Browse Articles

Water Cooperativity Impacts Aromatic Interactions in the Aggregation of Benzene with Water

Faster adaptation but slower divergence of X chromosomes under paternal genome elimination

Subnational survey data reveal persistent gaps in living standards across 75 low and middle-income countries

Structure–Emission Property Relationship of Bilayer 2D Hybrid Perovskites

Molecular patterns and mechanisms of tumorigenesis in HPV-associated and HPV-independent sinonasal squamous cell carcinoma

Abstract Mechanisms of tumorigenesis in sinonasal squamous cell carcinoma (SNSCC) remain poorly understood due to its rarity. A subset of SNSCC is associated with human papillomavirus (HPV), but it is unclear whether HPV drives tumorigenesis or acts as a neutral bystander. Here, we show that HPV-associated SNSCC shares mutational patterns found in HPV-associated cervical and head and neck squamous cell carcinoma, including lack of TP53 mutations, hotspot mutations in PI3K and FGFR3 , enrichment of APOBEC mutagenesis, viral integration at known hotspots, and frequent epigenetic regulator alterations. We identify HPV-associated SNSCC-specific recurrent mutations in KMT2C , UBXN11 , AP3S1 , MT-ND4 , and MT-ND5 , with KMT2D and FGFR3 mutations correlating with reduced overall survival. We establish an HPV-associated SNSCC cell line, showing that combinatorial small-molecule inhibition of YAP/TAZ and PI3K synergistically suppresses clonogenicity. Combining YAP/TAZ blockade with vertical PI3K inhibition may benefit HPV-associated SNSCC, whereas targeting MYC and horizontal inhibition of RAS/PI3K may suit HPV-independent SNSCC.

Ventral hippocampus neurons encode meal-related memory

Multiple intramolecular triggers converge to preferential G protein coupling in the CB2R

Addressing critiques refines global estimates of reforestation potential for climate change mitigation

Abstract Reforestation is a prominent climate change mitigation strategy, but available global maps of reforestation potential are widely criticized and highly variable, which limits their ability to provide robust estimates of both the locations and total area of opportunity. Here we develop global maps that address common critiques, build on a review of 89 reforestation maps created at multiple scales, and present eight reforestation scenarios with varying objectives, including providing ecosystem services, minimizing social conflicts, and delivering government policies. Across scenarios, we find up to 195 Mha (million hectares) are available (2225 TgCO2e (teragrams of carbon dioxide equivalent) per year total net mitigation potential), which is 71–92% smaller than previous estimates because of conservative modeling choices, incorporation of safeguards, and use of recent, high-resolution datasets. This area drops as low as 6 Mha (53 TgCO2e per year total net mitigation potential) if only statutorily protected areas are targeted. Few locations simultaneously achieve multiple objectives, suggesting that a mix of lands and restoration motivations will be needed to capitalize on the many potential benefits of reforestation.

Two-year-olds’ visual exploration of response options during memory decisions predicts metamemory monitoring one year later

Abstract Introspection on memory states guides decision-making, but little is known about how it emerges in childhood. Toddlers’ behavioral responses to difficult memory decisions (e.g., information seeking) suggest early capacity to track uncertain situations, but it is unclear whether these behaviors relate to later emerging capacity to introspect on memory accuracy (i.e., metamemory monitoring). In a pre-registered longitudinal study, 176 25- to 34-month-olds encode images, then are asked to select the familiar image from arrays that also include a new image (Time 1). One year later (Time 2), 157 participants complete a similar memory task and report decision confidence. Higher gaze transitions between responses, indicative of evaluation processes, faster response latencies, and greater memory at Time 1 predict Time 2 metamemory monitoring (i.e., greater confidence for accurate than inaccurate decisions). At Time 2, gaze transitions are associated with lower overall confidence. Overall, this research reveals potential building blocks of emerging metamemory monitoring.

Seasonality dominates changes in lake-surface extent and aligns with human residence

Tiny rotating device puts a new spin on blood-clot removal

This stretchy neural implant grows with an axolotl’s brain

NIH chief stands by funding cuts to ‘politicized science’ at tense hearing

Daily briefing: The moment that mathematics education starts to fail girls

Liquid carbon formed using a high-energy laser

Meet the MIT engineer who invented an AI-powered way to restore art

Various cell types in tissues cooperate in networks that are disrupted in disease

An open AI model could help medical experts to interpret chest X-rays

Dispersal dynamics of white-tailed deer in human-altered landscapes and implications for disease risk

Animal dispersal and migration can play critical roles in population dynamics and species distribution, and these behaviors often are influenced by their environment. The conversion from natural habitats to agricultural lands has altered over 40% of terrestrial surfaces and many wildlife species now inhabit landscapes that are fragmented or heavily composed of agriculture. Understanding how habitat drives patterns of dispersal or migration is of critical importance to population management, particularly in environments that may be changing rapidly with human presence and when considering emerging disease threats. We evaluated how habitat and agriculture in and around white-tailed deer natal ranges in southeastern Minnesota, USA influenced both the probability of dispersal and migration events and the distance animals traveled during those events. Counter to our predictions, we found no evidence that agriculture in the natal range influenced the probability that white-tailed deer would disperse or migrate. Sex, however, played an important role in shaping movement behaviors—compared with resident deer, males were 2.7 times more likely to disperse and 5.2 times less likely to migrate than females. Moreover, while agriculture did not influence the probability of a dispersal event occurring, it did influence the distance traveled with deer dispersing farther in areas with more agriculture and avoiding agriculture during dispersal events. Our results provide insight into the influence of habitat on key movement behaviors that may be extremely important for population management, especially in areas that may have a high prevalence of infectious disease.

Development and validation of an interpretable longitudinal preeclampsia risk prediction using machine learning

Preeclampsia is a pregnancy-specific disease characterized by new onset hypertension after 20 weeks of gestation that affects 2–8% of all pregnancies and contributes to up to 26% of maternal deaths. Despite extensive clinical research, current predictive tools fail to identify up to 66% of patients who develop preeclampsia. We sought to develop a tool to longitudinally predict preeclampsia risk. In this retrospective model development and validation study, we examined a large cohort of patients who delivered at three hospitals in the New England region between 05/2015 and 05/2023. We used sociodemographic, clinical diagnoses, family history, laboratory, and vital signs data. For external validation, we used the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b) cohort (2010–2013), which contained data from eight external sites in the US. Models were developed at eight gestational time points using logistic regression, elastic net, naïve-Bayes, random forest, xgboost, and deep neural network methods. We used Shapley values to investigate the relationships between features. Our study population (N = 101,357) had an incidence of preeclampsia of 6.1% (N = 6,160). Model AUCs ranged from 0.71–0.80 (95%CI 0.69–0.82), externally validated in the nuMoM2b cohort with an AUC range of 0.57–0.70 (95%CI 0.55–0.73). No significant differences in performance were found based on race and ethnicity. As these novel models identify more patients at risk for developing preeclampsia, the benefits of this approach need to be balanced with the need for surveillance in a larger at-risk population. This novel preeclampsia prediction approach allows clinicians to identify at-risk patients early and provide personalized predictions throughout pregnancy.