Browse Articles

Real-life intense fear is communicated through context, not facial expressions

Central emotion theories assume that during threatening and dangerous events the human face signals a prototypical, distinct, and universally recognized expression of fear which can be accurately decoded by conspecific perceivers. Due to the importance of fear expressions, an unusually large body of research has been dedicated to exploring their evolutionary origins, neurobiological mechanisms, and clinical significance. However, these studies typically utilize highly recognizable posed actor portrayals presumed to closely resemble the diagnostic physical appearance of real-life fearful faces. Here, we challenge this diagnosticity assumption. Following context-dependent frameworks (Barrett, 2017), we hypothesized that extrafacial context (e.g., situational information, body posture, etc.) plays a far greater role in fear communication than the signal of the isolated face. In 12 preregistered experiments (N = 4,180), we examined the perception of authentic, real-life videos documenting a diverse range of intense fear-inducing situations (e.g., height jumping, physical attacks, exposure to phobia triggers). Participants viewed the face alone, the context with no face, or the full video while various response methods of emotion perception were tested (forced choice, open-ended, multiple emotion scales, valence-arousal ratings). Across experiments, videos of the faces alone failed to communicate fear in a reliable manner. In sharp contrast, context with no faces, and faces with context were clearly and robustly perceived as fearful, with medium to large effect sizes. These findings suggest that despite the undisputed importance of perceiving fear reactions, facial expressions alone bear minimal diagnostic value, while context plays a critical role in real-life fear perception.

Maternal balanced energy-protein supplementation reshapes the maternal gut microbiome and enhances carbohydrate metabolism in infants: a randomized controlled trial

Abstract Balanced energy-protein (BEP) supplementation during pregnancy and lactation can improve birth outcomes and infant growth, with the gut microbiome as a potential mediator. The MISAME-III randomized controlled trial (ClinicalTrial.gov: NCT03533712) assessed the effect of BEP supplementation, provided during pregnancy and the first six months of lactation, on small-for-gestational age prevalence and length-for-age Z-scores at six months in rural Burkina Faso. Nested within MISAME-III, this sub-study examines the impact of BEP supplementation on maternal and infant gut microbiomes and their mediating role in birth outcomes and infant growth. A total of 152 mother-infant dyads (n = 71 intervention, n = 81 control) were included for metagenomic sequencing, with stool samples collected at the second and third trimesters, and at 1–2 and 5–6 months postpartum. BEP supplementation significantly altered maternal gut microbiome diversity, composition, and function, particularly those with immune-modulatory properties. Pathways linked to lipopolysaccharide biosynthesis were depleted and the species Bacteroides fragilis was enriched in BEP-supplemented mothers. Maternal BEP supplementation also accelerated infant microbiome changes and enhanced carbohydrate metabolism. Causal mediation analyses identified specific taxa mediating the effect of BEP on birth outcomes and infant growth. These findings suggest that maternal supplementation modulates gut microbiome composition and influences early-life development in resource-limited settings.

Predictors of internalised stigma among people with mental illness attending a psychiatry outpatient clinic in Ethiopia: Institution based cross sectional study

Background Despite initiatives to increase access to mental health care and improve the quality of life for individuals living with mental illness, there is limited information on internalized stigma and its impact on these individuals. This study aimed to determine the prevalence of internalised stigma and identify associated factors (sociodemographic, clinical, and substance use) among people with mental illness attending an outpatient clinic in Ethiopia. Method Institution-based cross-sectional study was conducted with patients with mental illness at the University of Gondar Hospital clinic. We recruited 638 participants from the clinic using systematic random sampling with an interval of three applied. Internalised stigma was measured using the nine-item (ISMI-9) Internalised stigma of Mental Illness Scale. Variables were coded and entered into SPSS-28 software for further analysis. To analyze the data, we used descriptive and multivariate logistic regression analysis. Adjusted odds ratio (AOR) with 95% confidence interval (CI) and p-value less than 0.05 were considered significant. Results Prevalence of internalised stigma among study participants was 49.1% (95% CI: 45, 52). The following attributes were associated with a greater likelihood of high internalised stigma, participants with no formal education (AOR=2.19, 95% CI:1.33, 3.61); patients with fair self-reported health (AOR=3.12, 95% CI:1.28, 7.59), patients with poor self-reported health (AOR= 9.11, 95% CI: 2.89, 28.73), patients with suicidal ideation (AOR=1.95, 95% CI:1.37, 2.79), alcohol users (AOR= 1.89, 95% CI:1.24,2.91), patient with low self-esteem (AOR=1.55, 95% CI:1.09, 2.21), patient with poor drug adherence (AOR=2.2, 95% CI:1.30,3.71), patients with family history of substance use (AOR= 2.46, 95% CI:1.54,3.93). Conclusions The prevalence of high internalised stigma among patients with mental illness in was high. Therefore, anti-stigma activities, early outpatient support, drug adherence information, and reduction of suicidal behaviors are all necessary to reduce stigma in patients with mental illnesses.

Theoretical modeling and fault diagnosis of pantograph–catenary arc under high-speed airflow

The decade-long growth of government-authored news media in China under Xi Jinping

Autocratic governments around the world use clandestine propaganda campaigns to influence the media. We document a decade-long trend in China toward the planting of government-authored articles in party and commercial newspapers. To examine this phenomenon, we develop an approach to identifying scripted propaganda—the coerced reprinting of lightly adapted government-authored articles in newspapers—that leverages the footprints left by the government when making media interventions. We show that in China, scripted propaganda is a daily phenomenon—on 90% of days from 2012 to 2022, the vast majority of party newspapers include at least some scripted propaganda at the direction of a central directive. On particular sensitive days, the amount of scripted propaganda can spike to 30% of the articles appearing in major newspapers. We show that scripted propaganda has strengthened under President Xi Jinping. In the last decade, the front page of party newspapers has evolved from 5% scripted articles to approximately 20% scripted. This government-authored content throughout the paper is increasingly homogeneous—fewer and fewer adaptations are done by individual newspapers. In contrast to popular speculation, we show that scripted content is not only on ideological topics (although it is increasingly ideological) and is also very prevalent in commercial papers. Using a case study of domestic coverage of COVID-19, we demonstrate how the regime uses scripting to shape, constrain, and delay information during crises. Our findings reveal the wide-ranging influence of government-authored propaganda in China’s media ecosystem.

Unraveling the molecular mechanism of polysaccharide lyases for efficient alginate degradation

Sexual dimorphism does not translate into foraging or trophic niche partitioning in Peruvian boobies (Sula variegata)

Intraspecific competition can lead to sexual segregation of diets or foraging behaviors in seabirds, and in some species the resulting niche partitioning is facilitated by sexual dimorphism. However, environmental stochasticity can mediate intraspecific competition and thus the extent of sex-based partitioning. The Peruvian booby (Sula variegata) is a sexually dimorphic seabird endemic to the Humboldt Current System (HCS), a highly variable environment due to El Niño Southern Oscillation. To determine the extent of sexual partitioning in this species, we quantified the foraging and trophic niches of breeding Peruvian boobies at Isla Guañape Norte, Peru in two years with different oceanographic conditions and nesting propensity. Morphometrics, GPS-tracked foraging behaviors, diets via regurgitates, and isotopic niches were compared between sexes and years where sample sizes permitted. Although females were larger and in better body condition than males, breeding Peruvian boobies in our study did not exhibit sex-specific foraging or isotopic niche partitioning and had few differences in diet. Anchoveta (Engraulis ringens) dominated diets in both years, reflecting Peruvian boobies’ dependence on this prey. Overall, while oceanographic conditions in 2016 were unfavorable enough to reduce nesting propensity, these effects did not qualitatively translate to foraging or dietary niche partitioning between the sexes for those individuals who opted to breed. In combination, our results suggest weak intraspecific competition during our study period, and highlight how the foraging strategies of Peruvian boobies have adapted to the variable environmental conditions found in the HCS.

Machine learning predicts spinal cord stimulation surgery outcomes and reveals novel neural markers for chronic pain

Epitope-directed selection of GPCR nanobody ligands with evolvable function

Antibodies have the potential to target G protein–coupled receptors (GPCRs) with high receptor, cellular, and tissue selectivity; however, few antibody ligands for GPCRs exist. Here, we describe a generalizable selection method to enrich for GPCR ligands from a synthetic camelid antibody fragment (nanobody) library. Our strategy yielded multiple nanobody ligands for the angiotensin II type I receptor (AT1R), a prototypical GPCR and important drug target. We found that nanobodies readily act as allosteric modulators, encoding selectivity for both the receptor and chemical features of GPCR ligands. We then used structure-guided design to convert two nanobodies from allosteric ligands to competitive AT1R inhibitors through simple mutations. This work demonstrates that nanobodies can encode multiple pharmacological behaviors and have great potential as evolvable scaffolds for the development of next-generation GPCR therapeutics.

Intrinsic strain of defect sites steering chlorination reaction for water purification

Parents’ work–family conflict and parent‒child relationship: The mediating role of parenting burnout and the moderating role of self-compassion

In today’s fast-paced society, balancing work and family has become a key challenge affecting individual well-being, particularly for working parents. The conflict between these roles not only impacts personal mental health but also strains family dynamics, especially the parent‒child relationship. The main objective of this study is to explore the impact of work‒family conflict on the parent‒child relationship, with a focus on the mediating role of parenting burnout and the moderating role of self-compassion. The findings of a sample of 818 working parents revealed that work–family conflict negatively affects parent–child relationships and increases parenting burnout, thus further damaging these relationships. However, self-compassion significantly mitigates these negative effects, reducing the risk of parenting burnout. This study highlights the importance of fostering self-compassion as a potential intervention to protect the parent‒child relationship in the context of the work‒family relationship.

Exploring the relationship between the tourist behavior and the spatial characteristics for rural tourism

Abstract With global urbanization, rural tourism has become a thriving trend for urban-rural sustainable development in addition to the urban landscape. However, research on rural landscape planning is still lacking. The topography of the rural areas is complex, with mountains and buildings arranged in accordance with the terrain, and pedestrian data is difficult to collect. Therefore, this study adopts mixed methods to obtain high-precision data. This study aims to investigate the relationships between tourist behavior and spatial characteristics. The results indicated that (1) Different rural spaces formed an uneven distribution of tourists’ spatial-temporal behavior characteristics, which could be attributed to three potential factors: easy space accessibility, good visual permeability, and herd mentality; (2) Visual space had a strong influence on guiding tourists compared to the passable space; (3) Historical trees, heritage buildings and cultural legacy are the positive influencing cultural factors for tourist attraction in spaces. Furthermore, these findings provided rationales to mobilize the utilization of the rural landscape resources and enhance the sustainable urban-rural development. These findings and methods improve our understanding of the temporal–spatial tourist behavior in rural tourism, which is of great significance for rural tourism planning and cultural legacy protection.

Large increases in public R&D investment are needed to avoid declines of US agricultural productivity

Increasing agricultural productivity is a gradual process with significant time lags between research and development (R&D) investment and the resulting gains. We estimate the response of US agricultural Total Factor Productivity to both R&D investment and weather and quantify the public R&D spending required to offset the emerging impacts of climate change. We find that offsetting the climate-induced productivity slowdown by 2050 will require R&D spending over 2021 to 2050 to grow at 5.2 to 7.8% per year under a fixed spending growth scenario or by an additional $2.2 to $3.8B per year under a fixed supplement spending scenario (in addition to the current spending of ~$5B per year). This amounts to an additional $208 to $434B or $65 to $113B over the period, respectively, and would be comparable in ambition to the public R&D spending growth that followed the two World Wars.

Species differences in opsonization and phagocyte recognition of preclinical poly-2-alkyl-2-oxazoline-coated nanoparticles

Revisiting the determinants of CO2 emissions: The role of higher education under the extended STIRPAT model

This study directly aligns with Sustainable Development Goals (SDGs), i.e., SDG-13 and SDG-4. Carbon emissions (CO2e) are primarily addressed under SDG-13: Climate Action, which aims to combat climate change and its impacts. CO2e reduction efforts contribute to achieving this goal by mitigating greenhouse gas emissions. SDG 4: Quality Education aims to ensure inclusive and equitable quality education for all. It emphasizes explicitly lifelong learning opportunities and targets higher education (HE) access to improve skills for sustainable development. Therefore, the current study aims to examine the determinants of CO2e in China and the role of HE under the extended STIRPAT model. This study utilizes the Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) methods using the time series data from 1985 to 2023. The finding shows that total population, GDP, and industry positively affect CO2e, while technological innovation and higher education negatively affect CO2e in China.

Analyzing cost impacts across the entire process of prefabricated building components from design to application

The impact of political assassinations on turnout: Evidence from Colombia

Although a growing literature has investigated the effects of various types of civil war violence on political behavior, no study has examined the impact of assassinations targeting politicians. This is a critical omission, as violence against local politicians is prevalent across civil war contexts and may be the most consequential form of violence for political participation by affecting both candidate supply and voter demand. Using an original dataset of nearly 2,000 killings of Colombian local politicians between 1980 and 2023, we estimate the impact of this violence on voter turnout. Taking municipalities where assassination attempts failed as a comparison group, we find that political assassinations significantly decrease voter turnout in both the short and medium terms, with effects persisting in various elections even after the signing of a peace agreement. These findings contrast with many studies suggesting that other forms of civil war violence enhance political participation during the postconflict period or after a truce or peace agreement. Our results suggest that different forms of violence can have distinct effects on political behavior, underscoring the need to theorize how the targeting, nature, and context of violence condition its effects. This echoes calls for more nuanced studies on the behavioral impacts of violence. Our findings also have implications for understanding democracy amid rising violence against political leaders in countries affected by organized crime, such as Mexico and Brazil; polarized contexts, such as the United States; and weakly institutionalized democracies, such as South Africa, Indonesia, and the Philippines.

GraphBAN: An inductive graph-based approach for enhanced prediction of compound-protein interactions

Individual participant data network meta-analysis of psychosocial interventions for survivors of intimate partner violence: Study protocol

Many systematic reviews and meta-analyses have been conducted in the field of Intimate Partner Violence (IPV) and the evidence shows small to moderate effect sizes in improving mental health outcomes. However, there is considerable heterogeneity due to variation in participants, interventions and contexts. It is therefore important to establish which participant and intervention characteristics affect the different psychosocial outcomes in different contexts. Individual Participant Network Meta-analysis (IPDNMA) is a gold-standard method to estimate moderating effects, compare the effectiveness of different interventions and thus answer the question of which intervention is best-suited for whom. We will conduct an IPDNMA of randomised controlled trials (RCTs) of psychosocial interventions for IPV survivors aimed at improving mental health, psychosocial outcomes such as self-efficacy and quality of life, reducing IPV and increasing safety-behaviours and dropout from the intervention (as an indication of intervention acceptability) compared to any type of control (PROSPERO registration number: CRD42023488502). We aim to establish collaborations with the authors of eligible RCTs, to obtain and harmonise the Individual Participant Data of the trials. We will conduct one-stage IPDNMA under a Bayesian framework using the multinma package in R, after testing which characteristics of the participants and interventions are effect modifiers. We anticipate that not all study authors will provide access to IPD, which is a limitation of IPDNMA. We aim to address this by combining studies with aggregate data and studies with IPD using Multi-Level Network Meta-Regression (ML-NMR) implemented in the multinma R package. This approach is novel in the field and makes full use of available evidence to inform clinical and policy-related decision making.

Research on the comprehensive dessert evaluation method in shale oil reservoirs based on fractal characteristics of conventional logging curves

Abstract The traditional logging evaluation of comprehensive sweet spots in shale oil reservoirs has problems such as complex explanatory parameters, incompatible quantitative characterization scales, and low-cost efficiency. A method based on the fractal characteristics of conventional logging curves is proposed to evaluate the comprehensive sweet spots of fractured horizontal wells in shale oil reservoirs. Firstly, the existing evaluation parameters and methods were reviewed, pointing out the limitations of traditional logging evaluation methods. Furthermore, we analyzed 63 fractured sections from three horizontal fractured wells in the Yingxiongling shale oil reservoir of the Qinghai Oilfield, using tracer monitoring data. By applying wavelet transform to reduce noise in high-frequency signals from conventional logging curves, we then used multifractal spectrum analysis and R/S analysis to extract the multifractal spectrum width (∆α) and fractal dimension (D) from four conventional logging attributes: natural gamma logging (GR), acoustic time difference logging (AC), density logging (DEN), and neutron logging (CNL). A multi-attribute comprehensive fractal evaluation index was developed by using the post-fracturing tracer monitoring profile as a constraint and applying the grey relational analysis method. This approach enabled a quantitative classification and evaluation of the key sweet spots in shale oil reservoirs after fracturing. The results show that the comprehensive fractal evaluation index of the high-yield well section after Class I layering is 0.75<∆ α‘<1, 0 < D‘<0.25; 0.35<∆ α‘<0.75, 0.25 < D‘<0.8 in the middle well section of Class II layer; Class III low production well Sect. 0<∆ α‘<0.35, 0.8<∆ α‘<1. Finally, a prediction model for physical property parameters characterized by fractals was introduced using machine learning algorithms, which is 31.9% more accurate than the conventional interpretation physical property parameter prediction model for the comprehensive sweet spot of fracturing. This evaluation method is a concise approach to comprehensively evaluate the sweet spot area based on the extraction of multifractal spectral characteristic parameters from conventional logging data. It is of great significance for characterizing the volume fracturing effect of shale oil and providing technical support for the effective development of shale on a large scale.