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Belief in belief: Even atheists in secular countries show intuitive preferences favoring religious belief
We find evidence of belief in belief —intuitive preferences for religious belief over atheism, even among atheist participants—across eight comparatively secular countries. Religion is a cross-cultural human universal, yet explicit markers of religiosity have rapidly waned in large parts of the world in recent decades. We explored whether intuitive religious influence lingers, even among nonbelievers in largely secular societies. We adapted a classic experimental philosophy task to test for this intuitive belief in belief among people in eight comparatively nonreligious countries: Canada, China, Czechia, Japan, the Netherlands, Sweden, the United Kingdom, and Vietnam (total N = 3,804). Our analyses revealed strong evidence that 1) people intuitively favor religious belief over atheism and that 2) this pattern was not moderated by participants’ own self-reported atheism. Indeed, 3) even atheists in relatively secular societies intuitively prefer belief to atheism. These inferences were robust across different analytic strategies and across other measures of individual differences in religiosity and religious instruction. Although explicit religious belief has rapidly declined in these countries, it is possible that belief in belief may still persist. These results speak to the complex psychological and cultural dynamics of secularization.
Injectable ECM-mimetic dynamic hydrogels abolish ferroptosis-induced post-discectomy herniation through delivering nucleus pulposus progenitor cell-derived exosomes
Maximum likelihood estimators are ineffective for acoustic detection of rare bat species
Acoustic monitoring is an important tool for determining presence or probable absence of threatened and endangered bats in the United States (US). Federal guidance requires the use of automated identification programs that classify audio files and calculate a Maximum Likelihood Estimator (MLE) for each bat species during each night of a survey. Acoustic presence or absence of species is based on a significant or non-significant MLE, which can have profound regulatory effects, positive or negative. Despite relying on this metric to determine presence of rare species for the past ten years, little is known about the number of files required by available programs to trigger significant MLE or the effect of species ratio on this calculation. We used 1,120 audio files containing echolocation calls from nine northeastern US bat species to simulate survey nights containing variable absolute counts and ratios of species’ audio files. We developed models to estimate the number of audio files that Kaleidoscope Pro (KPro) and SonoBat programs required to establish acoustic presence for each species, and we then applied our best model to a long-term acoustic dataset collected at the Fort Drum Military Installation in New York. Each program required a similar number of files to detect presence for some species, such as Myotis septentrionalis and M. sodalis (8 to 10 files), but differed in file requirements for other species, such as Lasiurus cinereus (KPro = 4; SonoBat = 7) and Perimyotis subflavus (KPro = 10; SonoBat = 6). Both programs performed poorly with determining presence for any species at low species ratio (<25%). Applying our model to the Fort Drum dataset revealed that the total number of audio files recorded within a night had a great effect on whether a rare species was correctly determined to be present. We conclude that MLE should be used with caution during surveys of rare species and could produce misleading results in certain conditions.
Prognostic value of sarcopenia in patients with unresectable colorectal liver metastases after drug-eluting beads transcatheter arterial chemoembolization: a single center retrospective study
Explaining human motor coordination via the synergy expansion hypothesis
The search for an answer to Bernstein’s degrees of freedom problem has propelled a large portion of research studies in human motor control over the past six decades. Different theories have been developed to explain how humans might use their incredibly complex neuro-musculo-skeletal system with astonishing ease. Among these theories, motor synergies appeared as one possible explanation. In this work, the authors investigate the nature and role of synergies and propose a theoretical framework, namely the “expansion hypothesis,” to answer Bernstein’s problem. The expansion hypothesis is articulated in three propositions: mechanical, developmental, and behavioral. Each proposition addresses a different question on the nature of synergies: i) How many synergies can humans have? ii) How do we learn and develop synergies? iii) How do we use synergies? An example numerical simulation is presented and analyzed to clarify the hypothesis propositions. The expansion hypothesis is contextualized with respect to the existing literature on motor synergies both in healthy and impaired individuals, as well as other prominent theories in human motor control and development. The expansion hypothesis provides a framework to better comprehend and explain the nature, use, and evolution of human motor skills.
Author Correction: On-surface synthesis of triangulene trimers via dehydration reaction
Correction: Reconstructing prehistoric lifeways using multi-Isotope analyses of human enamel, dentine, and bone from Legaire Sur, Spain
Cross-sectional analysis of eating disorder risk and risk correlates in candidates for bariatric surgery from the BariPredict cohort
Abstract Bariatric surgery is an effective intervention for managing obesity. Persons with obesity are a high-risk population for eating disorders (ED), and these can negatively impact perioperative and long-term outcomes of surgery. We aim to understand prevalence and correlates of ED in preintervention patients, identifying those needing psychological support. Baseline cross-sectional analysis of 275 patients of the BariPredict cohort (NCT06480058), a study to assess predictors of long-term surgery outcomes. Psychological assessments were conducted using SCOFF, KUAS, and BDI tools. Data were analyzed for prevalence of high ED risk and for associations of clinical, biological and demographic factors. Mean age was 38.5 years, mean BMI was 42.3 kg/m², with 62.5% being female. 65.8% of patients had a SCOFF score ≥ 2 indicating high ED risk. Class II obesity (p < 0.05), younger age (p < 0.01), and higher depression (p < 0.01) were associated with ED risk in a logistic regression adjusted for age, obesity class, diabetes, HbA1c, depression and anxiety scores. We report high preintervention prevalence of ED, with a risk profile corresponding to BMI of 35-39.9 Kg/m2 in younger adults with concurrent depression. This patient profile should be prioritized for psychological assessment and support to potentially improve outcomes of bariatric surgery.
The emergence of eukaryotes as an evolutionary algorithmic phase transition
The origin of eukaryotes represents one of the most significant events in evolution since it allowed the posterior emergence of multicellular organisms. Yet, it remains unclear how existing regulatory mechanisms of gene activity were transformed to allow this increase in complexity. Here, we address this question by analyzing the length distribution of proteins and their corresponding genes for 6,519 species across the tree of life. We find a scale-invariant relationship between gene mean length and variance maintained across the entire evolutionary history. Using a simple model, we show that this scale-invariant relationship naturally originates through a simple multiplicative process of gene growth. During the first phase of this process, corresponding to prokaryotes, protein length follows gene growth. At the onset of the eukaryotic cell, however, mean protein length stabilizes around 500 amino acids. While genes continued growing at the same rate as before, this growth primarily involved noncoding sequences that complemented proteins in regulating gene activity. Our analysis indicates that this shift at the origin of the eukaryotic cell was due to an algorithmic phase transition equivalent to that of certain search algorithms triggered by the constraints in finding increasingly larger proteins.
Global data-driven prediction of fire activity
Abstract Recent advancements in machine learning (ML) have expanded the potential use across scientific applications, including weather and hazard forecasting. The ability of these methods to extract information from diverse and novel data types enables the transition from forecasting fire weather, to predicting actual fire activity. In this study we demonstrate that this shift is feasible also within an operational context. Traditional methods of fire forecasts tend to over predict high fire danger, particularly in fuel limited biomes, often resulting in false alarms. By using data on fuel characteristics, ignitions and observed fire activity, data-driven predictions reduce the false-alarm rate of high-danger forecasts, enhancing their accuracy. This is made possible by high quality global datasets of fuel evolution and fire detection. We find that the quality of input data is more important when improving forecasts than the complexity of the ML architecture. While the focus on ML advancements is often justified, our findings highlight the importance of investing in high-quality data and, where necessary create it through physical models. Neglecting this aspect would undermine the potential gains from ML-based approaches, emphasizing that data quality is essential to achieve meaningful progress in fire activity forecasting.
Inkjet-printed transparent electrodes: Design, characterization, and initial in vivo evaluation for brain stimulation
Electrical stimulation is a powerful tool for investigating and modulating brain activity, as well as for treating neurological disorders. However, understanding the precise effects of electrical stimulation on neural activity has been hindered by limitations in recording neuronal responses near the stimulating electrode, such as stimulation artifacts in electrophysiology or obstruction of the field of view in imaging. In this study, we introduce a novel stimulation device fabricated from conductive polymers that is transparent and therefore compatible with optical imaging techniques. The device is manufactured using a combination of microfabrication and inkjet printing techniques and is flexible, allowing better adherence to the brain’s natural curvature. We characterized the electrical and optical properties of the electrodes, focusing on the trade-off between the maximum current that can be delivered and optical transmittance. We found that a 1 mm diameter, 350 nm thick PEDOT:PSS electrode could be used to apply a maximum current of 130 μA while maintaining 84% transmittance (approximately 50% under 2-photon imaging conditions). We then evaluated the electrode performance in the brain of an anesthetized mouse by measuring the electric field with a nearby recording electrode and found values up to 30 V/m. Finally, we combined experimental data with a finite-element model of the in vivo experimental setup to estimate the distribution of the electric field underneath the electrode in the mouse brain. Our findings indicate that the device can generate an electric field as high as 300 V/m directly beneath the electrode, demonstrating its potential for studying and manipulating neural activity using a range of electrical stimulation techniques relevant to human applications. Overall, this work presents a promising approach for developing versatile new tools to apply and study electrical brain stimulation.
Author Correction: Dual-branch image projection network for geographic atrophy segmentation in retinal OCT images
Manipulation of interoceptive signaling biases decision making in rhesus macaques
Several influential theories have proposed that interoceptive signals, sent from the body to the brain, contribute to neural processes that coordinate complex behaviors. We altered the physiological state of the body using compounds that have minimal effect on the brain and evaluated their effect on decision making in rhesus monkeys. We used glycopyrrolate, a nonspecific muscarinic (parasympathetic) antagonist, and isoproterenol, a beta-1/2 (sympathetic) agonist, to create a sympathetic-dominated state in the periphery, that was indexed by increased heart rate. Rhesus monkeys were trained on two variants of an approach-avoidance conflict task. The tasks offered a choice between enduring mildly aversive stimuli in exchange for a steady flow of rewards, or canceling the aversive stimuli, forgoing the rewards. The latency to interrupt the aversive stimuli was used as a measure of monkeys’ tolerance for contact with a hot but not painful stimulus or airflow directed at their muzzle. Both drugs reduced tolerance for the aversive stimuli. To determine whether the drug-induced autonomic state reduced the subjective value of the reward, we tested the effects of glycopyrrolate on a food preference task. Food preference was unaltered, suggesting that the sympathetic dominated state in the periphery selectively reduces tolerance for aversive stimuli without altering reward-seeking behaviors. As the drugs used are expected to have little or no direct effect on the brain, the observed biases in decision making are likely induced by interoceptive afferents that signal to the brain the physiological state of the body.
Lysine-arginine imbalance overcomes therapeutic tolerance governed by the transcription factor E3-lysosome axis in glioblastoma
Association of overweight/obesity and digestive system cancers: A meta-analysis and trial sequential analysis of prospective cohort studies
Background Previous researches have reported correlations between overweight/obesity and common digestive system cancers (DSCs), including gastric, liver, esophageal, colorectal, and pancreatic cancers. However, the inconsistency in defining overweight/obesity and the risk of recall bias from case-control and retrospective cohort studies may influence existing results. Therefore, we aimed to validate the relationship between overweight/obesity and common DSCs by combining prospective cohort studies based on the World Health Organization (WHO) criteria for defining overweight/obesity. Methods A comprehensive literature search was conducted across PubMed, Embase, Web of Science, and Cochrane databases, covering all publications up to February 7, 2024. The inclusion criteria focused on prospective cohort studies that examined the link between overweight/obesity and risks of DSCs. R software 4.1.3 and STATA 12 were utilised to calculate the relative risk (RR), with 95% confidence interval (CI) and prediction interval (PI). TSA v0.9.5.10 Beta software was used for trial sequential analysis (TSA). Results The meta-analysis encompassed 39 articles. The overall analysis showed that compared with normal weight, overweight/obesity increased the risks of liver cancer (overweight: RR [95% CI] = 1.237 [1.112-1.377]; 95% PI: 0.888-1.725; obesity: RR [95% CI] = 1.642 [1.466-1.839]; 95% PI: 1.143-2.358) and colorectal cancer (overweight: RR [95% CI] = 1.124 [1.056-1.197]; 95% PI: 0.931-1.357; obesity: RR [95% CI] = 1.366 [1.242-1.503]; 95% PI: 0.959-1.945) in the total population. Subgroup analysis revealed that overweight (RR [95% CI] = 1.237 [1.165-1.314]; 95% PI: 1.154-1.327) and obesity (RR [95% CI] = 1.306 [1.152-1.480]; 95% PI: 1.108-1.539) were associated with an increased risk of pancreatic cancer only in women, and overweight also increased the gastric cancer risk of women (RR [95% CI] = 1.041 [1.013-1.070], 95% PI: 0.806-1.230). No significant association of overweight/obesity and esophageal cancer was observed in both male and female. Conclusion Our study suggested that overweight/obesity elevated the risks of liver and colorectal cancer in both men and women. No significant association was found between overweight/obesity and the risk of developing esophageal cancer. Clinicians are advised to consider weight control as an effective measure for preventing pancreatic, liver, and colorectal cancers.
Polarisation reconfigurable anisotropic dielectric resonator antenna
Abstract A novel polarization reconfigurable anisotropic dielectric resonator antenna (ADRA) is presented utilizing a new modulation scheme to exploit the degree of freedom in the polarization domain. The ADRA comprises periodic assembly dielectric resonators with two different dielectrics constant, equal in size, a vertically positioned metal strip, one varactor diode, and six PIN diode switches. The modulation scheme utilizes the tilt angle and axial ratio (AR) of a wireless signal to convey additional information, enabling the realization of different working modes ranging from circular polarization (CP) to nearly linear polarization (LP). The proposed modulation scheme yields significantly better bit error rate (BER) performance and higher spectral efficiency in bits/s/Hz/antenna. Additionally, the paper presents an antenna design capable of generating an arbitrary polarization state, highlighting the system benefits of polarization modulation. Post-fabrication, the proposed approach is validated by comparing simulated and measured results. The proposed antenna provides a total efficiency higher than 93% in the desired frequency bands and consistent gain at approximately 7.64 dBi and 7.09 dBi at 3.8 GHz, with the impedance matching bandwidth ranging from 3.53 to 3.90 GHz and 3.56 to 3.91 GHz fully overlapping across all polarization states for the simulated and measured results, respectively. Experimental results affirm the robust performance of the proposed ADRA.
Modulation of host gene expression by the zinc finger antiviral protein
The zinc finger antiviral protein (ZAP) depletes nonself RNAs through recognition of their elevated CpG dinucleotide content. CpG dinucleotides are sparse in most endogenous mammalian mRNAs, but a subset might potentially be modulated by ZAP. While CpG frequency alone is insufficient to predict ZAP-regulation, we developed an algorithm using experimentally determined compositional features to predict which endogenous mRNAs may be ZAP-regulated. Using ZAP-knockout mice, we demonstrate that levels of many host mRNAs that are algorithmically predicted ZAP targets are indeed increased when ZAP is absent. ZAP is interferon-inducible, and we also identify genes that are downregulated by ZAP during an innate immune response. Many ZAP-regulated gene products are extracellular matrix or of nucleosome components, whose ZAP-mediated control is conserved in human cells. Overall, we provide a tool for the prediction of ZAP target genes and reveal host mRNAs that are ZAP-regulated.
Design and implementation of aerobic and ambient CO2-reduction as an entry-point for enhanced carbon fixation
Abstract The direct reduction of CO2 into one-carbon molecules is key to highly efficient biological CO2-fixation. However, this strategy is currently restricted to anaerobic organisms and low redox potentials. In this study, we introduce the CORE cycle, a synthetic metabolic pathway that converts CO2 to formate at aerobic conditions and ambient CO2 levels, using only NADPH as a reductant. Combining theoretical pathway design and analysis, enzyme bioprospecting and high-throughput screening, modular assembly and adaptive laboratory evolution, we realize the CORE cycle in vivo and demonstrate that the cycle supports growth of E. coli by supplementing C1-metabolism and serine biosynthesis from CO2. We further analyze the theoretical potential of the CORE cycle as a new entry-point for carbon in photorespiration and autotrophy. Overall, our work expands the solution space for biological carbon reduction, offering a promising approach to enhance CO2 fixation processes such as photosynthesis, and opening avenues for synthetic autotrophy.