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Directed regulation of high-temperature Daqu microbiota and metabolites using synthetic communities.

Assessing Handover Quality in the Emergency Department: Evaluating Communication Between EMS and Triage Nurses Using the Handoff CEX Italian Scale.

The unique human ability to process complex language requires the interaction of multiple brain areas located in the inferior frontal and posterior temporal cortex connected by white matter fiber tracts. These fiber tracts underlie the transfer of information between brain regions. In recent years, MRI of white matter brain networks has provided important insights into the plasticity of the structural brain basis underlying language. This structural network is shaped during childhood as a function of language learning by strengthening the connectivity between language-relevant regions mainly in the left hemisphere. In this way, the specific linguistic properties of the native language tongue lead to a modulation of the core language network observable in the adult brain. The brain basis underlying language processing also changes when a second language is learned, as shown by differences in brain connectivity between bilingual and monolingual individuals and by dynamic adaptations during second language learning. Studies of people who use sign language as their native language have shown a domain specificity of the sensory and motor systems rather than the core language network. This separation of the core language system from the sensory-motor system is evolutionarily based. Although the basic auditory-motor interface system is also present in monkeys and apes, the core language system reveals key differences between humans and nonhuman primates. Understanding the function and plasticity of this network is of paramount importance for human cognitive processes, including development and developmental disorders.

Chiral magnons are collective spin excitations whose dispersions break momentum inversion symmetry, $\omega(\boldsymbol{k}) \neq \omega(-\boldsymbol{k})$, leading to intrinsically nonreciprocal spin-wave propagation. This built-in directionality offers new opportunities for spin information transfer, thermal-spin interconversion, and low-dissipation nonreciprocal microwave devices, in a manner complementary to but distinct from topological magnonics. This review develops a unified framework for chiral magnons, covering symmetry-breaking mechanisms, material realizations, transport responses and many-body non-Hermitian dynamics, and evaluates routes toward room-temperature, device-relevant platforms. The discussion is based on symmetry analysis, model Hamiltonians and spin-wave theory, in combination with first-principles calculations and recent spectroscopic and transport measurements. The microscopic origins of chiral magnons are organized into three interrelated aspects, spin-orbit coupling (SOC)-driven Dzyaloshinskii-Moriya interactions (DMI) in non-centrosymmetric magnets and interfaces, altermagnetism in the weak SOC regime without DMI, and the spin space group (SSG) framework. On this basis, representative materials such as CrSb, α-MnTe, RuO<sub>2</sub> and MnF<sub>2</sub> are compared in terms of energy scales, coherence, momentum anisotropy and experimental visibility, clarifying how magnon splittings and lifetimes are reflected in direction-dependent spin Seebeck, spin Nernst and thermal Hall signals. The review further summarizes bulk-gap and Berry-curvature induced chiral edge states, enhancement of nonreciprocity via chiral spin pumping and cavity-magnon hybrids, and non-Hermitian features arising from multiparticle damping and gain-loss competition. Furthermore, remaining challenges, such as the stability of physical properties at room temperature, quantitative calibration of spectral and transport properties, as well as many-body competition also outlined. Finally, the possible strategies based on SSG-guided materials screening, multi-modal metrology and geometry phase engineering toward efficient spin logic, THz isolators and quantum routing based on chiral magnons also proposed.

Battery-Free Sensor Nodes (BFSNs) used in Simultaneous Wireless Information and Power Transfer (SWIPT) systems often rely on lightweight communication protocols with minimal security overhead due to strict energy constraints. As a result, conventional protocol-dependent security mechanisms cannot be employed, leaving BFSNs vulnerable to replay, spoofing, and other security threats. This paper explores a protocol-independent security mechanism that enhances BFSN security by exploiting the power wave for controlled backscattering. The method introduces a Manchester-encoded digital private key generated by the BFSN’s low-power microcontroller and backscattered through a polarization-shifting module enabled by a fail-safe RF switch, thereby avoiding the need for a dedicated backscattering rectifier. A LoRaWAN-based BFSN integrating this add-on module was implemented to experimentally validate the approach. Results show successful extraction of the backscattered key with minimal energy overhead (approximately 95 µJ for a 3 ms identification sequence), while the original high-efficiency RF rectifier used for harvesting remains unmodified. The orthogonal polarization between the incoming and backscattered waves additionally reduces clutter and cross-jamming effects. These findings demonstrate that secure identification can be seamlessly incorporated into existing BFSNs without altering their core architecture, offering an easy-to-integrate and energy-efficient solution for improving security in SWIPT-based sensing systems.

Plants can 'cry for help' in response to herbivory as well as anticipate herbivory by detecting specific environmental cues before damage occurs. But can plants 'anticipate help?' Building on the optimal defence and information transfer models of induced plant defence, we argue they can. We find literature support for key assumptions of the 'anticipating help' hypothesis, which proposes plants can (1) detect cues that signal reliable protection from enemies of herbivores (bodyguards), and (2) downregulate direct anti-herbivore resistance when bodyguards compensate. In an original a priori test of the assumptions of cue detection and downregulation of direct resistance, we use a meta-analysis of sequential herbivory experiments. We found that plants express induced susceptibility (dampened direct resistance) towards leaf-chewing herbivores only after induction by myrmecophilous sap-feeding herbivores, a putative cue for reliable ant-mediated protection against chewing herbivores. More generally, we expect 'anticipating help' behaviour in plants when local environmental cues predict reliable anti-herbivore protection from bodyguards that compensate for dampened direct resistance at a reduced fitness cost. The 'anticipating help' hypothesis can explain several enigmatic issues, such as induced susceptibility, associational resistance of plants, and how indirect resistance may benefit plant fitness under a wider range of conditions than previously recognised.

There is little data in the literature on the possible sequelae of subdural empyema. The presented case describes the novel information approach in diagnosis and treatment of a patient, who, after surgery for interhemispheric empyema, continued to have various complaints manifested by signs of damage to the nervous system, with which he sought treatment at the Outpatient department of the Research Institute of Virology. The patient underwent medicament testing to identify possible infectious agents in the patient’s internal organs, followed by application of levofloxacin, ribavirin and nystatin (tablet forms) placed in the field created by an ultra-low intensity laser as it passes through a spirally twisted waveguide emitter of the “device for transfer information from a drug to the human body”.According to the MRI of the brain and the patient’s clinical condition, this management tactic led to the disappearance of the patient’s leading complaints, a decrease in the symptoms of the disease, and an improvement in the prognosis of the pathological process. The proposed clinical approach is innovative, and the case report describes the results of treating a patient with neuro-infection after subdural empyema who was treated with a novel information medicine method. The study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Institutional Review Board of the Research Institute of Virology

Background: Decoding covert spatial attention (CSA) from dry, low-channel electroencephalography (EEG) is key for gaze-independent brain–computer interfaces (BCIs). Methods: We evaluate, on sixteen participants and three tasks (CSA, motor imagery (MI), Emotion), a four-electrode, subject-wise pipeline combining leak-safe preprocessing, multiresolution wavelets, and a compact Hybrid encoder (CNN-LSTM-MHSA) with robustness-oriented training (noise/shift/channel-dropout and supervised consistency). Results: Online, the Hybrid All-on-Wav achieved 0.695 accuracy with end-to-end latency ~2.03 s per 2.0 s decision window; the pure model inference latency is ≈185 ms on CPU and ≈11 ms on GPU. The same backbone without defenses reached 0.673, a CNN-LSTM 0.612, and a compact CNN 0.578. Offline subject-wise analyses showed a CSA median Δ balanced accuracy (BAcc) of +2.9%p (paired Wilcoxon p = 0.037; N = 16), with usability-aligned improvements (error 0.272 → 0.268; information transfer rate (ITR) 3.120 → 3.240). Effects were smaller for MI and present for Emotion. Conclusions: Even with simple hardware, compact attention-augmented models and training-time defenses support feasible, low-latency left–right CSA control above chance, suitable for embedded or laptop-class deployment.

Abstract This paper addresses the problem of imbalanced samples in the ball screw pair in engineering, as well as challenges such as poor model training performance and difficulties in edge deployment. A fault diagnosis method based on mechanism transfer is proposed. By analyzing the fault mechanism similarities in rolling components, the knowledge distillation framework is utilized to explore feature information transfer for cross-object fault diagnosis knowledge sharing. First, the fault mechanism similarities between rolling bearings and ball screw pairs are studied, and a unified description of fault mechanisms in rolling components is explored. This is achieved by leveraging the comprehensive knowledge of rolling bearings to complete the sample space of ball screw pairs, thereby improving fault diagnosis performance. Then, a dual-layer feature alignment knowledge distillation (DLFA-KD) framework is constructed. ResNet50 is used as the teacher model, and a lightweight student model is designed with multi-kernel depthwise separable convolutions (MK-DSC). Maximum mean discrepancy (MMD) and L2 distance are introduced to guide dual-layer feature alignment, and cross-entropy loss is used to optimize classification performance. Finally, a comprehensive sample set is constructed using multi-condition bearing data, and an imbalanced sample set is created using multi-condition ball screw pair data for mechanism transfer fault diagnosis performance verification. The experimental results show that the proposed method significantly improves model performance under various levels of sample imbalance, with an accuracy of up to 99.675%. Moreover, the student model’s parameter count is only 2% of that of the teacher model, and after edge deployment, the inference speed increases by 98.1 times. This method provides a new approach for edge-based intelligent fault diagnosis in industrial scenarios with imbalanced samples.

The role of prefrontal somatostatin interneurons in emotion recognition is well characterized. Here, for the first time, we investigated the role of these neurons during remote transfer of emotional information in the safe environment of the home cage. To do that mice with fluorescently labelled somatostatin interneurons were housed in pairs for three weeks, one labelled an Observer, and the other a Demonstrator. In the test session, the Demonstrator was subjected to aversive stimuli outside of the home cage, while the Observer remained there undisturbed. Upon the return of the Demonstrator to the home cage, we recorded the interactions of the two animals. The behavior of both partners, assessed and classified with machine learning algorithms, was clearly affected by the emotional state of the Demonstrator. To assess the role of prefrontal somatostatin interneurons in this process we chemogenetically manipulated their activity in the Observers and found that activation of these cells abolishes the enhanced social investigation of a stressed Demonstrator. This is associated with disinhibition of the prefrontal cortex. The manipulation also affects the neuronal activation patterns in Demonstrators, which seems to reflect the change in the behavior of the Observers.

Restoring stiffness perception in prosthetic users through non-invasive methods remains a major challenge in haptic feedback research. This study evaluates a wearable vibrotactile stimulation system that conveys object stiffness information through two encoding strategies: Proposed Spatiotemporal Encoding and Circular Encoding, applied to two anatomical locations: upper-arm and forearm. Ten healthy participants completed structured trials of stiffness-discrimination involving vibrotactile cues corresponding to four stiffness categories. The results showed significantly higher classification accuracy (CA) and information transfer (IT) with the Proposed encoding strategy at both sites. The upper-arm-proposed configuration achieved peak performance (CA: 97.75%, IT: 1.84 bit/s), whereas the forearm-circular strategy yielded the lowest (CA: 73.62%, IT: 0.86 bit/s). NASA-TLX scores indicated a significantly lower mental workload for the proposed strategy, with the upper-arm feedback location providing superior perceptual clarity. A supplementary evaluation with a transradial amputee further demonstrated that the proposed encoding strategy remained interpretable, achieving classification accuracies above 85%. The classification accuracies over different conditions followed the same pattern as observed in healthy participants. These findings validate the importance of encoding geometry and stimulation site in designing effective haptic interfaces and support the feasibility of spatially distributed, non-invasive vibrotactile feedback for enhancing tactile perception in prosthetic applications.

This study explores the impact of SBAR communication on interprofessional collaboration in healthcare. The main issue is the lack of structured communication among healthcare professionals. This lack of communication often leads to clinical errors. These clinical errors can interfere with the effectiveness of team coordination. A systematic literature review method was used to collect articles from PubMed, Google Scholar. The articles were selected based on inclusion criteria for the period 2020 to 2025. The main results show the implementation of SBAR. The application of SBAR improves clarity in information transfer. SBAR also strengthens cooperation between doctors and nurses. This cooperation contributes to reducing the risk of incidents in patients through good team coordination. These findings highlight the importance of SBAR in simplifying the exchange of important information. SBAR helps create a culture of safety for patients. This culture of safety serves to support the maximum healing process. The recommendations provided emphasize the importance of continuous training. This training aims to overcome various obstacles in its implementation in the field.

ConspectusAccurate equilibrium geometries are fundamental to predictive spectroscopy, reliable thermochemistry, and rational molecular design. Yet achieving high accuracy beyond small molecules remains a formidable challenge. High-level wave function methods, while exceptionally accurate, are computationally prohibitive for systems containing dozens of atoms. Density functional approaches, though efficient, often lack consistent reliability across diverse chemical environments. Though reduced-scaling strategies have enabled precise energy calculations for large systems, equivalent progress in the determination of equilibrium structures has been slower, leaving a persistent gap between the predictive accuracy and computational feasibility.This Account presents an integrated framework that tries to bridge this gap by combining composite quantum-chemical methods, data-driven corrections and fragment-based modeling. At its core lie explicitly correlated composite schemes capable of delivering mÅ/mrad accuracy (usually referred to as spectroscopic accuracy) for the geometrical parameters of molecules with up to about 20 atoms. These methods underpin the construction of a benchmark-quality geometry library (LCB25), comprising nearly 400 fragments encompassing all major functional groups and ring systems relevant to chemical, biological and pharmaceutical applications.Building on this reference, systematic bond-based corrections derived from LCB25 transfer spectroscopic-level accuracy to more affordable double-hybrid and hybrid functionals. Linear regressions suffice for double-hybrid models, while machine-learning Δ-corrections extend the same accuracy to hybrid functionals. Together, these refinements lead to geometries of near-spectroscopic accuracy for medium and large molecules (50-100 atoms) at a fraction of the cost of high-level composite methods. For larger architectures, the Nano-LEGO platform automates the assembly of accurate molecular geometries from preoptimized fragments, preserving the local structural fidelity within complex frameworks.Within this modular and hierarchical approach, continuous chemically meaningful descriptors known as synthons serve as the common language linking fragment-based modeling, data-driven corrections, and machine-learning predictions. This representation facilitates the transfer of local structural information across chemical families and supports the exploration of vast regions of chemical space with controlled accuracy.The same principles extend naturally to the design of functional and sustainable materials. Spectroscopically accurate yet affordable structural predictions are instrumental in the rational development of organocatalysts, molecular components for optoelectronic devices and supramolecular frameworks for applications aligned with the goals of circular economy.These methodological advances are complemented by efficient optimization algorithms, vibrational corrections based on second-order vibrational perturbation theory, and fully interoperable workflows that ensure scalability and robustness. Collectively, they establish a hierarchical data-enriched ecosystem delivering accurate, transferable, and cost-effective molecular geometries. Applications range from atmospheric and astrochemical intermediates to biomolecules, pharmaceuticals, and sustainable molecular materials, paving the way for predictive spectroscopy and structure-based design. All components of this framework are openly available through web platforms and GitHub, promoting transparency, accessibility, and community development.

Emerging evidence highlights the potential role of auditory stimulation in enhancing sleep-dependent memory consolidation. Pink noise appears to be an effective auditory stimulus for enhancing memory consolidation, likely due to its wide-range influence on brain oscillations. However, the specific underlying mechanisms by which pink noise enhances memory consolidation remain unclear. This perspective article presents a novel hypothesis exploring how pink noise, delivered through closed-loop auditory stimulation, may facilitate memory consolidation. Specifically, we suggest that pink noise may reach the hippocampus via the rapid auditory pathway, potentially increasing the likelihood of sharp-wave ripple (SW-R) generation. By increasing hippocampal ripple activity, the overall likelihood of synchronization with spindles and slow oscillations is also increased, enhancing hippocampal-cortical coupling. This suggests that pink noise might indirectly support slow oscillation-ripple-spindle coordination to promote systems-level consolidation and interregional information transfer. This, in turn, could enable long-term memory storage and support abstraction and generalization. Our hypothesis emphasizes a bottom-up mechanism originating from the hippocampus. Although this hypothesis currently lacks direct support from subcortical recordings, it builds on existing knowledge of sleep rhythms, hippocampal auditory pathways, and the known effects of SW-R modulation on memory formation. This perspective offers a framework for future work investigating the mechanisms by which pink noise stimulation can lead to memory enhancement.

40 Hz light flicker stimulation is deemed to hold considerable promise in the treatment of Alzheimer's disease (AD). However, whether its long-term effect can improve working memory and its related mechanisms remains to be further explored. In this study, 21 adult Wistar rats were randomly divided into the AD light-stimulation group, the AD group and the control group. AD models were established in the first two of these groups, with the light-stimulation group receiving long-term 40 Hz light flicker stimulation. Working memory performance across groups was subsequently evaluated using the T-maze task. To investigate the potential neural mechanisms underlying the effects of 40 Hz light stimulation on working memory, we examined changes in neuronal excitability within the hippocampus (HPC) and medial prefrontal cortex (mPFC), as well as alterations in inter-regional synchronization of neural activity. The findings demonstrated that prolonged 40 Hz light stimulation significantly improved working memory performance in AD model rats. Furthermore, the intervention enhanced the synchronization of neural activity between the hippocampus (HPC) and medial prefrontal cortex (mPFC), as well as the efficiency of information transfer, primarily mediated by theta and low-frequency gamma oscillations. This study provides theoretical support for exploring the mechanisms of 40 Hz light flicker stimulation and its further clinical application in the prevention and treatment of Alzheimer's disease.

Brain computer interface (BCI) system includes multiple links such as stimulus presentation, data acquisition, signal processing, external device control and command feedback. As an open-source software platform which covers all links of BCI chain, meta brain computer interface (MetaBCI) has provided flexible solutions for effectively encoding, decoding and feeding back brain activities, but has not yet provided an integrated tool that can support the implementation of a complete BCI system. In view of the above shortcoming, this paper designed and constructed a brain-controlled unmanned aerial vehicle system by using MetaBCI, which realized the online control of the physical unmanned aerial vehicle. The results of the experiment involving 10 subjects indicated that the average online classification accuracy and information transfer rate (ITR) of this system could reach 93.83% and 38.57 bits/min, respectively, which verified the feasibility of constructing a practical BCI system for external device control by using MetaBCI. Meanwhile, this paper elaborated the design idea, implementation process and the usage logic of MetaBCI toolkit involved in this brain-controlled unmanned aerial vehicle system in detail, hoping to provide guidance for subsequent developers to design and construct BCI systems that can meet individual needs by using MetaBCI independently.

Signaling quantum channels are fundamental to quantum communication, enabling the transfer of information from input to output states. In contrast, thermalization erases information about the initial state. This raises a crucial question: How does the thermalizing tendency of a quantum channel constrain its signaling power and vice versa? In this work, we address this question by considering three thermodynamic tasks associated with a quantum channel: the generation, preservation, and transmission of athermality. We provide faithful measures for athermality generation and athermality preservation of quantum channels, and prove that their difference quantifies athermality transmission. Analyzing these thermodynamic tasks, we find that the signaling ability of a quantum channel is upper-bounded by its athermality preservation and lower-bounded by its athermality transmission, thereby establishing a fundamental relationship between signaling and thermodynamic properties of channels for quantum communication. We demonstrate this interplay for the example of the quantum switch, revealing an explicit trade-off between the signaling ability and athermality of the quantum channels it can implement.

Introduction. Structural data accumulated to date indicate that histone amino acid sequence variability, limited and maintained throughout evolution, can, alone or in combination with post-translational modifications, regulate chromatin dynamics, with important functional consequences. However, histones predate chromatin and perform lesser-known functions beyond genome regulation. Aim. Based on an analysis of current publications, we propose a new understanding of histone functions that could potentially provide the basis for significantly improving the treatment of socially significant diseases such as cancer, chronic viral hepatitis, COVID-19, and neuroinfections. Materials and methods. Publications were searched and selected using the PubMed and Google Scholar databases using the following terms: DNA, proteins, histones, peptides, nucleosome, bioinformation. After reviewing the full texts of publications, we identified specific problematic areas in our current understanding of biological information transfer that could be addressed by elucidating the role of histones in implementing genetic functions. Results. Analysis of modern literature reviews and research results allows us to justifiably assign histones a key role – storing and transmitting bioinformation – while simultaneously assigning DNA an extremely important, yet secondary, function – protecting this information. Histones existed before chromatin and perform lesser-known functions beyond genome regulation. Histone sequences have remained virtually unchanged throughout evolution, suggesting that some of their "non-canonical" functions act in parallel or in concert with their genomic regulatory functions. Conclusions. This new understanding of histone functions significantly expands the capabilities of molecular genetics, modern biology, medicine, and bioinformatics. The high efficacy of exogenous natural peptides in medicine, based on their informational interactions with histones rather than with the DNA helix, creates promising scenarios for the treatment of socially significant diseases such as cancer, chronic viral hepatitis, COVID-19, and neuroinfections.

Social familiarity within groups promotes behavioural synchrony and facilitates information transfer. Whether it shapes collective decision-making under predator threat is unknown. Here groups of six medaka (Oryzias latipes) familiarised for one month were used to test whether familiarisation promotes instantaneous collective decision-making in response to a looming stimulus (LS) mimicking a predator attack. First, we analysed behavioural transitions, defined as changes among three behavioural states: high-speed, normal and freezing-like before, during, and after LS in groups of six individuals. Individuals showing high-speed state in response to LS typically tended to shift to freezing-like state afterwards, whereas non-responders were more likely to maintain normal state. Group-level analysis revealed a bimodal distribution in the number of individuals exhibiting freezing-like state, with peaks at zero and six individuals, corresponding to ‘all non-freezing’ and ‘all-freezing’. Clustering analysis further identified three consistent group profiles: ‘freezing-dominant’, ‘non-freezing-dominant’, and ‘mixed-type’ based on behavioural tendencies across 10 trials. In contrast, in unfamiliar groups assembled immediately before testing, the ‘freezing-dominant’ profile was absent, and the distribution in the number of individuals exhibiting freezing-like state shifted to unimodal. In these groups, even at the individual level, responses more often showed a transition from high-speed state to normal state rather than freezing-like state. The results indicate that social familiarity promotes synchronous freezing-like state and consensus decisions under looming threat. Our study presents a behavioural assay for predator-evoked collective decision-making in a genetic model fish, providing a framework for future efforts to link behavioural ethology with neuroscience.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-30656-4.