The research team set out to address a fundamental question: how does the quality of news content shared on social media correlate with user engagement across politically diverse platforms? Traditionally, much of the focus in this domain has been on Twitter (now known as X), primarily due to its open API and accessibility for academic scrutiny. Previous studies posited that right-leaning news outlets and users were disproportionately successful in garnering attention, especially for lower-quality or misleading information. However, Cornell’s latest research ventures beyond the confines of a single platform to examine seven diverse social media sites simultaneously, bringing a fresh and expansive perspective to the conversation.

The platforms selected represent a broad spectrum of political ideologies and community norms: BlueSky, Mastodon, LinkedIn, and Twitter/X were categorized as more liberal or politically neutral, while TruthSocial, Gab, and GETTR were identified with conservative leanings. By capturing every post containing links to news domains during January 2024—a total nearing 11 million posts—the researchers amassed an unprecedented dataset ripe for robust computational analysis. Their methodological rigor included isolating the effects attributable to content quality itself, independent of poster characteristics such as follower count or platform influence.

Central to the study is the operationalization of news quality. Instead of content-specific accuracy assessments, the team employed an established reliability rating system developed in 2023, which synthesizes numerous expert evaluations to assign credibility scores to over 11,000 news domains. This method offers a scalable proxy to estimate the veracity of linked news sources across millions of posts. Additionally, political orientation was ascertained and validated, allowing the researchers to correlate engagement trends with ideological alignment intrinsic to both the platform and the source material.

One of the most provocative findings is the consistent pattern whereby posts linked to lower-quality news receive higher engagement—measured through likes, shares, and comments—across every platform studied, irrespective of political stance. This phenomenon persists not only within algorithm-driven environments like Twitter/X and TruthSocial but also on platforms like Mastodon, which eschews ranking algorithms altogether. This strongly suggests that user preference, rather than automated amplification mechanisms alone, plays a decisive role in favoring sensational or less reliable news content.

The study nuanced earlier claims about ideological asymmetry by demonstrating that the amplification of low-quality news is not exclusive to the right-wing or conservative platforms. Although platforms with conservative user bases tend to share, on average, somewhat lower-quality news, the relative engagement advantage of such news over higher-quality content manifests equally on left-leaning sites. This “echo platform” effect, where conformity to the platform’s dominant political tone heightens engagement, underscores the role of identity affirmation and social reinforcement in shaping online information ecosystems.

Furthermore, the researchers controlled for numerous confounding variables to firmly attribute engagement differences to the content’s characteristics alone. This disentanglement from poster influence is critical, as it mitigates biases arising from highly followed users or influencers whose reach could otherwise skew results. By logarithmically adjusting for follower count and other user attributes, the study robustly demonstrates that quality deficits in news content, not the stature of the individual disseminator, predominantly account for increased virality on social media.

Beyond its implications for understanding digital information dissemination, the study holds significant import for public policy and platform design. The data signal a need to reconsider how social media ecosystems might inadvertently encourage the spread of unreliable information through inherent user preferences and social dynamics. Interventions that solely focus on algorithmic content moderation may be insufficient if user engagement patterns inherently favor sensational or partisan news regardless of accuracy.

David Rand, the lead investigator and professor whose expertise spans information science, marketing, management communication, and psychology, articulates the complexity of these dynamics. He compares social media interactions to “echo platforms,” where users affiliate with ideologically congruent content, and their engagement is heightened when such content aligns with the platform norm. This insight reconciles the paradox where misinformation appears virally potent across political divides, challenging the popular narrative that one ideological faction disproportionately drives misinformation spread.

The study also critically revisits the conclusions of the 2018 Science article that predominantly analyzed Twitter data and suggested particular political groups excelled at stoking false news engagement. By broadening the scope across multiple sites and incorporating political diversity among platforms, the current research refines and expands this earlier understanding, emphasizing the heterogeneity of social media landscapes and the limitations of generalizations drawn from single-platform studies.

Funding for this extensive research was provided by the Open Society Foundation, emphasizing the importance placed on unearthing empirical evidence to guide effective strategies in combating misinformation. The team’s work, published in the prestigious Proceedings of the National Academy of Sciences, exemplifies rigorous multidisciplinary scholarship. By merging computational social science with psychology and media studies, the research sets a new standard for future inquiries into the digital information age.

Cornell’s analysis offers urgent, data-driven insights to social media companies, policymakers, and users alike. Understanding that the problem of low-quality news engagement is endemic and ideologically widespread demands multifaceted responses that transcend partisan politics. Efforts to promote media literacy, incentivize high-quality journalism, and design platforms with nuanced user behavior in mind are crucial next steps supported by this landmark study.

This large-scale, methodologically robust analysis highlights the complex realities of modern social media engagement with partisan and low-quality news. It underscores the imperative to address the underlying human and systemic factors perpetuating misinformation in the digital sphere.

Subject of Research: Patterns of engagement with partisan and low-quality news across diverse social media platforms
Article Title: Divergent Patterns of Engagement With Partisan and Low-quality News Across Seven Social Media Platforms
News Publication Date: 30-Oct-2025
Web References: http://dx.doi.org/10.1073/pnas.2425739122
References: David Rand et al., Proceedings of the National Academy of Sciences, 2025
Keywords: social media, mass media, communications, social sciences

Tadpoles, the aquatic larval stage of frogs, utilize three primary mechanisms to obtain oxygen: aerial respiration via lungs, aquatic respiration through gills, and cutaneous respiration through their permeable skin. Unlike many amphibians, all adult frogs possess lungs, and their tadpoles typically develop these organs during larval stages. Despite this conserved developmental pathway, certain tadpoles have secondarily lost their lungs throughout evolutionary time, opting for alternative respiratory strategies in specialized habitats.

The comprehensive study, published on October 27, 2025, in the peer-reviewed journal Evolution, systematically investigates the evolutionary trajectories of lung loss across over 530 frog species representing almost every family and myriad genera. Among these, there are 28 distinct instances of lung loss identified. Globally, out of more than 5,000 frog species, only 95 are known to possess lungless tadpoles. The researchers employed advanced phylogenetic methods integrating genetic data and computational modeling to reconstruct ancestral states and to infer the ecological contexts under which lung loss occurred.

Analysis of these evolutionary events revealed striking ecological correlations. In fast-flowing stream environments, where water is consistently rich in dissolved oxygen, lungs may confer a disadvantage due to their buoyancy effects. Tadpoles with lungs might be inadvertently swept away by the current, reducing their chances of survival. Consequently, numerous lungless tadpoles have evolved specialized morphological traits, such as sucker mouths that enable them to cling to rocks and resist displacement in turbulent waters.

Interestingly, lungless tadpoles are not restricted to aquatic microhabitats within streams. Some species demonstrate terrestrial reproductive strategies whereby eggs are deposited in nests on land, often adjacent to moist zones near streams. These terrestrial tadpoles also display lung loss, underscoring a complex pattern of respiratory adaptation that transcends purely aquatic environments. Notably, despite the prevalence of pond habitats among extant frog species for tadpole development, evidence suggests that lung loss in pond-dwelling tadpoles has been a rare evolutionary event.

The findings prompt intriguing hypotheses concerning the selective pressures that drive lung loss. It is posited that the disadvantages of surface air-breathing—such as increased predation risk when surfacing or the energetic costs associated with traveling to the air-water interface—may create stronger selective constraints than the mere presence of lungs themselves. Thus, it might be more accurate to conceive lung loss as an indirect outcome of selective pressures against surface air-breathing behaviors.

From a developmental genetics standpoint, the conservation of lung developmental pathways in species with lungless tadpoles is particularly perplexing. This retention suggests that the genetic machinery required for lung formation remains latent but unused, and yet, evolution has repeatedly opted not to reactivate this developmental program even when beneficial. This empirical evidence complicates previously held assumptions that the re-emergence of lost traits is facilitated by the preservation of underlying genetic frameworks.

Moreover, this study underscores the unpredictable nature of evolutionary innovation. While the loss of complex organs like lungs appears to be evolutionarily “predictable” and repeatedly chosen under certain environmental contexts, the compensatory adaptations—that is, replacing lung function with alternative respiratory strategies—are varied and often unexpected. This diversity of adaptation illustrates the rich landscape of evolutionary solutions to similar ecological challenges.

The research methods involved synthesizing extensive phylogenetic trees constructed through DNA sequencing and molecular analysis, which enabled precise mapping of evolutionary trait changes over tens of millions of years. Coupled with ecological data on habitat preferences and physiological studies on oxygen acquisition efficiency, the study provides a comprehensive framework for understanding respiratory evolution in amphibians.

This study has broad implications for the field of evolutionary biology, particularly in understanding the constraints and opportunities in trait regain versus irreversible trait loss. It challenges the formerly held belief that evolutionary reversals are common and straightforward when the genetic and developmental substrates remain. Instead, it paints a picture of evolutionary pathways governed by a mixture of genetic potential, ecological demands, and selective pressures that may irreversibly close developmental options over time.

In conclusion, the lungless tadpole study illuminates the intricate balance between genetic retention and ecological necessity shaping amphibian evolution. It not only elucidates the mechanisms underlying respiratory adaptations in frogs but also informs larger questions about the evolutionary dynamics of trait loss and regain across diverse taxa. This research invites further inquiry into the molecular and environmental factors that prevent trait regeneration and enriches our understanding of how organisms navigate the evolutionary landscape.

Subject of Research: Evolutionary biology of respiratory adaptations in tadpoles
Article Title: Lungless tadpoles breathe fresh air into hypotheses for tetrapod lung loss and trait regain
News Publication Date: 27-Oct-2025
Web References: http://dx.doi.org/10.1093/evolut/qpaf192
References: Phillips J., Womack M., et al. (2025). Lungless tadpoles breathe fresh air into hypotheses for tetrapod lung loss and trait regain. Evolution. https://doi.org/10.1093/evolut/qpaf192
Keywords: Evolution, Evolutionary biology, Frogs, Amphibians, Respiratory adaptation, Lung loss, Trait regain, Phylogenetics, Developmental genetics

ME/CFS, characterized by profound fatigue, cognitive dysfunction, post-exertional malaise, and multi-systemic symptoms, has long challenged clinicians due to the absence of reliable diagnostic tests. The disease’s clinical overlap with other disorders renders symptom-based diagnosis problematic. Addressing this diagnostic void, the Cornell team has developed computational models capable of discerning disease-specific cfRNA patterns, essentially reading the molecular “activity logs” cells leave behind as they undergo damage or death. By capturing these cellular footprints, the study brings the prospect of a minimally invasive blood-based assay closer to reality.

The research, recently published on August 11, 2025, in the prestigious Proceedings of the National Academy of Sciences, details how plasma samples from ME/CFS patients and sedentary healthy controls were analyzed to isolate and sequence extracellular RNA fragments. These fragments serve as proxies for gene expression profiles from diverse tissues impacted by the disease. Utilizing advanced machine-learning classifiers, the team identified over 700 transcripts significantly divergent between ME/CFS cases and controls, facilitating a molecular signature indicative of the syndrome.

Leading the study, Anne Gardella, a doctoral candidate specializing in biochemistry, molecular, and cell biology at Cornell University, highlighted the unique capability of this method to shed light on systemic cellular alterations. “The circulating cfRNA reflects a composite snapshot of cellular turnover and stress responses occurring throughout the body,” Gardella explained. “This allows us to map disease-associated molecular changes across multiple organ systems simultaneously, which is crucial given ME/CFS’s widespread physiological impacts.”

The project was conceived through a collaboration between the De Vlaminck Lab, under associate professor Iwijn De Vlaminck, renowned for pioneering cell-free nucleic acid technologies, and Dr. Maureen Hanson’s team, leaders in ME/CFS pathophysiology research. De Vlaminck’s laboratory previously demonstrated the diagnostic power of cfRNA in identifying Kawasaki disease and multisystem inflammatory syndrome in children (MIS-C), signaling the versatility of this approach in inflammatory and immune-mediated conditions.

This interdisciplinary effort leveraged deep computational analysis, applying machine-learning algorithms adept at handling high-dimensional data to uncover patterns invisible to conventional statistical methods. These computational models not only confirmed immune dysregulation known to occur in ME/CFS but also implicated extracellular matrix disorganization and T cell exhaustion, signaling broad immune dysfunction and tissue remodeling abnormalities. Such insights provide a more nuanced biological framework for understanding ME/CFS beyond symptomatology.

Crucially, the team employed deconvolution techniques informed by cell type-specific gene expression markers, drawn from prior single-cell RNA sequencing data, to pinpoint the cellular origins of the cfRNA. This revealed six distinct cell types with differential RNA signatures in ME/CFS patients, with plasmacytoid dendritic cells—the primary producers of type I interferons—showing the most significant elevation. This finding suggests an aberrant antiviral immune activation state underpinning the disease’s chronicity.

Monocytes, platelets, and various T cell subsets also displayed altered cfRNA levels, reinforcing the hypothesis of systemic immune dysregulation. These immune perturbations may contribute to the constellation of symptoms experienced by patients, from neuroinflammation to vascular dysfunction. The data also hint at persistent immune activation or unresolved viral triggers, potentially connecting to the hypothesis of post-infectious etiologies for ME/CFS.

The cfRNA-based classifier developed achieved an accuracy rate of 77% in distinguishing ME/CFS patients from controls—a promising but preliminary figure. While this degree of precision is insufficient to constitute a standalone diagnostic tool today, it represents a significant leap forward given the historical diagnostic ambiguity surrounding ME/CFS. Improvements with larger cohorts and integration with other biomarkers could enhance diagnostic performance, ultimately aiding clinicians in making objective, timely diagnoses.

Beyond diagnostics, the technology offers a potent research instrument to dissect the multifaceted biology of ME/CFS and related chronic illnesses such as long COVID. Notably, while long COVID has recently amplified awareness of post-infectious chronic syndromes, ME/CFS remains more prevalent and, in many cases, more severely disabling. The Cornell team’s innovation could therefore serve as a reference model for studying infection-associated chronic diseases with overlapping symptomatology but distinct molecular fingerprints.

The study benefits from strong support by the National Institutes of Health and the WE&ME Foundation, underscoring the growing prioritization of ME/CFS research funding. The research’s translational potential is considerable, potentially catalyzing the development of future blood-based assays to monitor disease activity and therapeutic response, thereby personalizing patient care amidst a historically neglected field.

This research is a testament to the power of integrating molecular biology, computational science, and clinical insight to address one of medicine’s most confounding syndromes. With further validation and technological refinement, circulating cfRNA analysis stands to revolutionize not only ME/CFS diagnosis but also our understanding of chronic, systemic illnesses long shrouded in mystery, marking a new frontier in precision diagnostics.

Subject of Research: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and circulating cell-free RNA biomarkers

Article Title: Circulating cell-free RNA signatures for the characterization and diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome

News Publication Date: 11-Aug-2025

Web References:

• DOI: 10.1073/pnas.2507345122

Keywords: Chronic fatigue syndrome, diseases and disorders, health and medicine