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This meta-analysis investigated the factors underlying effective messages to counter attitudes and beliefs based on misinformation. Because misinformation can lead to poor decisions about consequential matters and is persistent and difficult to correct, debunking it is an important scientific and public-policy goal. This meta-analysis (k = 52, N = 6,878) revealed large effects for presenting misinformation (ds = 2.41–3.08), debunking (ds = 1.14–1.33), and the persistence of misinformation in the face of debunking (ds = 0.75–1.06). Persistence was stronger and the debunking effect was weaker when audiences generated reasons in support of the initial misinformation. A detailed debunking message correlated positively with the debunking effect. Surprisingly, however, a detailed debunking message also correlated positively with the misinformation-persistence effect.

Carbon Capture and Storage (CCS) involves trapping carbon dioxide (CO2) from power generation and heavy industrial processes and directing it into long-term geological storage (e.g., in depleted oil fields or saline aquifers). In doing so, CCS could facilitate global carbon abatement efforts. Yet, it remains controversial with high-profile public opposition to particular CCS developments. For instrumental, normative and substantive reasons, it is increasingly recognised that public acceptance of CCS as a vital precondition for its commercial-scale rollout. While much is known about factors influencing public support for CCS, relatively few cross-national studies have so far been undertaken. Here, we present findings from a large-scale international experimental study of public perceptions of CCS, to examine how individual, geographical and informational factors influence support for CCS. In particular, we compare the lens through which CCS is seen – as a ‘techno-fix’ climate change solution, as reusing a waste product (through Carbon Dioxide Utilisation [CDU]), or as part of a systemic approach to climate change mitigation. Pairing CCS with CDU led to higher support for CCS, although information frames interacted with national and individual-level factors. Depending on which CCS lens is chosen, different groups will be more or less likely to support CCS implementation. As with other issues, targeting CCS information to audience values is likely to be more effective than untargeted communication. Our findings also show mentioning (modest) costs of deploying CCS can lead to lower support. Discussing CCS costs should be done in the context of costs of broader energy system transformation and of not mitigating climate change so that the public can deliberate over the relative risks and benefits of CCS and alternatives in the context of broader sustainability pathways.

Intestinal metabolism can limit oral bioavailability of drugs and increase the risk of drug interactions. It is therefore important to be able to predict and quantify it in drug discovery and early development. In recent years, a plethora of models—in vivo, in situ and in vitro — have been discussed in the literature. The primary objective of this review is to summarize the current knowledge in the quantitative prediction of gut-wall metabolism. As well as discussing the successes of current models for intestinal metabolism, the challenges in the establishment of good preclinical models are highlighted, including species differences in the isoforms; regional abundances and activities of drug metabolizing enzymes; the interplay of enzyme-transporter proteins; and lack of knowledge on enzyme abundances and availability of empirical scaling factors. Due to its broad specificity and high abundance in the intestine, CYP3A is the enzyme that is frequently implicated in human gut metabolism and is therefore the major focus of this review. A strategy to assess the impact of gut wall metabolism on oral bioavailability during drug discovery and early development phases is presented. Current gaps in the mechanistic understanding and the prediction of gut metabolism are highlighted, with suggestions on how they can be overcome in the future.

Accurately representing mesoscale convective systems (MCSs) is crucial to simulating the energy and water cycles in global climate models. Using a novel MCS identification and tracking algorithm applied to observations and model simulations, we evaluate how well the Energy Exascale Earth System Model (E3SM) simulates MCSs over the central US. Simulations performed by E3SM at 25 km grid spacing with and without superparameterization (SP) are compared and evaluated against observations using multiple metrics highlighting important MCS characteristics. Compared to E3SM, the superparameterized model (SP‐E3SM) better simulates MCS number and MCS precipitation amount, diurnal cycle, propagation, and the probability distribution of precipitation rate in both spring and summer. The improvement from SP is partly contributed by improvement in simulating the large‐scale environments, featuring enhanced atmospheric low‐level moisture and larger moisture transport to the central US relative to E3SM. However, SP‐E3SM still underestimates MCS precipitation amount, particularly in summer. This underestimation is closely related to the negative bias in MCS precipitation intensity, although the drier environments simulated during summer also contributes to underestimation of MCS frequency. Without SP, the larger bias in MCS precipitation amount is closely related to the negative bias in MCS frequency, while the substantial dry bias in the large‐scale environments also contributes to underestimation of MCS intensity. Our results suggest that SP improves MCS simulation by improving modeling of the large‐scale environments and convection initiation, which are both major limiting factors in E3SM even at 25 km grid spacing where deep convection is represented by a cumulus parameterization. Plain Language Summary Large thunderstorms called mesoscale convective systems (MCSs) are an important source of flood‐producing rainfalls. In this paper, we examine how well the Energy Exascale Earth System Model (E3SM) simulate MCSs over the central US in spring and summer by comparing against observations. We run two versions of E3SM: one is the standard E3SM that uses a traditional parameterization to simulate deep convection, the other is E3SM with a superparameterization (SP‐E3SM) that uses a cloud resolving model within each E3SM grid column to explicitly simulate deep convection. By using a novel detection and tracking algorithm to characterize MCS features, we find that SP‐E3SM can better simulate the number, rainfall amount and intensity, and the diurnal cycle of MCSs compared to E3SM. SP improves MCS simulations by improving the representation of the large‐scale circulations and convection initiation. Despite the improvement, SP‐E3SM still underestimates the MCS rainfall amount, which is largely related to the underestimation of MCS rainfall intensity. In contrast, the larger underestimation of rainfall amount in E3SM is attributed in large parts to the lower MCS frequency. This study highlights the importance of large‐scale moisture transport and convection initiation in simulating MCSs. Key Points Mesoscale convective systems (MCSs) in E3SM at 25 km with and without superparameterization (SP) are evaluated the central US Including SP significantly improves MCS simulations in both spring and summer, although large dry biases are still apparent in summer Improvements from SP are contributed by improved simulations of the large‐scale environments and MCS number and precipitation frequency

Many components of the circadian molecular clock are conserved from flies to mammals; however, the role of mammalian Timeless remains ambiguous. Here, we report a mutation in the human TIMELESS (hTIM) gene that causes familial advanced sleep phase (FASP). Tim CRISPR mutant mice exhibit FASP with altered photic entrainment but normal circadian period. We demonstrate that the mutation prevents TIM accumulation in the nucleus and has altered affinity for CRY2, leading to destabilization of PER/CRY complex and a shortened period in nonmature mouse embryonic fibroblasts (MEFs). We conclude that TIM, when excluded from the nucleus, can destabilize the negative regulators of the circadian clock, alter light entrainment, and cause FASP.

Collagen gels are widely used in experiments on cell mechanics because they mimic the extracellular matrix in physiological conditions. Collagen gels are often characterized by their bulk rheology; however, variations in the collagen fiber microstructure and cell adhesion forces cause the mechanical properties to be inhomogeneous at the cellular scale. We study the mechanics of type I collagen on the scale of tens to hundreds of microns by using holographic optical tweezers to apply pN forces to microparticles embedded in the collagen fiber network. We find that in response to optical forces, particle displacements are inhomogeneous, anisotropic, and asymmetric. Gels prepared at 21 °C and 37 °C show qualitative difference in their micromechanical characteristics. We also demonstrate that contracting cells remodel the micromechanics of their surrounding extracellular matrix in a strainand distance-dependent manner. To further understand the micromechanics of cellularized extracellular matrix, we have constructed a computational model which reproduces the main experiment findings.

Climate change sensitivities of subtropical cloud‐topped marine boundary layers are analyzed using large‐eddy simulation (LES) of three CGILS cases of well‐mixed stratocumulus, cumulus under stratocumulus, and shallow cumulus cloud regimes, respectively. For each case, a steadily forced control simulation on a small horizontally doubly periodic domain is run 10–20 days into quasi‐steady state. The LES is rerun to steady state with forcings perturbed by changes in temperature, free‐tropospheric relative humidity (RH), CO2 concentration, subsidence, inversion stability, and wind speed; cloud responses to combined forcings superpose approximately linearly. For all three cloud regimes and 2× CO2 forcing perturbations estimated from the CMIP3 multimodel mean, the LES predicts positive shortwave cloud feedback, like most CMIP3 global climate models. At both stratocumulus locations, the cloud remains overcast but thins in the warmer, moister, CO2‐enhanced climate, due to the combined effects of an increased lower‐tropospheric vertical humidity gradient and an enhanced free‐tropospheric greenhouse effect that reduces the radiative driving of turbulence. Reduced subsidence due to weakening of tropical overturning circulations partly counteracts these two factors by raising the inversion and allowing the cloud layer to deepen. These compensating mechanisms may explain the large scatter in low cloud feedbacks predicted by climate models. CMIP3‐predicted changes in wind speed, inversion stability, and free‐tropospheric RH have lesser impacts on the cloud thickness. In the shallow cumulus regime, precipitation regulates the simulated boundary‐layer depth and vertical structure. Cloud‐droplet (aerosol) concentration limits the boundary‐layer depth and affects the simulated cloud feedbacks. Key Points LES low‐cloud feedbacks positive due to enhanced vertical humidity gradients Less subsidence in warmer climate counteracts positive low cloud feedbacks Precipitation and cloud droplet number affect cumulus depth, climate feedbacks

The emergence of multidrug-resistant (MDR) bacterial pathogens has heightened the urgency for novel antibacterial agents. The bacterial cell wall usually comprises peptidoglycan, which presents a prime target for antibacterial drug development due to its indispensable role in maintaining cellular integrity. Conventional antibiotics such as β-lactams and glycopeptides hinder peptidoglycan synthesis through competitive binding of penicillin-binding proteins (PBPs) and sequestration of lipid-linked precursor molecules. Nevertheless, prevalent resistance mechanisms including target modification, β-lactamase hydrolysis, and multi-drug efflux pumps have limited their clinical utility. This comprehensive analysis explicates the molecular machinery underlying bacterial cell wall assembly, evaluates both explored and unexplored enzymatic nodes within this pathway, and highlights the transformative impact of high-resolution structural elucidation in accelerating structure-guided drug discovery. Novel targets such as GlmS, GlmM, GlmU, Mur ligases, D,L-transpeptidases are assessed for their inclusiveness for the discovery of next-generation antibiotics. Additionally, cell wall inhibitors are also examined for their mechanisms of action and evolutionary constraints on MDR development. High-resolution crystallographic data provide valuable insights into molecular blueprints for structure-guided optimization of pharmacophores, enhancing binding affinity and circumventing resistance determinants. This review proposes a roadmap for future innovation, advocating for the convergence of computational biology platforms, machine learning-driven compound screening, and nanoscale delivery systems to improve therapeutic efficacy and pharmacokinetics. The synergy of structural insights and cutting-edge technologies offers a multidisciplinary framework for revitalizing the antibacterial arsenal and combating MDR infections efficiently.

Familial Advanced Sleep Phase (FASP) is a heritable human sleep phenotype characterized by very early sleep and wake times. We identified a missense mutation in the human Cryptochrome 2 ( CRY2 ) gene that co-segregates with FASP in one family. The mutation leads to replacement of an alanine residue at position 260 with a threonine (A260T). In mice, the CRY2 mutation causes a shortened circadian period and reduced phase-shift to early-night light pulse associated with phase-advanced behavioral rhythms in the light-dark cycle. The A260T mutation is located in the phosphate loop of the flavin adenine dinucleotide (FAD) binding domain of CRY2. The mutation alters the conformation of CRY2, increasing its accessibility and affinity for FBXL3 (an E3 ubiquitin ligase), thus promoting its degradation. These results demonstrate that CRY2 stability controlled by FBXL3 plays a key role in the regulation of human sleep wake behavior. Sleep is an essential process in animals. In humans, the disturbance of normal sleep-wake cycles through shift-work or long-term sleep disorders increases the risk of developing conditions including mental illness, cancer and metabolic syndromes. Understanding how sleep-wake behavior is controlled within cells may help researchers to develop effective therapies to reduce the ill effects of disturbed sleep-wakLouise cycles on health. To understand how our sleep-wake cycles are regulated in cells, researchers have been looking for genetic mutations that affect human sleep schedules. For example, some people have a ‘morning lark’ schedule that makes them prone to go to sleep early and rise early the next day. Others are prone to be ‘night owls’, staying up later at night and waking up later in the morning. By studying the mutations that underlie these behaviors, researchers hope to understand precisely how these genes regulate sleep schedules. Now, Hirano et al. have identified a particular mutation in a gene called Cryptochrome 2 ( CRY2 ) that causes people to have shorter sleep-wake cycles so that they wake up very early in the morning and struggle to stay awake in the evening. For the experiments, mice were genetically engineered to carry the mutant human CRY2 gene, which shortened the sleep-wake cycles of the mice and their responses to light so that they both woke up earlier and went to sleep earlier. Further experiments examined what effect the mutation has on the protein that is produced by CRY2. The mutation changes the shape of the protein, which allows an enzyme called FBXL3 to bind to the mutant protein more easily and rapidly break it down. The length of sleep cycles may be determined by how long it takes FBXL3 to break down the protein produced by CRY2 . The findings of Hirano et al. may help researchers to develop treatments for people with sleep problems.

Sleep deprivation can impair human health and performance. Habitual total sleep time and homeostatic sleep response to sleep deprivation are quantitative traits in humans. Genetic loci for these traits have been identified in model organisms, but none of these potential animal models have a corresponding human genotype and phenotype. We have identified a mutation in a transcriptional repressor (hDEC2-P385R) that is associated with a human short sleep phenotype. Activity profiles and sleep recordings of transgenic mice carrying this mutation showed increased vigilance time and less sleep time than control mice in a zeitgeber time- and sleep deprivation-dependent manner. These mice represent a model of human sleep homeostasis that provides an opportunity to probe the effect of sleep on human physical and mental health.