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To investigate the relationship between maximal exercise capacity measured before severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and hospitalization due to coronavirus disease 2019 (COVID-19).


Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2017) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2018) were collected by the National Center for Health Statistics. In 2021, 1,898,160 new cancer cases and 608,570 cancer deaths are projected to occur in the United States. After increasing for most of the 20th century, the cancer death rate has fallen continuously from its peak in 1991 through 2018, for a total decline of 31%, because of reductions in smoking and improvements in early detection and treatment. This translates to 3.2 million fewer cancer deaths than would have occurred if peak rates had persisted. Long-term declines in mortality for the 4 leading cancers have halted for prostate cancer and slowed for breast and colorectal cancers, but accelerated for lung cancer, which accounted for almost one-half of the total mortality decline from 2014 to 2018. The pace of the annual decline in lung cancer mortality doubled from 3.1% during 2009 through 2013 to 5.5% during 2014 through 2018 in men, from 1.8% to 4.4% in women, and from 2.4% to 5% overall. This trend coincides with steady declines in incidence (2.2%-2.3%) but rapid gains in survival specifically for nonsmall cell lung cancer (NSCLC). For example, NSCLC 2-year relative survival increased from 34% for persons diagnosed during 2009 through 2010 to 42% during 2015 through 2016, including absolute increases of 5% to 6% for every stage of diagnosis; survival for small cell lung cancer remained at 14% to 15%. Improved treatment accelerated progress against lung cancer and drove a record drop in overall cancer mortality, despite slowing momentum for other common cancers.


Recurrent major depressive disorder (rMDD) is a relapsing-remitting disease with high morbidity and a 5-year risk of recurrence of up to 80%. This was a prospective pilot study to examine the potential diagnostic and prognostic value of targeted plasma metabolomics in the care of patients with rMDD in remission. We used an established LC-MS/MS platform to measure 399 metabolites in 68 subjects with rMDD (n = 45 females and 23 males) in antidepressant-free remission and 59 age- and sex-matched controls (n = 40 females and 19 males). Patients were then followed prospectively for 2.5 years. Metabolomics explained up to 43% of the phenotypic variance. The strongest biomarkers were gender specific. 80% of the metabolic predictors of recurrence in both males and females belonged to 6 pathways: (1) phospholipids, (2) sphingomyelins, (3) glycosphingolipids, (4) eicosanoids, (5) microbiome, and (6) purines. These changes traced to altered mitochondrial regulation of cellular redox, signaling, energy, and lipid metabolism. Metabolomics identified a chemical endophenotype that could be used to stratify rrMDD patients at greatest risk for recurrence with an accuracy over 0.90 (95%CI = 0.69-1.0). Power calculations suggest that a validation study of at least 198 females and 198 males (99 cases and 99 controls each) will be needed to confirm these results. Although a small study, these results are the first to show the potential utility of metabolomics in assisting with the important clinical challenge of prospectively identifying the patients at greatest risk of recurrence of a depressive episode and those who are at lower risk.


Political disagreements in social media can result in removing (i.e., “unfriending”) a person from one’s online network. Given that such actions could lead to the (ideological) homogenization of networks, it is pivotal to understand the psychological processes intertwined in unfriending decisions. This requires not only addressing different types of disagreements but also analyzing them in the relational context they occur. This article proposes that political disagreements leading to drastic measures such as unfriending are attributable to more deeply rooted moral dissents. Based on moral foundations theory and relationship regulation research, this work presents empirical evidence from two experiments. In both studies, subjects rated political statements (that violated different moral foundations) with regard to perceived reprehensibility and the likelihood of unfriending the source. Study 1 (N = 721) revealed that moral judgments of a political statement are moderately related to the unfriending decision. Study 2 (N = 822) replicated this finding but indicated that unfriending is less likely when the source of the morally reprehensible statement is relationally close to the unfriender and provides emotional support. This research extends unfriending literature by pointing to morality as a new dimension of analysis and offers initial evidence uncovering the psychological trade-off behind the decision of terminating digital ties. Drawing on this, our findings inform research on the homogenization of online networks by indicating that selective avoidance (in the form of politically motivated unfriending) is conditional upon the relational context and the interpersonal benefits individuals receive therein.


Understanding public attitudes towards death is needed to inform health policies to foster community death awareness and preparedness. Linguistic sentiment analysis of how people describe their feelings about death can add to knowledge gained from traditional self-reports. This study provided the first description of emotive attitudes expressed towards death utilising textual sentiment analysis for the dimensions of valence, arousal and dominance. A linguistic lexicon of sentiment norms was applied to activities conducted in an online course for the general-public designed to generate discussion about death. We analysed the sentiment of words people chose to describe feelings about death, for themselves, for perceptions of the feelings of ‘others’, and for longitudinal changes over the time-period of exposure to a course about death (n = 1491). The results demonstrated that sadness pervades affective responses to death, and that inevitability, peace, and fear were also frequent reactions. However, words chosen to represent perceptions of others' feelings towards death suggested that participants perceived others as feeling more negative about death than they do themselves. Analysis of valence, arousal and dominance dimensions of sentiment pre-to-post course participation demonstrated that participants chose significantly happier (more positive) valence words, less arousing (calmer) words, and more dominant (in-control) words to express their feelings about death by the course end. This suggests that the course may have been helpful in participants becoming more emotionally accepting in their feelings and attitude towards death. Furthermore, the change over time appeared greater for younger participants, who showed more increase in the dominance (power/control) and pleasantness (valence) in words chosen at course completion. Sentiment analysis of words to describe death usefully extended our understanding of community death attitudes and emotions. Future application of sentiment analysis to other related areas of health policy interest such as attitudes towards Advance Care Planning and palliative care may prove fruitful.


Human perception is based on expectations. We expect visual upright and gravity upright, sensed through vision, vestibular and other sensory systems, to agree. Equally, we expect that visual and vestibular information about self-motion will correspond. What happens when these assumptions are violated? Tilting a person from upright so that gravity is not where it should be impacts both visually induced self-motion (vection) and the perception of upright. How might the two be connected? Using virtual reality, we varied the strength of visual orientation cues, and hence the probability of participants experiencing a visual reorientation illusion (VRI) in which visual cues to orientation dominate gravity, using an oriented corridor and a starfield while also varying head-on-trunk orientation and body posture. The effectiveness of the optic flow in simulating self-motion was assessed by how much visual motion was required to evoke the perception that the participant had reached the position of a previously presented target. VRI was assessed by questionnaire When participants reported higher levels of VRI they also required less visual motion to evoke the sense of traveling through a given distance, regardless of head or body posture, or the type of visual environment. We conclude that experiencing a VRI, in which visual-vestibular conflict is resolved and the direction of upright is reinterpreted, affects the effectiveness of optic flow at simulating motion through the environment. Therefore, any apparent effect of head or body posture or type of environment are largely indirect effects related instead, to the level of VRI experienced by the observer. We discuss potential mechanisms for this such as reinterpreting gravity information or altering the weighting of orientation cues.


Despite growing recognition among journalists and political pundits, the concept of victimhood has been largely ignored in empirical social science research. In this article, we develop a theory about, and use unique nationally-representative survey data to estimate, two manifestations of victimhood: an egocentric one entailing only perceptions of one’s own victimhood, and one focused on blaming “the system.” We find that these manifestations of victimhood cut across partisan, ideological, and sociodemographic lines, suggesting that feelings of victimhood are confined to neither “actual” victims nor those partisans on the losing side of elections. Moreover, both manifestations of victimhood, while related to candidate support and various racial attitudes, prove to be distinct from related psychological constructs, such as (collective) narcissism, system justification, and relative deprivation. Finally, an experiment based on candidate rhetoric demonstrates that some political messaging can make supporters feel like victims, which has consequences for subsequent attitudes and behavior.


Across a wide range of studies, researchers often conclude that the home environment and children’s outcomes are causally linked. In contrast, behavioral genetic studies show that parents influence their children by providing them with both environment and genes, meaning the environment that parents provide should not be considered in the absence of genetic influences, because that can lead to erroneous conclusions on causation. This article seeks to provide behavioral scientists with a synopsis of numerous methods to estimate the direct effect of the environment, controlling for the potential of genetic confounding. Ideally, using genetically sensitive designs can fully disentangle this genetic confound, but these require specialized samples. In the near future, researchers will likely have access to measured DNA variants (summarized in a polygenic scores), which could serve as a partial genetic control, but that is currently not an option that is ideal or widely available. We also propose a work around for when genetically sensitive data are not readily available: the Familial Control Method. In this method, one measures the same trait in the parents as the child, and the parents' trait is then used as a covariate (e.g., a genetic proxy). When these options are all not possible, we plead with our colleagues to clearly mention genetic confound as a limitation, and to be cautious with any environmental causal statements which could lead to unnecessary parent blaming.


Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.


Although the key role of long-distance trade in the transformation of cuisines worldwide has been well-documented since at least the Roman era, the prehistory of the Eurasian food trade is less visible. In order to shed light on the transformation of Eastern Mediterranean cuisines during the Bronze Age and Early Iron Age, we analyzed microremains and proteins preserved in the dental calculus of individuals who lived during the second millennium BCE in the Southern Levant. Our results provide clear evidence for the consumption of expected staple foods, such as cereals (Triticeae), sesame (Sesamum), and dates (Phoenix). We additionally report evidence for the consumption of soybean (Glycine), probable banana (Musa), and turmeric (Curcuma), which pushes back the earliest evidence of these foods in the Mediterranean by centuries (turmeric) or even millennia (soybean). We find that, from the early second millennium onwards, at least some people in the Eastern Mediterranean had access to food from distant locations, including South Asia, and such goods were likely consumed as oils, dried fruits, and spices. These insights force us to rethink the complexity and intensity of Indo-Mediterranean trade during the Bronze Age as well as the degree of globalization in early Eastern Mediterranean cuisine.