Browse Articles

AI-derived therapeutic development of a serotonin receptor–targeting drug for the treatment of opioid use disorder

The opioid epidemic has led to a devastating loss of life nationwide. Of those dependent on opioids, many individuals desire to quit or reduce use, but their efforts are often unsuccessful given the powerful reinforcing properties associated with opioid drugs, including fentanyl. Here, we developed a therapeutic drug based on an AI-based platform, which was rationally designed to identify markers of dysregulation from human drug user postmortem brain tissue. Two top candidate compounds, GATC-021 and GATC-1021, were synthesized and validated with in vitro screening for target specificity. Thereafter, the drug candidates were examined for their effectiveness in modulating opioid reinforcement and intake. GATC-1021 emerged as the most efficacious compound as it significantly decreased fentanyl intake in both male and female rats, without any notable side effects. GATC-1021 was further found to modulate gene expression patterns in addiction-relevant brain regions following fentanyl-induced alterations. These findings validate GATC’s AI-based platform with its polypharmacy-focused drug development approach and further support the clinical potential of GATC-1021 as a promising therapeutic for those suffering from opioid use disorder.

Advantages of magnetic compression in rat colonic anastomosis: a comparative study with a transcriptomic perspective

Configuration of circum-Antarctic circulation at the last green- to icehouse climate transition

During the Eocene–Oligocene Transition ( ∼ 34.4 to 33.7 Ma), major climatic and tectonic changes initiated Earth’s current icehouse climate. Plate motion intensified mountain building, reduced atmospheric CO 2 , and triggered global cooling. Crucially, the opening of the Tasman Gateway and Drake Passage initiated the formation of the Antarctic Circumpolar Current (ACC), today Earth’s strongest ocean current. However, the ACC’s initial structure during its onset remains poorly understood, limiting our understanding in controlling global circulation patterns and heat distribution at the time. Here, we present data-validated, high-resolution coupled climate–ice sheet simulations of the Early Oligocene Glacial Maximum ( ∼ 33.7 to 33.2 Ma), showing that early ocean–atmosphere circulation around Antarctica was closely tied to Southern Ocean gateway geometry and the presence of the early Antarctic Ice Sheet. Unlike today, however, these gateways were not aligned with the westerly wind belt, hence limiting ACC development and promoting strong Antarctic amplification. We conclude that orogenesis, CO 2 drawdown, and Southern Hemisphere gateway opening alone were insufficient to establish a strong ACC ∼ 34 Ma. Only the later alignment of westerly winds with open oceanic gateways enabled the enhancement of interhemispheric overturning circulation, promoted carbon uptake, and the long-term stabilization of Earth’s icehouse climate.

A cut-off value for endothelial dysfunction based on the triglyceride-glucose index

A swarm intelligence approach to density function reconstruction from moments using entropy optimization

This paper presents a bioinspired optimization approach to address a class of inverse problems involving entropy optimization (EOP) from knowledge of the moments of a distribution function. In particular, we study the Hausdorff moment problem, where one seeks to reconstruct a (probability) density distribution by inverting a completely monotonic sequence of moments of the distribution in a bounded interval. It is shown that the resulting EOP can be handled very efficiently using the collective intelligence of a swarm (of optimizers), which provides a robust and accurate solution by effectively incorporating information from up to a thousand moments of the density. The efficacy of the approach is demonstrated by reconstructing the invariant density functions for the logistics map, spectral densities of large real-symmetric random matrices, encountered in the study of physics of disordered solids, and financial time series involving daily price fluctuations of a mutual fund. The agreement between true densities and the corresponding maximum-entropy approximants is examined by comparing the Kullback–Leibler divergence and the Fisher information of the densities.

Caesarean section may be associated with suspected motor developmental delay at 3 years of age in the Japan Environment and Children’s Study

An insect that cooperates like bacteria

Religiosity and political worldviews as protective factors during an ongoing national trauma

Semiochemicals and odorant receptors underlying potato cultivar susceptibility and resistance to potato tuber moth

Infestation of potato by the potato tuber moth ( Phthorimaea operculella ) varies markedly among cultivars, yet the chemical and molecular mechanisms underlying this variation remain poorly understood. Here, we combine field surveys, chemical ecology, functional genomics, and structural modeling to reveal how cultivar-specific volatile profiles shape moth oviposition behavior and pest outcomes. Field and laboratory assays identified marked differences in adult attraction, oviposition, and larval damage among potato cultivars, which correlated with distinct blends of emitted volatile organic compounds (VOCs). Behavioral analyses revealed that among other VOCs, trans -nerolidol and β-ionone act as attractants, whereas 3-carene and benzyl tiglate function as oviposition deterrents. Electrophysiological screening and heterologous expression deorphanized six female-biased odorant receptors (ORs), identifying three narrowly tuned receptors linked to cultivar susceptibility or resistance. PopeOR01, upregulated following mating, selectively detects the attractant trans -nerolidol, which is enriched in susceptible cultivars, whereas PopeOR15 and PopeOR73 are tuned to repellents benzyl tiglate and 3-carene, respectively, which are enriched in resistant cultivars. CRISPR/Cas9-mediated knockouts confirmed that PopeOR01 and PopeOR73 are essential for antennal detection and behavioral responses to their cognate ligands. AlphaFold3 modeling, molecular docking, and molecular dynamics simulations revealed conserved OR-Orco channel architecture and stable ligand-binding modes consistent with physiological and behavioral data. Together, our results establish a mechanistic link between potato cultivar chemistry, insect olfactory receptor function, and pest behavior, providing a molecular framework for sustainable, semiochemical-based management of the potato tuber moth.

Coupled methods for detecting fatigue damage in thin-walled composite structures with different types of notches

Abstract The paper focused on the fatigue testing of thin-walled composite structures with notches. The fatigue experiments were supported by non-destructive diagnostic techniques, including thermography, acoustic emission, and digital microscopy. The study analysed the influence of notch geometry on the initiation and evolution of damage in CFRP (carbon fiber reinforced polymer) specimens with a [0/45/-45/90] s lay-up. All specimens were tested under identical fatigue loading conditions. Within the scope of the research, quantitative characteristics of thin-walled structures under fatigue loading were developed, and the recorded damage mechanisms were examined qualitatively. The combination of interdisciplinary research methods made it possible to carry out a thorough analysis of composite structure behaviour. Tests involving the complete failure of the specimens were not conducted. Instead, the study focused on the detection and monitoring of early stages of damage within the low-cycle fatigue regime. The application of coupled diagnostic methods for detecting and monitoring fatigue damage made it possible to investigate the differences in damage initiation and development between specimens with U-shaped and V-shaped notches.

Expanded applicability of the triple oxygen isotope composition of phytoliths as an indicator of atmospheric relative humidity

Impaired lung function is associated with elevated blood biomarkers of AD/ADRD: unraveling the interplay with risk of dementia

The central dogma in reverse

NATON robotic-assisted unicompartmental knee arthroplasty achieves superior radiological alignment and comparable one-year functional outcomes to conventional surgery

Proteome-wide prediction of interactions between structured domains and peptide motifs reveals functionally coherent subnetworks

Many protein–protein interactions (PPIs) are mediated by the binding of short linear motifs (SLiMs) to peptide recognition domains (PRDs). Here, we describe PrePPI-SLiM, a proteome-scale computational pipeline that leverages data from the Eukaryotic Linear Motif (ELM) database to predict whether two proteins will form a peptide-mediated complex. The ELM database defines classes of protein–peptide interactions with SLiMs represented by sequence motifs and PRDs represented by Pfam domains. PrePPI-SLiM systematically evaluates all pairwise combinations of proteins within a proteome and identifies PRD–SLiM pairs that occur in the same ELM class. This evidence together with disorder prediction and sequence conservation of the motif are integrated in a naïve Bayes framework to assign a likelihood for complex formation. To obtain potential PDB templates for atomistic models of PrePPI–SLiM interactions, we associate individual PPI predictions with homologous PDB complexes involving the same PRD Pfam domain and SLIM, and obtain PDB templates for 92% of our high-confidence predictions. Moreover, studies with AF3Complex suggest that prior knowledge of the interacting PRD and SLiM, as provided here, is a critical starting point for creating a 3D model of the specific sequences of the PRD and SLiM query proteins. Finally, we demonstrate that clustering of the high-confidence PrePPI-SLiM interactome yields functionally coherent PPI networks that reveal mechanistic insights into cellular processes. The PrePPI webserver provides convenient access to high-confidence PrePPI-SLiM predictions, PDB templates for modeling, and functional networks.

Tribological performance of mechanical face seals for Martian applications

Performative planning creates a values mismatch between wildfire plans and community needs

To mitigate the potential impacts of wildfire, communities across the United States are engaging in collaborative wildfire risk mitigation planning. Planning involves identifying a set of goals, developing management strategies to achieve those goals, and codifying the goals and strategies in a written document. A plan’s goals and strategies are informed by values—the things plan authors and communities want to protect or enhance. Identifying and evaluating these values can give insight into whether a plan is meeting the needs of local wildfire risk and vulnerability, incorporating best practice from national policies, or simply reflecting broader cultural trends. This paper explores these tensions using the case of Community Wildfire Protection Plans (CWPPs), which are local (neighborhood to multicounty) plans developed collaboratively by diverse wildfire-related stakeholders. Drawing on a combination of manual coding and computational text analysis, we first characterize the values to be protected in 2268 CWPPs from across the United States. We then evaluate what shapes the values articulated in individual CWPPs, exploring the degree to which values reflect local wildfire risk and socioeconomic vulnerability, updates in policy guidance from US federal agencies, and/or broader cultural trends. This paper makes three primary contributions: 1) mapping local wildfire values at the national scale; 2) understanding tensions in environmental governance in a multilevel federalist system; and 3) advancing values as an important metric for evaluating the quality of management plans.

Manganese-nickel cobaltite/graphitic carbon nitride/cerium oxide nanocomposite for vanillin sensing in food samples

<i>BpFLC</i> coordinates seasonal and age-related flowering in <i>Betula platyphylla</i> through environmental cues and epigenetic regulation

The Flowering Locus C ( FLC ) gene is a flowering repressor in annual plants, but its function in perennial woody species remains less understood. Here, we explored the role of BpFLC in Betula platyphylla using a genotype that flowers after 5 to 6 y of growth in the field. Overexpression of BpFLC extended vegetative growth in transgenic B. platyphylla , without flowering even after 7 y in the field. CRISPR/Cas9-mediated loss of function in BpFLC led to early flowering after a 3-year growth. Integrated ATAC-seq, RNA-seq, and Flowering-Interactive Database (Flor-ID) analyses of BpFLC overexpression transgenics against the wild type identified a flowering-promoting TF BpGI ( GIGANTEA ) as a unique direct target of BpFLC. The BpFLC– BpGI binding represses BpGI ’s flowering-promoting functions. Full genome Y1H identified BpHEN4 (HUA ENHANCER4) and BpELIP1 (EARLY LIGHT-INDUCED PROTEIN1) as the only two BpFLC binding genes that shared synchronized upregulation patterns with BpFLC under various environmental cues, including temperatures and photoperiods. Overexpression of BpHEN4 or BpELIP1 in B. platyphylla activated BpFLC expression. BpHEN4 and BpELIP1 dimerize and cobind to the G-box in BpFLC ’s first intron but not the promoter for BpFLC upregulation. Our study suggested a FLC -mediated flowering repressor model in B. platyphylla where BpHEN4 and BpELIP1 are signals transducing environmental cues and cobind to BpFLC ’s first intron to activate BpFLC, leading to elevated BpGI chromatin accessibility for more effective BpFLC– BpGI interactions to drive BpGI -mediated downregulation of flowering-promoting TFs to delay flowering. The greater transgene containment with growth/biomass benefit would be a unique economic trait for any key forest species.

Inhibition of TRPC6 channel suppresses bladder cancer proliferation by disrupting store-operated calcium entry