need to search and thereby capping the achievable security level.

The core problem, as the researchers frame it, is how to break through the physical limitations of global coupling and achieve independent control of multiple degrees of freedom at the microscopic scale. Their answer is the vectorial optical pen, a conceptual and technical tool that allows researchers to write information into an optical field with the precision of fine brushwork rather than broad brushstrokes. Where traditional holographic encryption treats the canvas as a whole, the vectorial optical pen addresses each focal spot individually. Using this approach, the team can independently and precisely control the spatial location, polarization state, and orbital angular momentum of individual focuses on an imaging plane, decoupling the spatial distribution of light from its other physical dimensions.

This decoupling is more than a technical nicety; it establishes the physical foundation for high-capacity encryption. Because each mode in the structured optical field can be controlled without influencing its neighbors, the coherent crosstalk that plagues globally coupled systems is effectively eliminated. Crosstalk between modes is a primary channel through which information leaks in optical encryption, and suppressing it means that each pixel of the encrypted image can carry its own independent layer of security. The result is a system in which the key space grows with the number of independently addressable pixels and degrees of freedom, rather than being constrained by the global architecture of the encoding scheme.

To demonstrate the practical power of the concept, the researchers built and verified a double-lock encryption scheme that operates entirely at the physical level. On the encryption side, the information to be protected, for example the letters S, Z, and U used in the team’s demonstration, is first converted into ASCII codes. The researchers then customize the degrees of freedom of individual optical focuses and encode the digital information into the holographic phase, producing the ciphertext. In effect, this process sets a unique lock for every single pixel of the encrypted image, with the lock parameters drawn from the polarization and orbital angular momentum channels of light.

Decryption requires a key that is itself optical. Only when the incident light simultaneously possesses the correct polarization state and the correct orbital angular momentum parameters can it act as a key to open the pixel-level locks. Under these matching conditions, the optical field interferes correctly and the encrypted information is extracted. If either parameter is wrong, the field suffers severe distortion and the information becomes entirely undecipherable. This behavior is what the researchers mean by guaranteeing reliability at the physical level: security does not depend on computational hardness assumptions that future algorithms might break, but on the wave optics of interference itself. An adversary who lacks the precise polarization and orbital angular momentum key cannot reconstruct the plaintext, no matter how much computing power is applied to the captured ciphertext.

Recognizing that any encryption scheme must withstand quantitative scrutiny, the team subjected their method to a rigorous probability analysis combined with a morphological crossing-feature extraction algorithm. They independently calculated the recognition probability distributions of decrypted results under different orders of incident light, effectively measuring how likely a decoder with partially incorrect keys would be to recover recognizable information. The quantitative data confirmed extremely low crosstalk between encryption channels, meaning that information encoded in one degree of freedom does not bleed into another in ways an attacker could exploit. The ultimate joint decoding probability further validated the robustness of the system, indicating that even the combined requirements of correct polarization and correct orbital angular momentum can be met reliably by an authorized user while remaining vanishingly improbable for an unauthorized one.

The significance of this work lies in how it reframes the security capacity of optical systems. By achieving pixel-resolved, multiple degrees-of-freedom control, the vectorial optical pen transforms each point of an image into an independent cryptographic unit whose state spans several physical dimensions simultaneously. The theoretical key space of such a system scales combinatorially with the number of pixels and the number of distinguishable states per degree of freedom, offering a route to capacities and security levels that globally coupled Fourier architectures cannot reach. At the same time, the physical-layer nature of the double-lock mechanism provides a defense against iterative retrieval attacks that have undermined earlier holographic schemes, since those attacks rely on the very global coupling the new method eliminates.

The research, published as Peng and colleagues’ study of multiple degrees-of-freedom optical encryption via pixel-resolved vectorial holography in Opto-Electronic Technology, was supported by the National Key R&D Program of China, the National Natural Science Foundation of China, the Shenzhen Key Laboratory of Photonics and Biophotonics, the Shenzhen Key Laboratory for Biomedical Optics and Molecular Imaging, and the Shenzhen Science and Technology Program. As digitalization deepens across finance, healthcare, government, and communications, the demand for encryption that is both high-capacity and physically robust continues to grow. The Shenzhen University and BGI Research teams argue that their pixel-resolved approach offers a practical and feasible path toward high-capacity, high-security micro-optical information encryption systems, and their demonstration suggests that the future of secure communication may be written not in bits alone, but in the polarization, phase, and twisted wavefronts of light itself, one pixel at a time.

Subject of Research: Pixel-resolved vectorial holography for multiple degrees-of-freedom optical encryption

Article Title: New optical encryption technique uses light to strengthen information security

Article References: New optical encryption technique uses light to strengthen information security. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: optical encryption, vectorial holography, orbital angular momentum, polarization, information security, photonics, holographic phase encoding, crosstalk suppression, double-lock encryption, light field manipulation, Fourier optics, cryptanalysis resistance

The study focused on the earliest and most volatile days of the invasion. Because the Russian government blocked X just two days after the invasion began, sharply limiting the ability of Russian users to comment publicly, the researchers restricted their X dataset to the first 48 hours, collecting a total of 5,480 tweets tagged with the most active hashtags, #RussiaUkraineConflict and #RussiaUkraineWar. For Wikipedia, they cast a wider temporal net, gathering user interactions from one month before the invasion to one month after it, covering roughly 85 distinct discussion threads on the article’s talk pages. This asymmetry in data collection is itself revealing: it captures the moment when a fast-moving social media firestorm collided with a slower, more deliberate knowledge-building process.

To make sense of the X data, the team turned to natural language processing. They cleaned the corpus with stopword filtering and extracted discussion themes using bigrams, pairs of adjacent words whose co-occurrence frequencies reveal which concepts travel together in the same sentences. The conditional probability of one word following another was computed from the counts of word pairs, allowing the researchers to build networks in which the most frequently used words became nodes connected to their most common companions. To classify each tweet’s stance without importing the researchers’ own political judgments, they used Amazon Mechanical Turk workers, deliberately excluding anyone residing in Russia, Ukraine, or Belarus. Each sentence was evaluated by at least three independent annotators, and a tweet was labeled pro-war or anti-war only if at least two-thirds of its tags agreed. In the end, 78.4 percent of the sample received a reliable stance label, while the ambiguous remainder was excluded.

The results exposed a striking fragmentation. The pro-war community on X organized its discourse around geopolitical and ideological narratives, with NATO’s eastward expansion and the 2014 ‘Revolution of Dignity’ in Ukraine, framed by that community as a coup, serving as central justifying themes. The anti-war community, by contrast, largely ignored the NATO question and instead concentrated on humanitarian arguments: civilian casualties, the suffering of families under bombardment, and the characterization of Vladimir Putin as a war criminal. Crucially, the researchers found almost no thematic overlap between the two camps. The only shared topic, NATO, was itself so deeply polarized that it offered no common ground for dialogue. Without a single shared channel of discussion, the two communities talked past each other, each expressing opinions largely unsupported by sources, which further reduced the possibility of criticism, correction, or any meaningful exchange.

Wikipedia told a fundamentally different story. On the encyclopedia’s talk pages, where editors must arrive at wording that all parties can accept, the researchers found that almost none of the themes dominating X appeared at all. Instead, discussions revolved around editing requests, sourcing requirements, naming conventions, and factual accuracy. Editors debated how to frame events, which actors to identify, and how to maintain contextual precision, rather than whether the war was justified. The platform’s rules requiring verifiable citations and a neutral point of view transformed what had been an explosive ideological clash on X into a technical negotiation over evidence and language. Conflict did not vanish, but it was channeled into procedures designed to resolve it.

One of the study’s most intriguing findings emerged from a heatmap of Wikipedia editing activity. Two accounts, Tobby72 and the IP-based user 8.28.81.21, had been active on the article well before the invasion, even requesting that the page title be changed to ‘Russo-Ukrainian War’ months before Russian forces crossed the border. The authors suggest this early activity could be consistent with preparation for the invasion as part of a propaganda effort, though they present this as an observation rather than a proven conclusion. The heatmap also revealed a division of labor typical of large collaborative projects: a small core of experienced, named editor accounts performed most of the sustained work of reviewing and correcting the page, while many casual or anonymous contributors offered a single suggestion and never returned. Unanswered proposals, the researchers note, were treated as tacitly accepted modifications.

The most technically distinctive contribution of the paper lies in its measurement of linguistic entropy, a quantity borrowed from information theory that captures the unpredictability, and by extension the complexity, of the language used. Applying Shannon entropy alongside BERT-based sentiment and emotion models, the researchers found that sentiment levels were broadly similar across the two platforms, but entropy diverged dramatically. X exhibited significantly lower entropy, reflecting the short, punchy, emotionally direct statements that the platform’s character limit and real-time dynamics reward. Wikipedia showed markedly higher entropy, consistent with the formal, precise, and contextually rich prose that editors must produce to satisfy standards of verifiability and neutrality. In other words, the platforms were not merely hosting different opinions; they were inducing different kinds of language altogether.

The authors frame this difference through the social roles each platform assigns to its users. On X, participants behave as citizens exercising free expression with minimal constraint, an arrangement that favors immediacy and provocation over nuance. On Wikipedia, participants function as volunteers embedded in a structured culture of editorial guidelines, peer review, and dispute resolution mechanisms that mirror organized labor. This culture, the study argues, creates a collaborative environment in which disagreement is processed through rules rather than raw confrontation, allowing contributors who hold opposing views about the war itself to cooperate on the narrower question of how to document it accurately. The requirement to cite sources also opens every claim to criticism, which paradoxically strengthens rather than weakens the possibility of agreement.

The study is candid about its limitations. The absence of Russian voices on X after the government blockade restricts the comparison, a larger dataset might have revealed temporal fluctuations in sentiment and entropy tied to specific events, and the possible presence of bots in the X data cannot be excluded. The researchers also acknowledge that they could not verify whether any X users and Wikipedia editors were the same individuals, since neither platform exposes account-level identifiers that would permit reliable cross-platform matching. Sentiment and emotion detection, applied through validated pretrained models rather than ones retrained on war discourse, may also have missed domain-specific expressions such as sarcasm or euphemism. Yet even with these caveats, the findings carry a clear message for anyone concerned with the health of the digital public sphere. Platform design, community norms, and the presence or absence of shared evidentiary standards can determine whether a polarizing event fractures a community into warring echo chambers or becomes the occasion for structured, evidence-based collaboration. As debates over algorithmic amplification and content moderation intensify, this comparison of X and Wikipedia suggests that the most powerful algorithmic influence on online conflict may not be the recommendation engine at all, but the deeper architecture that decides what kind of conversation a platform makes possible.

Subject of Research: Comparative analysis of conflict and cooperation dynamics on X and Wikipedia during the Russia-Ukraine war

Article Title: Algorithmic influence on conflict and cooperation in digital communities

Article References: Russo, A., & Caliandro, A. (2026). Algorithmic influence on conflict and cooperation in digital communities. PLOS Complex Systems, 3(4), e0000087. https://doi.org/10.1371/journal.pcsy.0000087

Image Credits: AI Generated

DOI: 10.1371/journal.pcsy.0000087

Keywords: algorithmic influence, X platform, Wikipedia, polarization, natural language processing, Shannon entropy, Russia-Ukraine war, online cooperation, echo chambers, sentiment analysis, platform design, digital communities

The award places the University of Arizona at the center of an unusual corner of NASA’s astrophysics portfolio. PUFFINS is the second mission the university has led under the Astrophysics Pioneers program, an initiative launched in 2020 to deliver high-value science on small, cost-capped platforms. The university also leads Aspera, a first-generation Pioneers mission scheduled to launch early next year, and contributed significantly to Pandora, which launched in January of this year. According to university leadership, Arizona has emerged as the only university leading multiple missions in the Pioneers program, while also running mission operations for Pandora. The new mission is a joint effort with the McDonald Observatory at The University of Texas at Austin and an international network of early-career and senior scientists, with corporate partners including Tucson-based Ascending Node Technologies and SFL Missions Inc. of Toronto.

At the heart of the satellite sits a specialized telescope just 10 inches across, roughly the size of a large dinner plate, designed to capture ultraviolet light from distant stars. Despite its modest aperture, the instrument’s value lies not in collecting vast quantities of light but in dissecting it with extraordinary care. PUFFINS will measure the polarization properties of starlight across a range of ultraviolet wavelengths using a technique called spectropolarimetry, an approach that has not been deployed in space in nearly thirty years. Polarization describes the orientation of light waves as they travel, and it carries information that ordinary brightness measurements cannot reveal. When unpolarized starlight passes through a cloud of interstellar dust, the dust imprints a preferred orientation on the light, and the precise way that imprint varies with wavelength encodes the size, composition, and alignment of the grains themselves.

The physics behind the technique is elegant. Interstellar dust grains made of silicates, when spun up by collisions and other processes, tend to align with the galaxy’s magnetic field, much like tiny compass needles. Once aligned, they act collectively as a polarizing filter for starlight passing through them. By measuring that polarization in the ultraviolet, PUFFINS can probe the smallest grain sizes, those smaller than about 50 nanometers, roughly the size of the common cold virus. Such grains are effectively invisible to optical and infrared telescopes, which is precisely why the ultraviolet window matters. The small grains are believed to play an outsized role in the chemistry and energy balance of the interstellar medium, yet their properties remain poorly constrained by existing observations.

Ramya Anche, an assistant research professor at Steward Observatory who serves as the mission’s principal investigator, described the stakes in plain terms. PUFFINS, she said, will change how we understand the dust between stars, and understanding these tiny grains is essential to building a complete picture of how interstellar dust forms, evolves over time, and ends up incorporated into new stars and planets. For Anche, the mission is also a personal milestone. She said PUFFINS represents the culmination of more than a decade of instrument-building work in polarimetry, and that it will be the first instrument she helped design that will actually be built and launched into space. She led the winning proposal to NASA while still a postdoctoral researcher at Steward Observatory, a detail that Steward Observatory director Buell Jannuzi highlighted as evidence of the institution’s unusual willingness to let junior scientists lead major programs.

B-G Andersson, the mission’s science principal investigator and assistant director for research at McDonald Observatory, has spent more than two decades studying how interstellar dust grains align with magnetic fields. He framed the mission’s scientific ambition around one of the oldest puzzles in the field. Interstellar polarization was discovered in 1949, he noted, and astronomers are finally beginning to understand its origin in dust grains. PUFFINS, he said, will work on fully solving what for more than fifty years was the second-longest-standing mystery of interstellar medium physics. The connection between grain alignment and magnetic fields means the mission’s data will also inform studies of the galaxy’s magnetic structure, a topic that touches everything from star formation to the propagation of cosmic rays.

The reach of interstellar dust extends far beyond the specialists who study it directly. Dust makes up only about one percent of the visible mass of the Milky Way, yet its effects ripple through nearly every corner of astrophysics. It dims and reddens the light of distant supernovae, complicating measurements of cosmic expansion. It shields molecules in cold clouds, enabling the chemistry that precedes star birth. It injects heavy elements, forged inside dying stars, back into the galactic ecosystem, where they later condense into the next generation of stars and planets. Because dust properties vary with environment, uncertainties about dust translate directly into uncertainties about nearly every astronomical measurement made from within the Milky Way.

PUFFINS is designed to attack that variability head-on. By observing stars at different distances and in different environments, including nearby stellar nurseries, reflection nebulae where dust scatters starlight back toward Earth, and even the Magellanic Clouds, our closest extra-galactic neighbors, the mission will build a detailed map of how interstellar dust varies across the sky. Comparing polarization signatures across such diverse settings allows scientists to separate the effects of grain composition from those of grain size distribution and magnetic environment. The target list of about 70 stars is chosen so that each sightline probes a distinct combination of dust conditions, turning the spacecraft into a sampling network for the galaxy’s dusty byways.

The mission is currently in its early design phase, with a launch target of 2030. Its planners see it as more than a standalone experiment: PUFFINS is intended to serve as a critical bridge to NASA’s Habitable Worlds Observatory, the agency’s next flagship space telescope currently in development for the 2040s. That flagship may carry an ultraviolet spectropolarimeter in one of its instrument ports, and PUFFINS data can help define what science such an instrument could accomplish. Demonstrating spectropolarimetry in orbit on a small platform, decades after the last such instrument flew, would de-risk the technology and sharpen the scientific case for its inclusion on a far larger observatory.

Behind the hardware, the team has been deliberate about designing PUFFINS as a training ground as much as a science mission. Graduate students and undergraduate researchers are embedded in the instrument development effort from the start, and the University of Arizona roster spans faculty, postdoctoral researchers, and students across Steward Observatory. Kyle Van Gorkom, an early-career faculty member at Steward Observatory who serves as deputy principal investigator and leads the spacecraft interface work, said the team is excited to start from conceptualizing a space telescope and see it through from build to launch to operating in orbit. While the payload is being designed and assembled, the science team will acquire spectropolarimetry data of the mission’s target stars in visible and infrared light using University of Arizona telescopes and other facilities around the world, groundwork that will enhance the ultraviolet data PUFFINS collects and enable a more complete analysis. Erika Hamden, a professor of astrophysics at Steward Observatory who leads the Arizona Space Institute, said the institute was set up to enable exactly these types of missions and that the team has a great science idea. If all goes to plan, by the early 2030s a dinner-plate-sized telescope will be quietly reading the light of distant stars, and with it the story of the dust that fills the space between them.

Subject of Research: Ultraviolet spectropolarimetry of starlight to characterize interstellar dust grains

Article Title: Stories from star dust: U of A-led mission will study light from distant stars

Article References: Stories from star dust: U of A-led mission will study light from distant stars. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: PUFFINS, NASA, interstellar dust, polarization, ultraviolet astronomy, spectropolarimetry, University of Arizona, Steward Observatory, Astrophysics Pioneers, small satellites, magnetic fields, star formation

The study, led by Marian Moser Jones, associate professor of health services management and policy at The Ohio State University College of Public Health, with senior author Amy Fairchild, a professor at the University of Minnesota School of Public Health, interviewed 109 leaders from 18 geographically and politically diverse states. The participants came from suburban and rural communities as well as larger jurisdictions, and included both local and state-level officials. The breadth of the sample matters, because it demonstrates that the hostility was not confined to a handful of high-profile coastal cities or particularly contentious statehouses. It reached into small towns and rural counties, places where public health work had historically been conducted with little public attention and considerable community trust.

The headline finding is stark: 76 percent of the leaders interviewed reported being threatened or harassed. The researchers categorized this level of hostility as extraordinary, distinguishing it clearly from the ordinary friction that accompanies any contested public policy. As Jones explained, the backlash being studied is different from people disagreeing about wearing masks or getting a COVID vaccine. This, she said, is true hostility, threats of violence, and the undermining of officials in ways that damage their ability to do their jobs. In other words, the problem documented here is not the healthy noise of democratic debate but a sustained campaign of intimidation aimed at the individuals charged with safeguarding community health.

The specific experiences described by study participants illustrate how menacing that campaign became. One leader recounted the FBI arrest of a person making ongoing, credible death threats, an arrest that brought home the seriousness of the danger when the official learned that the suspect’s house contained more than 100 guns. Another described a persistent stalker, a man she characterized as scary and obsessed, who sent her a picture of someone strangling a child the same age as her own child. A third described coming home from work to find a note taped to the front door threatening to kill the family dog, accompanied by a photograph of the dog taken in the family’s backyard. These are not anonymous insults on social media; they are intrusions into the private lives and homes of public servants and their families.

Beyond the direct threats, roughly half of the leaders interviewed experienced what the researchers call undermining backlash, a form of hostility that made it difficult or impossible for them to function professionally. This took the form of overwhelming their offices with burdensome data requests, repeatedly demanding revisions to pandemic guidelines, and publicly disparaging their qualifications. Undermining is subtler than a death threat, but its cumulative effect can be just as corrosive. An official who must divert staff time to answering hostile records requests, or who must repeatedly defend basic credentials in public meetings, has less capacity to inspect restaurants, track disease outbreaks, run vaccination clinics or support mothers and infants. The study suggests that this second, quieter form of backlash may be at least as damaging to the profession’s capacity as the overt threats.

The consequences for the public health workforce have been severe. Many of the leaders interviewed have retired early or left the field altogether, according to Jones. She noted that politicians expect a certain degree of hostility when they enter public life, but that before the pandemic most public health officials had never been in the spotlight and had never been targets. The experience has been hard on the profession, she said, and the exodus of experienced leaders carries real costs for communities, because institutional knowledge about outbreak response, environmental health, food safety and maternal health leaves with every early retirement and resignation.

Yet the research is not only a catalogue of damage. One of its most valuable contributions is the identification of strategies that some officials used successfully to reduce the intensity of the backlash, approaches that could inform the response to future fraught moments in public health leadership. Particularly in smaller communities, officials who had deep personal ties to the area often knew the people making threats and creating other challenges. In some cases, they had success bringing upset community members or small business owners to the table for direct conversations, or simply calling opponents and talking the situation through. Jones recounted that officials would sometimes say things like, listen, you’re threatening my kids, and that this kind of direct, personal appeal would sometimes turn the temperature down.

Those personal interventions appear to have had measurable effects. Jones said that, anecdotally, promoting civil discourse seemed to cut down on the backlash. It did not stop the hostility entirely, but it helped prevent officials from being fired or forced out of their positions. Fairchild added that some health officials who weathered the backlash involved local businesses in decision making. These officials understood, she said, that they needed to explain not only the science but also acknowledge the painful tradeoffs at stake and explain the rationales behind difficult decisions. The lesson is a technical one about crisis communication: transparency about uncertainty and tradeoffs, combined with genuine stakeholder engagement, appears to build a buffer of legitimacy that pure top-down mandates do not.

The research team, whose work with public health leaders is ongoing, has also identified potential policy approaches. One is criminalizing doxing, the act of publicly revealing private or personally identifiable information about someone online without their permission. In many of the cases documented, officials’ home addresses or phone numbers were shared online specifically to encourage organized harassment. Another proposal is requiring boards of health members to have backgrounds related to the field, a response to communities where, the researchers found, people with little or no connection to public health are calling the shots. Both measures aim at structural fixes: one to raise the cost of coordinated intimidation, the other to ensure that the people overseeing health departments have the expertise to evaluate the professionals who run them.

Outside of formal policy, the researchers point toward a longer-term strategy of relationship building. Jones suggested that health officials may build bridges outside of a pandemic by cultivating relationships with different groups in the community who hold different values and viewpoints. Bringing people who disagreed about the pandemic together around issues that matter to them, such as the ongoing opioid crisis, can be powerful, she said. She also emphasized that there is a great deal of work to do to address the vicious polarization in the country, and that for public health officials, part of that work may involve explaining more clearly why they are relevant: the full range of work they do to keep people healthy, from keeping food safe, to helping mothers and babies, to offering people help quitting smoking. The study received funding from the Commonwealth Fund, the Mellon Foundation and the National Science Foundation, and included co-authors from New York University and Syracuse University. Its central warning is that the canaries in this backlash coal mine, as the article’s title puts it, were public health officers, and that what happened to them during the pandemic foreshadows a broader political crisis that the nation has yet to resolve.

Subject of Research: Post-pandemic harassment and threats against US public health officials and strategies to reduce the backlash

Article Title: Public health leaders report widespread harassment, threats after COVID-19

Article References: Public health leaders report widespread harassment, threats after COVID-19. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: public health, COVID-19, harassment, threats, backlash, health officials, American Journal of Public Health, doxing, civil discourse, polarization, workforce, policy

The theoretical foundation of the study rests on Social Representations Theory, a framework first proposed by social psychologist Serge Moscovici in 1961. The theory examines the commonsense knowledge that groups produce through social communication, and it identifies two core processes: objectification, in which abstract ideas become concrete and real, and anchoring, in which new information is integrated into pre-existing systems of thought. Crucially, later work by William Doise and colleagues argued that social representations are not necessarily sets of fully shared beliefs. Instead, they function as organizing principles of position-taking, meaning that people can hold divergent, even opposing, views of the same object while remaining anchored in a common symbolic framework. This insight is what makes the Brazilian case so revealing: consensus and dissensus coexist, structured by deeper shared principles.

Brazil offers a particularly fertile setting for such an investigation. The country’s contemporary political landscape is marked by intense polarization, weakening democratic institutions, and the strategic mobilization of historical narratives by political actors seeking to reshape collective memory along ideological lines. The authors note that the traditional founding myth of racial democracy, the idea that Brazil’s identity rests on harmonious fusion of white, Black, and indigenous peoples, has lost its unifying power. As animosity between political camps has grown, this myth has diluted, leaving social groups more distant from one another and national identities more fragmented. In a polarized environment, competing versions of the past become weapons in symbolic conflicts over the present.

To capture these dynamics empirically, the researchers recruited 420 Brazilian adults through online channels, including messaging groups and university networks, supplemented by snowball sampling. The sample included 173 participants aged 18 to 30, 111 aged 45 to 65, 98 aged 30 to 45, and 9 over 65. Women made up 63 percent of respondents, and politically, 38.2 percent identified with the Left, 34.7 percent with the Center, 9.5 percent with the Right, and 17.6 percent with no political camp. Each participant rated their positive and negative emotions toward ten historical events on a seven-point scale: the Arrival of the Portuguese Royal Family, Independence, Abolition of Slavery, the Proclamation of the Republic, the Military Dictatorship, the Free Vote Movement, the 1988 Federal Constitution, the Real Plan, the Covid-19 pandemic, and the 2022 presidential election.

The analytical engine of the study was Latent Profile Analysis, a statistical technique conducted in RStudio that identifies hidden subgroups within a sample based on patterns of responses. Similar in spirit to factor analysis, LPA uses mixture modeling to cluster individuals who answer in statistically similar ways, producing mutually exclusive profiles. The researchers evaluated competing models using three indicators: the Akaike Information Criterion and the Bayesian Information Criterion, both of which favor simpler, more efficient models with lower values, and Entropy, which measures classification accuracy on a scale from 0 to 1. After balancing these indicators, a six-subgroup model emerged as the best statistical fit, revealing six distinct ways of emotionally positioning oneself toward Brazilian history.

The first profile, labeled Nationalists, tended to rate highly positive those events that showcased Brazilian autonomy and initiative, such as Independence, the Proclamation of the Republic, and the homegrown economic stabilization program known as the Real Plan, while rating lower events in which Brazil did not take the leading role, like the arrival of the Portuguese Royal Family. A second profile, the Youth Nationalists, shared much of this national pride but diverged in evaluating the 1980s: they rated the Free Vote Movement and the 1988 Constitution lower, while expressing strong positivity toward the 2022 election. As their name suggests, 58.1 percent of this group was under 30, illustrating how social insertion, in this case generational position, shapes position-taking on the national past.

The Democrats profile, representing 8.8 percent of the sample and composed predominantly of women with left-wing affiliations, celebrated events embodying equality and citizenship, such as the Free Vote Movement and the Citizen Constitution of 1988, while rating the Royal Family’s arrival and the Military Dictatorship negatively. Intriguingly, this group also rated Abolition of Slavery lower than other profiles did. The authors interpret this not as a rejection of emancipation but as a historically informed disillusionment: abolition in 1888 functioned largely as a legal rupture that left the hierarchies of the slaveholding elite intact, and the Democrats’ enthusiasm for the 1988 Constitution suggests they value events that produced genuine structural change over symbolic milestones that did not. The Oligarchs profile, by contrast, was exclusively male and half right-leaning, and it rated events concentrating power in specific groups, such as the Royal Family’s arrival and the Military Dictatorship, very positively, while disfavoring egalitarian moments like the Republic’s proclamation and the 1988 Constitution.

Two further profiles completed the picture. The Historical Constants, 7.38 percent of the sample, rated nearly all events uniformly high, above 4.5 except for the dictatorship, showing little differentiation. Drawing on prior cross-cultural research by Hanke and colleagues, the authors interpret this consistency not as disengagement but as a distinct evaluative orientation marked by low polarization and a preference for non-extreme positions. Finally, the Republicans, the largest profile at 45.47 percent, displayed strongly polarized ratings: extreme positivity toward Independence, the Republic’s proclamation, abolition, the 1988 Constitution, and the 2022 election, paired with sharp negativity toward the dictatorship and monarchical power. Predominantly female and left-affiliated, this group exemplifies what Doise described as emotionally charged consensus anchored in core moral beliefs, a cohesive collective narrative celebrating democratic institutions and civic engagement.

Perhaps the study’s most striking theoretical contribution lies in what unites these six divergent profiles. Despite their conflicting evaluations, all subgroups appear organized around a single common principle: an orientation toward a project for society and an imagined collective future. The same event can serve as a utopia for one group and a dystopia for another, a future to be achieved or a future to be avoided. Building on work by Zittoun and Gillespie on collective imagination and by de Saint-Laurent on the role of memory in envisioning possible futures, the authors argue that remembering is fundamentally future-oriented. Groups select which past events to valorize in order to delineate the society they wish to construct, effectively sketching competing versions of Brazilian national identity. The authors caution that their sample, recruited online and overrepresenting left-leaning participants, does not fully represent Brazil’s population, and that the single-item emotional scale cannot capture participants’ subjective meanings directly. Still, the findings carry practical weight: in a world marked by rising polarization, understanding how groups use memory to imagine the future may illuminate not only what divides societies, but also what could bring them together.

Subject of Research: Group variations in emotional position-taking toward major Brazilian historical events and their link to imagined collective futures

Article Title: Historical Memories of Great Brazilian Events: Group Variations in Position-Taking

Article References: Eskinazi, R., de Fátima de Souza Santos, M., & Wagoner, B. (2026). Historical Memories of Great Brazilian Events: Group Variations in Position-Taking. Trends in Psychology. https://doi.org/10.1007/s43076-026-00517-8

Image Credits: AI Generated

DOI: 10.1007/s43076-026-00517-8

Keywords: collective memory, social representations, Brazil, historical memory, Latent Profile Analysis, social psychology, polarization, national identity, political affiliation, collective future, Trends in Psychology, intergroup relations