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Adaptive electricity consumption forecasting approach for universal environments

Metabolic engineering of <i>Bacillus subtilis</i> for the production of active hemoglobins and myoglobins by improving heme supply

Hemoglobins (Hb) and myoglobins (Mb) are important hemoproteins with broad applications in food and medicine. Microbial cell factory is a promising approach for the green and sustainable production of hemoproteins. However, current microbial hosts face the challenges of safety and insufficient heme supply. Here, we report a global regulation strategy, “push–restrain–pull–block,” to enhance heme supply for producing various active Hb and Mb in food-grade Bacillus subtilis . Initially, the insufficient supply of the precursor 5-aminolevulinate was overcome by relieving feedback inhibition and mitigating the negative effects of HemX on HemA. Next, HemD was identified as the primary uroporphyrinogen III synthase and self-assembled with HemC to minimize the formation of the uroporphyrinogen I by-product. Additionally, the coproporphyrin-dependent pathway was selected as the superior downstream route for heme synthesis, and crucial rate-limiting steps were subsequently enhanced. Moreover, heme consumption was blocked by eliminating protoheme IX farnesyltransferase. Finally, through the combination and fine-tuned expression of key genes, a 221-fold improvement of heme supply was achieved in the engineered strain. Using this stable prokaryotic chassis, we achieved production of 0.81, 0.82, 1.11, and 1.01 g L −1 of soybean Hb, clover Hb (C-Hb), bovine Mb (B-Mb), and porcine Mb, respectively, through fermentation, marking the highest reported titers in prokaryotic systems. These hemoproteins exhibit properties similar to natural standards. Furthermore, the synthesized C-Hb and B-Mb demonstrated superior effects for preparing plant-based meat analogs as colorants and flavoring agents. This work provides a universal platform for producing other high-value hemoproteins, promising future advancements in food processing and biocatalysis.

Numerical analysis of coal rock gas dynamics disaster risk in coal thickness variation area and research on prevention and control

Divergent oxygen trends in ice-covered lakes driven by ice-cover decline and ecological memory

Dissolved oxygen (DO) is an essential resource in ice-covered lakes, regulating water quality and biodiversity, including the survival of economically important fish species. Most of the world’s lakes seasonally freeze, often resulting in oxygen depletion as ice cover inhibits water column ventilation and snow cover limits photosynthesis while respiration continues. Widespread shortening of ice-cover duration in a warmer world might improve winter oxygenation, but this hypothesis remains untested. Here, we performed a systematic analysis of 6.6 million physical and chemical observations from 19,645 lakes in the Northern Hemisphere during 1960 to 2022. Contrary to expectations, under-ice DO trends ranged from significantly negative in small lakes (A surf &lt;10 ha) (−0.14 ± 0.05 mg L −1 decade −1 ) to significantly positive in large lakes (≥10 4 ha) (0.11 ± 0.03 mg L −1 decade −1 ). This morphometric scaling emerged partly because ice-cover periods have shortened 2.2 times faster in large lakes compared to small lakes. Hierarchical modeling revealed that in smaller lakes, increasingly oxygen-depleted conditions in summer carried over to the ice-cover season, because fetch size limited wind-driven aeration in fall. As a result of this cross-seasonal ecological memory, under-ice hypoxic zones have expanded. Oxygen trended most negative in small eutrophic and humic lakes with high seasonal oxygen depletion rates. In larger lakes (≥10 3 ha), negligible summer deoxygenation, prolonged ventilation in fall, and shortening of the oxygen drawdown period in winter explained positive DO trends. However, in the vast majority of seasonally ice-covered lakes, which are small, continued climate warming is likely to exacerbate deoxygenation.

Changes in saddle setback and intensity affect comfort and lower limb kinematics in recreational cyclists

How to tackle the looming challenge of solar PV panel recycling

Advancing the accuracy of clathrin protein prediction through multi-source protein language models

Abstract Clathrin is a key cytoplasmic protein that serves as the predominant structural element in the formation of coated vesicles. Specifically, clarithin enables the scission of newly formed vesicles from the plasma membrane’s cytoplasmic face. Efficient and accurate identification of clathrins is essential for understanding human diseases and aiding drug target development. Recent advancements in computational methods for identifying clathrins using sequence data have greatly improved large-scale clathrin screening. Here, we propose a high-accuracy computational approach, termed PLM-CLA, to achieve more accurate identification of clathrins. In PLM-CLA, we leveraged multi-source pre-trained protein language models (PLMs), which were trained on large-scale protein sequences from multiple database sources, including ProtT5-BFD, ProtT5-UR50, ProstT5, and ESM-2. These models were used to encode complementary feature embeddings, capturing diverse and valuable information. To the best of our knowledge, PLM-CLA is the first attempt designed using various PLM-based embeddings to identify clathrins. To enhance prediction performance, we utilized a feature selection method to optimize these fused feature embeddings. Finally, we employed a long short-term memory (LSTM) neural network model coupled with the optimal feature subset to identify clathrins. Benchmarking experiments, including independent tests, showed that PLM-CLA significantly outperformed state-of-the-art methods, achieving an accuracy of 0.961, MCC of 0.917, and AUC of 0.997. Furthermore, PLM-CLA secured outstanding performance in terms of MCC, with values of 0.971 and 0.904 on two existing independent test datasets. We anticipate that the proposed PLM-CLA model will serve as a promising tool for large-scale identification of clathrins in resource-limited settings.

Sulfur-mediated transformation from osmium nanocrystals to single atoms for efficient alkaline hydrogen evolution reaction

Osmium (Os)-based catalysts, recognized for their unique chemical and electronic properties along with cost-effectiveness, hold great potential for the hydrogen evolution reaction (HER). However, their practical application has long been limited because pure Os exhibits excessively strong adsorption of intermediates and suffers from stability issues. Herein, we report the development of a highly stable catalyst achieved by implanting the sulfur (S) atom into the matrix, facilitating the transformation of Os nanocrystals into Os single atoms. The prepared atomically dispersed Os catalyst (Os-SA@SNC) demonstrates outstanding catalytic activity, requiring only a 13 mV overpotential to achieve a current density of 10 mA cm −2 in 1.0 M potassium hydroxide (KOH) solution, as well as the excellent durability. This performance surpasses that of commercial Pt/C and outperforms most of the reported state-of-the-art electrocatalysts. Theoretical simulations clarify the important role of S atoms in promoting the dispersion and diffusion of Os atoms. Moreover, density functional theory calculations indicate that S atoms adjust the local electronic structure of Os active sites, further facilitating the adsorption/dissociation of H 2 O and optimizing the hydrogen adsorption free energy (ΔG *H ), thereby accelerating the kinetics of both the Volmer and Heyrovsky steps in alkaline HER. This work revitalizes Os-based catalysts for energy conversion and paves the way for innovative HER catalyst design and application to contaminated soil/water remediation.

A novel obfuscation method based on majority logic for preventing unauthorized access to binary deep neural networks

Cerebral blood flow is modulated by astrocytic cAMP elevation independently of IP ₃ R2-mediated Ca ²⁺ signaling in mice

Local neural activation drives regional increase of cerebral blood flow (CBF), in a phenomenon known as functional hyperemia. Astrocytes, which enwrap cerebral blood vessels and respond to neuronal activity through their G protein–coupled receptors (GPCRs), play a vital role in brain energy metabolism. Although astrocytic calcium (Ca 2+ ) signaling has been widely studied in relation to neurovascular coupling, the role of cyclic adenosine monophosphate (cAMP), another key second messenger of GPCRs, on CBF has not been established. In this study, we explored the effects of optogenetically induced astrocytic cAMP elevation on CBF. We engineered adeno-associated viral vectors (AAVs) to express a bacterial photoactivated adenylyl cyclase in astrocytes, which triggers an increase in cAMP upon blue light stimulation. Opto-stimulation also elevated astrocytic Ca 2+ , albeit with a delayed onset under mild stimulation. In vivo imaging of anesthetized and awake wild-type mice through a thinned skull preparation revealed that optogenetically induced astrocytic cAMP elevation led to pronounced arteriole dilation, with a latency of 1.8 s and maximal dilation reached within 10 s in the awake state and slower response under anesthesia. Mild opto-stimulation causing sensory-level cAMP elevations was sufficient to induce arteriole dilation. This effect was preserved in IP 3 receptor type 2-knockout (IP 3 R2 −/− ) mice, indicating a mechanism independent of GPCR-induced intracellular Ca 2+ elevations. These findings highlight astrocytic cAMP as a key modulator of cerebral vasodilation, contributing to our understanding of local CBF regulation. This study opens broad avenues for understanding astrocyte-mediated control of CBF and its implications in neurological diseases characterized by dysregulated blood flow.

Association and predictive value of the triglyceride glucose-weight adjusted waist index for cardiovascular outcomes in patients with type 2 diabetes

A privileged ER compartment for posttranslational heteromeric assembly of an ion channel

Mechanisms underlying heterotypic subunit assembly of ion channels and other oligomeric complexes are poorly understood. In the human heart, heteromeric assembly of two isoforms encoded by the human ether-à-go-go related gene ( hERG ) is essential for the normal function of cardiac I Kr in ventricular repolarization, with loss of hERG1b contributing to arrhythmias associated with long QT-syndrome (LQTS). While hERG1a homomers traffic efficiently to the plasma membrane, hERG1b homomers are retained in the endoplasmic reticulum (ER). When expressed together, the two subunits avidly associate during biogenesis. Seeking rules specifying heteromeric association, we characterized the fate of hERG1b proteins using confocal and superresolution imaging in fixed and live HeLa cells. We found hERG1b sequestered in punctate intracellular structures when expressed alone in HeLa cells. These puncta, which depend on the presence of an N-terminal “RXR” ER retention signal, represent a privileged ER subcompartment distinct from that containing ER-retained, type 2 (hERG-based) LQTS mutant proteins, which were rapidly degraded by the proteasome. Introducing hERG1a to cells with preformed hERG1b puncta dissolved these puncta by rescuing extant hERG1b. Rescue occurred by association of fully translated hERG1b with 1a, a surprising finding given previous studies demonstrating cotranslational heteromeric association. We propose that sequestration limits potentially deleterious surface expression of hERG1b homomeric channels while preserving hERG1b for an alternative mode of heteromeric hERG1a/1b channel assembly posttranslationally. These findings reveal a surprising versatility of biosynthetic pathways promoting heteromeric assembly.

Rapidly increasing cyanobacteria blooms in the subarctic Great Slave Lake: observations from Indigenous, local, and scientific knowledge

Abstract Cyanobacteria blooms, typically associated with warm, eutrophic lakes, are increasingly observed in colder, oligotrophic lakes. Cyanobacteria blooms can have ecological impacts and pose health risks when composed of toxin-producing taxa. By combining Indigenous, local, and scientific knowledge sources, we document a profound shift in Great Slave Lake—a huge, remote, oligotrophic lake in Northwest Territories, Canada. Suspected blooms were first observed in 1989, localized near point-source sewage effluent. Since 2009, sporadic blooms have appeared in new areas of the North Arm, away from known point source nutrients, and become increasingly frequent. By 2020, bloom density increased, with the densest and most widespread blooms observed in 2024. These blooms have generally been nearshore and transient, most frequently located in sheltered waters, which are warmer and shallower relative to the rest of the lake. Dolichospermum is the dominant genus, with no microcystin toxins detected. We hypothesize these unprecedented blooms may be climate-driven, enabled by a combination of warmer water, reduced wind and ice cover, and potentially fueled by nutrient inputs from record water levels, intensified wildfires, permafrost thaw, and cultural eutrophication. By synthesizing across knowledge systems, we establish a foundation for collaborative research and monitoring in rapidly changing northern water bodies.

Epigenetic cellular memory in <i>Pseudomonas aeruginosa</i> generates phenotypic variation in response to host environments

Phenotypic diversification within pathogen populations can enhance survival in stressful environments, broaden niche colonization, and expand the ecological range of infectious diseases due to emerging collective pathogenicity characteristics. We describe a gene regulatory network property in the opportunistic pathogen Pseudomonas aeruginosa that generates diversity of gene expression and pathogenicity behavior at the single-cell level and that is stabilized by epigenetic cellular memory. The resulting heterogeneity in the expression of the glpD gene—an indicator of host-derived glycerol metabolism and intra-host presence—shapes adaptive processes that are subject to natural selection. Our work on how epigenetics generates phenotypic variation in response to the environment and how these changes are inherited to the next generation provides insights into phenotypic diversity and the emergence of unique functionalities at higher levels of organization. These could be crucial for controlling infectious disease outcomes.

Localized brain stimulation with mild magnetic hyperthermia promotes microglia activity towards reactive and autophagic phenotypes in vivo

Spin-informed universal graph neural networks for simulating magnetic ordering

The screening and discovery of magnetic materials are hindered by the computational cost of first-principles density-functional theory (DFT) calculations required to find the ground state magnetic ordering. Although universal machine-learning interatomic potentials (uMLIPs), also known as atomistic foundation models, offer high-fidelity models of many atomistic systems with significant speedup, they currently lack the inputs required for predicting magnetic ordering. In this work, we present a data-efficient, spin-informed graph neural network framework that incorporates spin degrees of freedom as inputs and preserves physical symmetries, extending the functionality of uMLIPs to simulate magnetic orderings. This framework speeds up DFT calculations through better initial guesses for magnetic moments, determines the ground-state ordering of bulk materials and even generalizes to magnetic ordering in surfaces. Furthermore, we implement a closed-loop anomaly detection approach that effectively addresses the classic “chicken-and-egg” problem of creating a high-quality dataset while developing a uMLIP, unearthing anomalies in large benchmark datasets and boosting model accuracy.

ADME analysis, metabolic prediction, and molecular docking of lipoic acid with SARS-CoV-2 Omicron spike protein

A circular RNA overcomes acquired resistance to BET inhibitors by antagonizing IGF2BP2-mediated c-MYC translation in TNBC

Bromodomain-and-extraterminal-domain (BET) proteins are promising therapeutic targets for refractory solid tumors, including triple-negative breast cancer (TNBC). However, acquired resistance to BET inhibitors (BETi) remains a significant clinical challenge. Elucidation of the underlying mechanisms of BETi resistance is therefore of critical importance. In this study, we identified the RNA-binding protein IGF2BP2 as a key driver of acquired BETi resistance in TNBC, primarily through its role in enhancing the translation of c-MYC mRNA. Given that IGF2BP2 is not an ideal target for small-molecular drugs, we performed RNA immunoprecipitation sequencing (RIP-Seq) and found circRNA-BISC as a potent IGF2BP2 repressor. BISC effectively inhibited both c-MYC translation and BETi resistance. Notably, BISC contains a “CAC-linker-XGGX” motif that specifically binds IGF2BP2 rather than to IGF2BP1 and IGF2BP3. The efficacy and selectivity of BISC in targeting IGF2BP2 prompted further exploration of BISC-based RNA therapeutics for TNBC. In vitro transcribed and circularized BISC, when combined with the BETi OTX-015, demonstrated impressive tumor regression in BETi-resistant TNBC models without detectable toxicity. These findings establish BISC as a potent IGF2BP2 repressor and highlight the feasibility of circRNA-based therapeutic strategies to overcome BETi resistance in TNBC.

Deciphering the role of crucial miRNAs involved in diabetic cardiomyopathy through a multiomics approach

Abstract Conventional drug discovery routes take decades to identify critical gene signatures involved in a disease. Though in silico platforms and software have simplified the process by reducing the time and energy needed to arrive at significant molecular targets for disease conditions, they are not accessible to everyone. Here, we propose a systematic strategic protocol to identify critical players in the disease pathogenesis using the vast amount of molecular omics data available on various public domains, setting diabetic cardiomyopathy as the case study. We use databases like KEGG, DisGeNET, HMDD, and literature to curate the key genes and miRNAs associated with the disease. We analysed 395 genes and 20 miRNAs for our analysis. Critical pathways like the insulin resistance pathway, the AGE–RAGE pathway, and the PI3K–AKT–mTOR pathway were enriched in our analysis through the Metascape platform. A protein–protein interaction network was generated using the STRING database. The export of this network to the Cytoscape platform helped to identify the clusters, node interactions, and hub genes. Our approach finally identified hsa-miR-302a-3p as the critical miRNA that regulates the highest-ranked hub gene, AKT1. This systematic methodology lays a solid foundation for the identification of critical therapeutic targets for any disease condition, thereby increasing the success rate for further stages of development.

Gelated microvesicle–mediated delivery of mesenchymal stem cell mitochondria for the treatment of myocardial infarction

Mitochondrial dysfunction is closely linked to cardiomyocyte injury following myocardial infarction (MI). While mitochondrial transplantation is a promising therapeutic strategy, challenges remain in maintaining mitochondrial structural integrity, enhancing delivery efficiency, and increasing the mitochondrial supply. Herein, we developed a gelated microvesicle–based mitochondria delivery system (Mito@Microgels) for transplanting mesenchymal stem cell mitochondria, addressing the aforementioned issues. Further decoration of phosphatidylserine on the surface of Mito@Microgels boosted cellular uptake efficiency by cardiomyocytes. These Mito@Microgels effectively deliver active mitochondria to cardiomyocytes, improving the mitochondrial network architecture and function and consequently reducing the cellular injury induced by oxidative stress. Moreover, Mito@Microgels attenuated the inflammatory phenotype of macrophages, helping resolve excessive local inflammation. In vivo animal studies using a rat MI model further validated the therapeutic efficacy of the Mito@Microgels, as evidenced by improved myocardial function, prevention of infarcted left ventricular wall thinning, and increased cardiomyocyte survival. Our study introduces an efficient mitochondrial delivery strategy with significant potential for cardiac repair post-MI and other mitochondria-related diseases.