共找到 20 条结果
Objective: Online patient education materials (OPEMs) are important resources for patients seeking health information. While the National Institutes of Health (NIH) and American Medical Association (AMA) recommend a sixth-grade readability level for OPEMs, commonly available material often exceeds such criteria. Large language models (LLMs), such as ChatGPT and Gemini, have emerged as tools for health education with potential applications in simplification of health material. This study assesses the utility of ChatGPT and Gemini in enhancing the readability of OPEMs for peripheral nerve surgeries. Methods: Eleven common peripheral nerve surgeries were used as online search terms. The first 20 unique search results were assessed; results were excluded if they did not include patient-facing material. ChatGPT and Gemini were instructed to rewrite the text of the OPEM at or below a sixth-grade reading level. Readability metrics were calculated for original OPEMs, alongside ChatGPT and Gemini rewrites. LLM responses were reviewed for accuracy/quality (five-point scale) and comprehensiveness (three-point scale) using predefined criteria. Results: A total of 220 websites were assessed. In total, 155 OPEMs met the inclusion criteria; 65 websites were excluded because they were academic journal articles or other provider-facing materials. The average Flesch-Kincaid grade level (FKGL) of OPEMs was 11.3, significantly greater than the NIH/AMA-sixth grade recommendations (p < 0.001). The average FKGL of ChatGPT rewrites was significantly lower than that of OPEMs (11.3 vs. 7.5, p < 0.001), as was the average FKGL of Gemini rewrites (11.3 vs. 5.6, p < 0.001). ChatGPT rewrites were of higher accuracy/quality (4.5/5.0 vs. 4.0/5.0, p < 0.001) and comprehensiveness (2.0/3.0 vs. 1.0/3.0, p < 0.001) relative to Gemini rewrites. Conclusions: The readability of online patient education materials for peripheral nerve surgery significantly exceeded NIH/AMA recommendations. ChatGPT and Gemini were able to significantly simplify the reading level of these OPEMs. LLMs may serve as tools to improve the readability of peripheral nerve surgery OPEMs.
Mulberry (Morus spp.) includes ecologically important tree species that are highly valued for their exceptional economic and medicinal properties. Among its diverse species, Morus wittiorum and Morus laevigata are particularly valuable genetic resources because of their resistance to Sclerotinia, their relatively high content of specific flavonoids, and elongated fruit morphology. In this study, hybridization experiments were conducted using 10 mulberry accessions spanning three taxonomic sections (Alba, Wittiorum, and Laevigata). All six attempted intersectional crosses successfully yielded hybrid progeny. Using genomic in situ hybridization with blocking DNA, we detected distinct chromosomal signal patterns among the three sections, enabling precise identification of hybrid and wild-type chromosomal constitutions. Notably, this study provides the first documented evidence of 2n gamete formation in the genus Morus, where 2n eggs from M. wittiorum 'W-4' produced a pentaploid hybrid, 'Mp-7'. This discovery not only rewrites the chromosomal inheritance patterns of Morus but also unveils untapped polyploid breeding potential. These findings provide an efficient approach for identifying hybrids and offer novel polyploid breeding strategies, thereby promising to reshape global mulberry breeding and creating new opportunities for the genetic improvement of this agronomically important species.
When we are awake, we pay attention to a specific object in the surrounding world. Feedforward transmission of sensory information is enhanced in the cortico-cortical networks during the inhalation phase of the respiratory cycle for identification and evaluation of sensory information. Memory engrams of the associated scene are recalled by the sensory signal as a search tag. In the mammalian olfactory system, a topographic pattern of activated glomeruli in the olfactory bulb is transferred to the piriform cortex via the anterior olfactory nucleus, and then to higher cognitive areas. The odor map is utilized as a QR code (two-dimensional bar code) for recollection of the associative memory scene. Higher cognitive areas generate imagery of the multisensory cognitive scene, determine the valence of input information, and make behavioral decisions during the exhalation phase of respiration. The cognitive scene information for valence decision is transmitted back to the olfactory cortical areas in the top-down direction through the same set of pyramidal cells as used for the feedforward transmission of sensory information. The top-down information not only directs the output behaviors and generates emotional states but also rewrites the existing memory engrams. Then, How is this attentional switch from the surrounding outer world to the cognitive inner world regulated in a respiration-phase correlated manner? We propose that the basal forebrain inputs to neurogliaform cells in the piriform cortex may play a key role in switching attention by layer-specific blanket inhibition of pyramidal cells.
The sciences divide into those that discover laws and those that reconstruct histories. We argue that this division does not reflect a difference in subject matter, but a difference in epistemic regime. Law-based sciences operate under episodic closure: systems are idealized so that the outcomes of prior interactions do not alter the rules governing future ones. This regime-defining idealization (distinguished from pragmatic idealization) underlies the predictive successes of physics, but creates a systematic blind spot for evolutionary dynamics. We formalize this distinction using Stability-Driven Assembly (SDA), a minimal non-equilibrium framework in which differential persistence couples episodes into population-level evolutionary dynamics without genes, replication, or predefined fitness functions. Representing compositional objects as λ-calculus terms, we show that episodic science studies isolated λ-reductions under fixed rules, while evolutionary science studies populations of λ-instantiations whose outputs re-enter the space of operators. The resulting dynamics are self-modifying and irreducibly sequential: each step rewrites the conditions for the next. A four-quadrant taxonomy locates episodic science, evolutionary science, and two commonly conflated intermediate cases: formal possibility and constructive potential, within a single framework. From this analysis we derive the "No Free Telos" constraint: in constructive systems where population feedback reshapes the effective dynamics at each step, the cost of predicting future states cannot in general be reduced below the cost of simulating the generative history. The resulting framework bridges episodic and historical sciences, not by reducing one to the other, but by identifying population-level memory as the structural condition that transforms law-governed episodes into open-ended evolutionary processes.
The realization of rewritable and customizable electromagnetic illusions fundamentally hinges upon the ability to achieve precise spatiotemporal control over electromagnetic waves. Conventional metasurfaces are confined to globally stationary, periodic protocols, lacking the information entropy to orchestrate complex illusion patterns. Here, we introduce a modular metasurface time-domain programming framework that organizes discrete temporal modulation waveforms as reusable modulation units within a predefined library. By flexibly selecting and sequencing these units, rather than redesigning the entire control law for each new task, the framework redistributes the spectral components of the scattered field to synthesize diverse electromagnetic illusions. A deep generative model is established to map target illusions directly to specific time-domain modulation sequences. The metasurface executes these signals across distinct pulses to physically realize the user-defined illusion. Validated on a synthetic aperture imaging testbed, the system rewrites periodic baselines and synthesizes representative aperiodic illusion patterns under user-specified inputs, achieving high fidelity between intended objectives and measurements (structural similarity index ≥0.91). This work establishes a practical route from target-scene specification to executable metasurface control and provides a scalable paradigm for task-driven wave manipulation in radar imaging scenarios.
Graph-based pangenome references often misrepresent Copy Number Variations (CNVs) and Variable Number Tandem Repeats (VNTRs) as alternative acyclic paths, which hinders downstream analyses, degrades alignment behavior, and reduces interpretability in graph visualizations. For these reasons, we introduce PANPHORTE, a topology-optimization methodology that detects repeat-driven misrepresentations within superbubbles and rewrites them into structures that more faithfully reflect the underlying biology. Given a pangenome graph annotated with haplotype paths, PANPHORTE identifies repetitive elements inside superbubbles, isolates shared repeat sequences across distinct subpaths, and refactors the graph by splitting nodes and introducing explicit cycles, encoding CNVs and VNTRs without loss of information. We provide a C++ command-line implementation of the proposed specifications, and a complementary pipeline that applies PANPHORTE followed by GFAffix to further reduce redundancy in regions not affected by repeat-induced artifacts. We evaluate PANPHORTE on synthetic and real pangenome graphs, showing reductions in memory footprint of up to 71.69%, improvements in exact read matches of up to 34.4%, and substantially clearer visual identification of repeated loci.
Fibrous porous media, such as paper and textiles, are extensively used in point-of-care diagnostics and smart sensors, due to capillarity and bio-compatibility. However, the fluid permeation through such substrates defies the simplicity of classical capillarity, owing to interaction between swelling and pore-scale heterogeneity. We hypothesize that a swelling porous matrix becomes an active participant in fluid permeation through evolving local heterogeneity, scripting emergent pathways of transport, thereby limiting classical models, such as Lucas-Washburn and Darcy's model. In the present study, we investigate the effect of swelling induced evolution of pore scale heterogeneity on macroscopic imbibition patterns. We develop a comprehensive mathematical model incorporating the swelling kinetics of fibres and evolving pore scale heterogeneity to modify Darcy's law, thereby accounting for liquid absorption into swelling fibres. The evolution of local permeability K and porosity φ were obtained using capillary-bundle approach, upon upscaling the evolving underlying Pore Size Distribution (PSD), validated with Pore Network Modelling simulations. The overall theoretical model was validated with the lateral flow imbibition experiments through different fibrous porous substrates. We show that the coupled interplay between evolving pore-scale flow pathways and absorption, driven by localized swelling, impedes the imbibition. We demonstrate that the evolving underlying PSD critically affects the microscopic flow distribution, which significantly affects the slowing down of the imbibition front. Our results demonstrate that the resulting feedback between dynamic morphology and flow redistribution gives rise to distinct wicking modes- Continuous, Interrupted and Termination. By mapping the conditions that toggle between these competing regimes, we thus reveal a universal framework for understanding capillary phenomena in living, swelling, or reactive media, where the flow rewrites the medium as much as the medium guides the flow.
The complement system is traditionally recognized as a major effector of innate immunity, essential for pathogen clearance, inflammation and the maintenance of tissue homeostasis. In recent years, however, its role in cancer has been substantially redefined. Beyond its canonical extracellular activity, complement has emerged as a multifaceted regulator of tumor biology, acting not only within the tumor microenvironment but also intracellularly through the recently described intracellular complement system (complosome). While extracellular complement primarily shapes immune responses and the tumor microenvironment, the complosome directly regulates fundamental cellular processes, including metabolism, proliferation, autophagy, stress responses and cell survival. In this review, we discuss current evidence on the canonical and non-canonical roles of complement in cancer. Importantly, complement signaling exhibits a strong context-dependent duality, exerting either tumor-promoting or tumor-restraining effects depending on the tumor type, disease stage, cellular source, and localization. Taken together, the available evidence indicates that the complosome is not merely an extension of classical complement biology, but a distinct and biologically significant signaling network that rewrites our understanding of complement in cancer. Its growing relevance in tumor development and therapy resistance positions it as a promising target for future mechanistic studies and innovative therapeutic interventions.
After more than a decade of clinical experience with BTK inhibitors, resistance to BTK targeting has become a moving target, shaped by drug-specific BTK mutations, downstream signaling escape, and disease-dependent adaptive programs. The arrival of BTK degraders introduces a mechanistically distinct modality for lymphoid malignancies, but also raises a timely question: does degrading BTK rewrite the rules of resistance, or simply redraw its boundaries?
This qualitative study explores how digitalisation primarily through electronic health records and digital documentation systems is experienced by psychiatric nurses and patients within a state hospital in eastern Turkey, with particular attention to its perceived influence on professional identity, the therapeutic relationship, and ethical responsibilities. References to artificial intelligence in this paper reflect participants' anticipatory perceptions rather than documented routine AI use in this setting. Using a qualitative, phenomenologically informed approach, data were collected from 16 psychiatric nurses and 14 patients in a Turkish state hospital through semi-structured interviews and analysed using Colaizzi's seven-step descriptive phenomenological method. The findings suggest separate themes for nurses and patients, followed by three integrated themes reflecting their shared experiences: 'Identity Under the Pressure of Digitalisation: The Silent Rewriting of the Professional Role,' 'The Fragility of the Therapeutic Relationship in Screen-Mediated Care,' and 'The Digital Trust Paradox: Between Privacy, Surveillance, and Responsibility.' Participants described that digitalisation was associated with increased efficiency and professional visibility, while also being experienced as contributing to more structured and technically oriented care practices, perceived reductions in empathic engagement, and concerns related to trust and privacy. Overall, the findings suggest that digitalisation in psychiatric nursing is experienced as extending beyond technical efficiency to include changes in how professional identity and therapeutic relationships are perceived. Participants described that digital practices may be experienced as introducing more technical and screen-mediated elements into care, which may be perceived as limiting empathic engagement and aspects of the therapeutic relationship. In addition, participants reported concerns related to digital trust, including issues of privacy, surveillance, and responsibility. Specifically, participants described a perceived shift from relational to technical care, a 'digital trust paradox' in which surveillance and accountability coexist with distrust, and a concern that screen-mediated work distances nurses from the humanistic core of their role. These findings highlight the importance of developing context-sensitive and ethically informed approaches to the use of digital systems, rather than assuming widespread or routine use of artificial intelligence in clinical practice.
Prime editing has become a highly programmable and accurate genome-editing platform that can install targeted substitutions, insertions, and deletions without introducing double-strand breaks or requiring a separate donor DNA template. This review summarizes recent developments about prime editing mechanisms, such as knowledge about flap dynamics, repair pathway interactions, and pegRNA architecture, and improvements in engineering, resulting in high-efficiency systems, including PEmax, PE4/5, TWIN-PE, PASTE, and PrimeRoot. Such advances now make prime editing applicable to therapeutic gene correction, agricultural biotechnology, microbial engineering, and functional genomics. However, delivery, chromatin context, mismatch-repair variability, and large-fragment integration remain major barriers to broad application. By comparing prime editing with other genome-editing modalities, this review summarizes its unique advantages and highlights strategic innovations needed for its next stage of development. Together, these developments position prime editing as a highly programmable platform with strong potential to shape the future of precise genome rewriting.
We present mrfmsim, an open-source Python package that facilitates the design, simulation, and analysis of magnetic resonance force microscopy (MRFM) experiments. MRFM is a scanning-probe technique that detects magnetic resonance from nanoscale ensembles of nuclear or electron spins with a force sensor. Because MRFM experiments are complex and operate at sensitivity limits, numerical simulation is essential for designing experiments and estimating per-spin sensitivity and imaging resolution from measured signals. In this paper, we highlight the challenges of developing MRFM simulations and show that software designed to simulate specific experiments only in a rapidly evolving experimental field can yield erroneous results. The mrfmsim package addresses these challenges by supporting post-definition customization without rewriting the internal model and by employing a plugin system for extending functionality. We show that the package's modular, extendable, and readable architecture improves reproducibility and accelerates development.
Clazosentan reduces angiographic vasospasm after aneurysmal subarachnoid hemorrhage (aSAH), but functional benefit may vary across patients. We used causal machine learning to explore heterogeneity and derive an interpretable rule. In a secondary analysis of the RECOVER dataset [multicenter retrospective cohort of aSAH treated by clipping or coiling within 48 h (N = 506)], we compared clazosentan-containing management (with or without fasudil) with fasudil-only prophylaxis. After applying inverse probability of treatment weighting for prespecified confounders [age, World Federation of Neurosurgical Societies (WFNS) grade, Fisher grade, and body mass index (BMI)], we used a causal forest to estimate conditional average treatment effects (CATEs) on favorable discharge outcome (modified Rankin Scale 0-2 at discharge). A policy tree summarized CATEs, and external validation was performed in an independent cohort (N = 181). CATEs were heterogeneous (mean 0.18 ± 0.14). The policy tree split first on BMI (≤ 20.03 kg/m2): patients with BMI ≤ 20.03 and WFNS ≤ 2 showed no clear estimated benefit (mean CATE - 0.058), whereas those with BMI > 20.03 or WFNS > 2 showed higher estimated benefit (CATE 0.24-0.25). In external validation, the same rule identified a subgroup with higher odds of favorable recovery with clazosentan; estimates in the low-benefit subgroup were imprecise (n = 27). In observational cohorts with limited overlap in treatment assignment, causal machine learning suggested heterogeneity in the estimated association of a clazosentan-containing strategy with discharge outcomes and produced a simple BMI/WFNS policy tree. These findings are hypothesis-generating and require prospective validation including safety endpoints and longer-term functional outcomes.
暂无摘要（点击查看详情）
Youth addiction often unfolds within landscapes of neglect, yet adult accounts of these histories are commonly gathered through one-off interviews or clinical assessments. This study examined how adults in stable recovery narrate adolescent alcohol and other drug use and associated neglect through handwritten diary-style writing, and what such writing contributes methodologically to qualitative inquiry across time. This paper reports a secondary analysis of community-generated qualitative materials produced through the SIDINL peer-support and mental health recovery network. The available corpus comprised n = 14 handwritten diary-style texts and then participants took part in a participant-led co-reading conversation. Four cases (n = 4) were selected for in-depth vignette-based analysis based on explicit consent for secondary analysis and quotation, sufficient narrative density/legibility of written material, completion of co-reading discussion, and feasibility of de-identification. Data were analyzed using case-centered narrative summaries and reflexive thematic analysis, attending to both content and material features of handwriting. The analysis foregrounded three recurring patterns. (1) "No one was watching": participants described moving through unsupervised spaces where adults were absent or silent; substance use was framed as both relief and proof of invisibility, and neglect appeared as both wound and perceived freedom from scrutiny. (2) "My body on the page": writers portrayed the body as a site of self-neglect and communication, describing hunger, injury, dirt, ignored symptoms, and hygiene or clothing as shields that kept others away or signaled distress that others did not read. (3) "Writing from after": letter and then/now formats staged dialogue between youth and adult selves, redistributing responsibility for neglect across families, institutions, and self while also acknowledging harms caused during use. Handwritten diary-style writing, paired with participant-led co-reading, generated temporally layered narratives of youth addiction and neglect that extend beyond single interview recall. The approach positions writing as an active practice of identity reconstruction in recovery and offers a practical method for qualitative substance-use research where control over disclosure and careful attention to shame, stigma, and omission of care are essential.
Nuclear magnetic resonance (NMR) spectra are often complicated by overlapping signals from heterogeneous interactions. Multidimensional NMR is used to separate signals from different interactions and improve resolution. If the heterogeneous interactions are refocusable, windowed Carr-Purcell-Meiboom-Gill (CPMG) detection can provide signal enhancement; however, it has previously not been straightforward to combine multidimensional NMR with windowed CPMG detection, particularly when split-t1 or delayed acquisition is used. Here, we use generalized hypercomplex acquisition schemes to restore valid phase encoding. It is not necessary to control (or even consider) the details of coherence scrambling during CPMG pulse trains. Instead, it is sufficient to treat 2D NMR experiments with CPMG detection as if they were phase-sensitive 3D experiments. Our schemes are not unique; other phase-cycling schemes can yield equivalent results. Nevertheless, our algorithms are general and may be applied without rewriting the base phase cycle of the pulse sequence. We highlight two examples: (1) removal of heterogeneous broadening from water-exchange experiments in a nonuniform field and (2) I = 3/2 87Rb 3QMAS CPMG of RbNO3.
Epigenetic modifications furnish a hidden regulatory layer that shapes cellular fate and evolutionary potential without rewriting the genetic code. In eukaryotes, methylome maps have profoundly transformed our understanding of development, disease, and lineage diversification. In bacteria, which represent the most abundant and ecologically versatile forms of life, the epigenome remains a largely uncharted dimension. To enable population-scale comparison of bacterial methylomes, we develop a principled strategy to prioritize methylation systems that are enzymatically encoded, broadly conserved and phylogenetically informative, thereby defining a stable substrate for quantitative comparative analysis. We reconstruct the first population-scale bacterial methylation-informed phylogenies that broadly recapitulate sequence-based relationships while resolving epi-phylogroups associated with GC content and environmental stress resilience. We introduce a three-metric quantitative framework (MPK, MR, and MFR) that converts site-level methylation calls into standardized, cross-sample comparable quantitative traits, enabling robust identification of highly methylated core genes from as few as 30 Escherichia coli strains. Finally, co-methylation network analysis identifies virulence-enriched modules and coordinated methylation of horizontally acquired virulence loci, providing the first evidence that horizontally acquired virulence loci are epigenetically assimilated into host regulatory circuitry. Together, this framework enables locus-resolved, population-scale integration of bacterial methylation data to interrogate epigenetic contributions to evolution, fitness and pathogenicity.
Background: Healthcare-associated bloodstream infections (HABSIs) are among the main categories of nosocomial infections. This analysis aims to identify the clinical characteristics of patients in the emergency department (ED) who will develop a HABSI during their hospital stay. Methods: Main outcome measures were HABSI and the cumulative survival rate at 30 days. The features tested in a logistic model were age, sex, vitals by the National Early Warning Score (NEWS), priority levels, main complaints, comorbidities by the Charlson Comorbidity Index (CCI), trauma-related disease, main diagnosis and ED length of stay. Results: In 414 (2.3%) out of 18,304 patients, aged 75 (16) years, mean (SD), a diagnosis of HABSI was recorded. HABSIs occurred in subjects with main diagnosis of diseases of the respiratory system (N = 116; 28.0%), digestive system (N = 72; 17.4%), and circulatory system (N = 68; 16.4%). The main key clinical features selected by the logistic model were: NEWS > 6, diagnosis of neoplasms, CCI > 4, and diagnosis of diseases of the digestive system. The ROC curve for the HABSI risk score was 0.703 ± 0.027 in predicting the outcome, (sensitivity 79%, specificity 51%, at optimal cut-off score). The overall hazard mortality risk was twofold higher in patients with HABSIs (hazard ratio: 2.319; 95% confidence interval: 1.871-2.875; p-value: <0.001). The overall 30-day survival rate was lower among patients with HABSIs (33%) vs. non-HABSI patients (62%). Conclusions: A group of main clinical features in subjects without suspect of infectious disease in the ED are associated with HABSIs. These features negatively impact survival rate during hospital stays.