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Identifying microbial functional guilds performing cryptic organotrophic and lithotrophic redox cycles in anaerobic granular biofilms
Granular biofilms used in anaerobic digester systems contain diverse microbial populations that interact to hydrolyze organic matter and produce methane within controlled environments. Prior research investigated the feasibility of utilizing granular biofilms obtained from an anaerobic digester to remove nitrate without the addition of exogenous electron donors. These granules possessed a unique structure of alternating light and dark iron sulfide and pyrite rich layers that potentially served as both an electron source and sink, linking carbon, nitrogen, sulfur, and iron cycles. To characterize the functional roles of diverse microbial populations enriched within these layered biofilms, we analyzed metagenomes obtained from three different granules. Comparisons between the functional gene content of forty metagenome assembled genomes (MAGs) identified phylogenetically cohesive functional guilds. Each of these functional MAG clusters was assigned to specific steps in anaerobic digestion (hydrolysis, acidogenesis, acetogenesis, and methanogenesis) and anaerobic respiration (denitrification and sulfate reduction). Comparisons with metagenomes derived from a variety of natural and engineered ecosystems confirmed that the enriched denitrifying bacteria were similar to populations typically found in wetlands and biological nitrogen removal systems. Analysis of read alignments to individual genes within the forty MAGs identified conserved genomic features that were representative of the functions that distinguished functional guilds. Overall, this research illustrates the utility of functional based classification of microorganisms for characterizing ecosystem functions and highlights the potential application of engineered ecosystems to serve as experimental models for complex natural ecosystems.
Plant-derived hydrogel and photosynthetic nano-units for myocardial infarction therapy
Donor–Acceptor Porous Aromatic Framework Cathode with Fast Redox Kinetics for Ultralow‐Temperature (−70 °C) Potassium‐Organic Batteries
Abstract Low‐temperature rechargeable batteries are essential for cryogenic energy storage. However, lowering the working temperature will exacerbate the disadvantages of slowed reaction kinetics and mechanical instability of inorganic electrode materials, thus causing severe capacity degradation. In this work, for the first time, we demonstrated that constructing a donor–acceptor (D–A) porous aromatic framework (PAF‐310) using p‐type phenazine (PZ) and n‐type hexaazatrinaphthylene (HATN) as storage blocks can accelerate charge transport and thus facilitate the reaction kinetics even at low‐temperature conditions. When employed as the cathode of potassium ion batteries (PIBs), PAF‐310 possesses higher electrochemical performance than its counterparts, including impressive discharge specific capacity (215.6 mAh g −1 at 0.2 A g −1 ) and outstanding rate performance (77.8 mAh g −1 at 50 A g −1 ) at 25 °C. Furthermore, PAF‐310 also delivers impressive specific capacities in low‐temperature conditions (168.2 mAh g −1 at −20 °C and 130.1 mAh g −1 at −40 °C at 0.2 A g −1 ). Even at −70 °C, PAF‐310 still exhibits good specific capacity (102.2 mAh g −1 at 50 mA g −1 ). Moreover, various in/ex‐situ spectral characterizations and theoretical calculations were employed to elucidate the continuous co‐storage mechanism of K + and PF 6 − in PAF‐310. This contribution sheds a feasible molecular design strategy towards low‐temperature stabilized PIBs.
Patterns and influencing factors of smokeless tobacco use among pregnant and lactating mothers in urban slums of bhubaneswar, Odisha
Associations between Kynurenine pathway metabolites and cognitive dysfunction in major depressive disorder
This research sought to investigate the relationship between cognitive impairment and kynurenine pathway metabolites in individuals diagnosed with major depressive disorder (MDD). A total of 67 patients diagnosed with MDD and 61 healthy controls (HC) were enrolled in this study. Cognitive function was assessed utilizing the MATRICS Consensus Cognitive Battery. Plasma levels of tryptophan (TRP), kynurenine (KYN), kynurenic acid (KYNA), and quinolinic acid (QUIN) were quantified by liquid chromatography-tandem mass spectrometry. Subsequently, we examined the potential associations between metabolites of the KYN pathway and cognitive dysfunction. MDD patients exhibited significantly poorer performance across all cognitive domains, including processing speed, attention/vigilance, working memory, verbal learning, visual learning, reasoning and problem-solving, and social cognition. Inter-group comparisons indicated that levels of KYN, QUIN, and the KYN/TRP ratio in MDD patients were significantly lower than those in HC, whereas KYNA and the KYNA/QUIN ratio were significantly higher. In MDD patients, a negative correlation was observed between KYN levels and working memory (r = −0.302, p = 0.020), and the KYN/TRP ratio was also negatively correlated with working memory (r = −0.307, p = 0.018). Our findings indicate that impaired working memory in MDD is correlated with increased KYN levels and KYN/TRP ratio. This suggests that the KYN pathway may play a role in the pathological mechanisms underlying neurocognitive dysfunction, particularly working memory deficits, in MDD.
CENcyclopedia: dynamic landscape of kinetochore architecture throughout the cell cycle
Risk factors for the progression of distal adding-on phenomenon after surgery in patients with Lenke type 1 and 2 adolescent idiopathic scoliosis
Molecular basis of ligand binding and receptor activation at the human A3 adenosine receptor
Abstract Adenosine receptors (ARs: A 1 AR, A 2A AR, A 2B AR, and A 3 AR) are crucial therapeutic targets; however, developing selective, efficacious drugs for them remains a significant challenge. Here, we present high-resolution cryo-electron microscopy (cryo-EM) structures of the human A 3 AR in three distinct functional states: bound to the endogenous agonist adenosine, the clinically relevant agonist Piclidenoson, and the covalent antagonist LUF7602. These structures, complemented by mutagenesis and pharmacological studies, reveal an A 3 AR activation mechanism that involves an extensive hydrogen bond network from the extracellular surface down to the orthosteric binding site. In addition, we identify a cryptic pocket that accommodates the N 6 -iodobenzyl group of Piclidenoson through a ligand-dependent conformational change of M174 5.35 . Our comprehensive structural and functional characterisation of A 3 AR advances our understanding of adenosine receptor pharmacology and establishes a foundation for developing more selective therapeutics for various disorders, including inflammatory diseases, cancer, and glaucoma.
Scalable architecture for autonomous malware detection and defense in software-defined networks using federated learning approaches
Abstract This paper proposes a scalable and autonomous malware detection and defence architecture in software-defined networks (SDNs) that employs federated learning (FL). This architecture combines SDN’s centralized management of potentially significant data streams with FL’s decentralized, privacy-preserving learning capabilities in a distributed manner adaptable to varying time and space constraints. This enables a flexible, adaptive design and prevention approach in large-scale, heterogeneous networks. Using balanced datasets, we observed detection rates of up to 96% for controlled DDoS and Botnet attacks. However, in more realistic simulations that utilized diverse, real-world imbalanced datasets (such as CICIDS 2017 and UNSW-NB15) and complex scenarios like data exfiltration, the performance dropped to an overall accuracy of 59.50%. This reflects the challenges encountered in real-world deployments. We analyzed performance metrics such as detection accuracy, latency (less than 1 s), throughput recovery (from 300 to 500 Mbps), and communication overhead comparatively. Our architecture minimizes privacy risks by ensuring that raw data never leaves the device; only model updates are shared for aggregation at the global level. While it effectively detects high-impact incursions, there is room for improvement in identifying more subtle threats, which can be addressed with enriched datasets and improved feature engineering. This work offers a robust, privacy-preserving framework for deploying scalable and intelligent malware detection in contemporary network infrastructures.
In-situ localised alignment assisted salting-out enhanced ionogels with high strength, toughness and impact resistance
Gender-specific associations of metabolic and circadian syndromes with melanoma risk: insights from NHANES 2007–2018
The sub-arc mantle has remained oxidized since the Neoproterozoic oxygenation event
Impact of a self management mobile application on quality of life and limb circumference in women with breast cancer related lymphedema
Investigational eIF2B activator DNL343 modulates the integrated stress response in preclinical models of TDP-43 pathology and individuals with ALS in a randomized clinical trial
Bite-sized self-compassion: a pilot cohort study of a well-being tool for healthcare workers
Highly conductive single-molecule junctions through electrocatalytic formation of benzyl-type Au‒C bonds
Abstract Creating reliable molecular-scale electronic devices demands strong, stable connections between metal electrodes and organic molecules. A significant challenge is forming robust chemical bonds directly to gold electrodes, as gold is notoriously unreactive. Conventional methods for creating gold-carbon (Au‒C) bonds are therefore limited. Here we demonstrate an electrocatalytic solution: using an applied voltage, we inject a single electron from a gold electrode into specific organic salts (pyridinium ions). This electron transfer breaks the salt apart, generating highly reactive carbon-based radicals. These radicals spontaneously form strong, direct covalent bonds (Au‒C) with the gold surface. Using precise single-molecule measurements, we show this radical-mediated bonding creates exceptionally stable molecular junctions. Furthermore, these junctions exhibit excellent electrical conductivity across the molecule’s core structure. This high conductivity arises because the direct Au‒C bond allows efficient overlap of electron orbitals between the gold and the molecule. Our strategy provides a versatile and controlled way to build atomically precise, highly conductive interfaces between metals and organic components, advancing the design of functional molecular electronics through tailored covalent connections.
Chirality Unbound in Graphene Nanoribbons
Abstract In this manuscript, we report the first demonstration of controlled helicity in extended graphene nanoribbons (GNRs). We present a wealth of new graphene nanoribbons that are a direct consequence of the high‐yielding and robust synthetic method revealed in this study. We created a series of defect‐free, ultralong, chiral cove‐edged graphene nanoribbons where helical twisting of the graphene nanoribbon backbone is tuned through functionalization with chiral side chains. S ‐configured point chiral centers in the side chains transfer their chiral information to induce a helically chiral, right‐handed twist in the graphene nanoribbon. As the backbone is extended, these helically twisted graphene nanoribbons exhibit a substantial increase in their circular dichroic response. The longest variant synthesized consists of an average of 268 linearly fused rings, reaching 65 nm in average length with nearly 10 full end‐to‐end helical rotations. The structure exhibits an extraordinary |Δ ε | value of 6780 M −1 cm −1 at 550 nm—the highest recorded for an organic molecule in the visible wavelength range. This new chiroptic material acts as room‐temperature spin filters in thin films due to its chirality‐induced spin selectivity.