Induction of lung progenitor cell-like organoids by porcine pluripotent stem cells.

Organoids are in vitro 3D models that are generated using stem cells to study organ development and regeneration. Despite the extensive research on lung organoids, there is limited information on pig lung cell generation or development. Here, we identified five epithelial cell types along with their characteristic markers using scRNA-seq. Additionally, we found that NKX2.1 and FOXA2 acted as the crucial core transcription factors in porcine lung development. The presence of SOX9/SOX2 double-positive cells was identified as a key marker for lung progenitor cells. The Monocle algorithm was used to create a pseudo-temporal differentiation trajectory of epithelial cells, leading to the identification of signaling pathways related to porcine lung development. Moreover, we established the differentiation method from porcine pluripotent stem cells (pPSCs) to SOX17+ FOXA2+ definitive endoderm (DE) and NKX2.1+ FOXA2+ CDX2- anterior foregut endoderm (AFE). The AFE is further differentiated into lung organoids while closely monitoring the differentiation process. We showed that NKX2.1 overexpression facilitated the induction of lung organoids and supported subsequent lung differentiation and maturation. This model offers valuable insights into studying the interaction patterns between cells and the signaling pathways during the development of the porcine lung.

Human striatal organoids derived from pluripotent stem cells recapitulate striatal development and compartments.

The striatum links neuronal circuits in the human brain, and its malfunction causes neuronal disorders such as Huntington's disease (HD). A human striatum model that recapitulates fetal striatal development is vital to decoding the pathogenesis of striatum-related neurological disorders and developing therapeutic strategies. Here, we developed a method to construct human striatal organoids (hStrOs) from human pluripotent stem cells (hPSCs), including hStrOs-derived assembloids. Our hStrOs partially replicated the fetal striatum and formed striosome and matrix-like compartments in vitro. Single-cell RNA sequencing revealed distinct striatal lineages in hStrOs, diverging from dorsal forebrain fate. Using hStrOs-derived assembloids, we replicated the striatal targeting projections from different brain parts. Furthermore, hStrOs can serve as hosts for striatal neuronal allografts to test allograft neuronal survival and functional integration. Our hStrOs are suitable for studying striatal development and related disorders, characterizing the neural circuitry between different brain regions, and testing therapeutic strategies.

Functionalized 2D membranes for separations at the 1-nm scale.

The ongoing evolution of two-dimensional (2D) material-based membranes has prompted the realization of mass separations at the 1-nm scale due to their well-defined selective nano- and subnanochannels. Strategic membrane functionalization is further found to be key to augmenting channel accuracy and efficiency in distinguishing ions, gases and molecules within this range and is thus trending as a research focus in energy-, resource-, environment- and pharmaceutical-related applications. In this review, we present the fundamentals underpinning functionalized 2D membranes in various separations, elucidating the critical "method-interaction-property" relationship. Starting with an introduction to various functionalization strategies, we focus our discussion on functionalization-induced channel-species interactions and reveal how they shape the transport- and operation-related features of the membrane in different scenarios. We also highlight the limitations and challenges of current functionalized 2D membranes and outline the necessary breakthroughs needed to apply them as reliable and high-performance separation units across industries in the future.

DNA-Mediated Magnetic-Dimer Assembly for Fault-Free Ultra-High-Field Magnetic Resonance Imaging of Tumors.

Ultra-high-field (UHF) magnetic resonance imaging (MRI) stands as a pivotal cornerstone in biomedical imaging, yet the challenge of false imaging persists, constraining its full potential. Despite the development of dual-mode contrast agents improving conventional MRI, their effectiveness in UHF remains suboptimal due to the high magnetic moment, resulting in diminished T1 relaxivity and excessively enhanced T2 relaxivity. Herein, we report a DNA-mediated magnetic-dimer assembly (DMA) of iron oxide nanoparticles that harnesses UHF-tailored nanomagnetism for fault-free UHF-MRI. DMA exhibits a dually enhanced longitudinal relaxivity of 4.42 mM-1·s-1 and transverse relaxivity of 26.23 mM-1·s-1 at 9 T, demonstrating a typical T1-T2 dual-mode UHF-MRI contrast agent. Importantly, DMA leverages T1-T2 dual-modality image fusion to achieve artifact-free breast cancer visualization, effectively filtering interference from hundred-micrometer-level false-positive signals with unprecedented precision. The UHF-tailored T1-T2 dual-mode DMA contrast agents hold promise for elevating the accuracy of MR imaging in disease diagnosis.

The Ycx1 protein encoded by the yeast YDL206W gene plays a role in calcium and calcineurin signaling.

Calcium is ubiquitously present in all living cells and plays important regulatory roles in a wide variety of biological processes. In yeast, many effects of calcium are mediated via the action of calcineurin, a calcium/calmodulin-dependent protein phosphatase. Proper signaling of calcium and calcineurin is important in yeast, and the calcineurin pathway has emerged as a valuable target for developing novel antifungal drugs. Here, we report a role of YDL206W in calcium and calcineurin signaling in yeast. YDL206W is an uncharacterized gene in yeast, encoding a protein with two sodium/calcium exchange domains. Disrupting the YDL206W gene leads to a diminished level of calcium-induced activation of calcineurin and a reduced accumulation of cytosolic calcium. Consistent with a role of calcineurin in regulating pheromone and cell wall integrity signaling, the ydl206wΔ mutants display an enhanced growth arrest induced by pheromone treatment and poor growth at elevated temperature. Subcellular localization studies indicate that YDL206W is localized in endoplasmic reticulum and Golgi. Together, our results reveal YDL206W as a new regulator for calcineurin signaling in yeast and suggest a role of the endoplasmic reticulum and Golgi in regulating cytosolic calcium in yeast.

StMLP1, as a Kunitz trypsin inhibitor, enhances potato resistance and specifically expresses in vascular bundles during Ralstonia solanacearum infection.

Miraculin-like proteins (MLPs), members of the Kunitz trypsin inhibitor (KTI) family that are present in various plants, have been discovered to have a role in defending plants against pathogens. In this study, we identified a gene StMLP1 in potato that belongs to the KTI family. We found that the expression of StMLP1 gradually increases during Ralstonia solanacearum (R. solanacearum) infection. We characterized the promoter of StMLP1 as an inducible promoter that can be triggered by R. solanacearum and as a tissue-specific promoter with specificity for vascular bundle expression. Our findings demonstrate that StMLP1 exhibits trypsin inhibitor activity, and that its signal peptide is essential for proper localization and function. Overexpression of StMLP1 in potato can enhance the resistance to R. solanacearum. Inhibiting the expression of StMLP1 during infection accelerated the infection by R. solanacearum to a certain extent. In addition, the RNA-seq results of the overexpression-StMLP1 lines indicated that StMLP1 was involved in potato immunity. All these findings in our study reveal that StMLP1 functions as a positive regulator that is induced and specifically expressed in vascular bundles in response to R. solanacearum infection.

Mapping morphological cortical networks with joint probability distributions from multiple morphological features.

Morphological features sourced from structural magnetic resonance imaging can be used to infer human brain connectivity. Although integrating different morphological features may theoretically be beneficial for obtaining more precise morphological connectivity networks (MCNs), the empirical evidence to support this supposition is scarce. Moreover, the incorporation of different morphological features remains an open question. In this study, we proposed a method to construct cortical MCNs based on multiple morphological features. Specifically, we adopted a multi-dimensional kernel density estimation algorithm to fit regional joint probability distributions (PDs) from different combinations of four morphological features, and estimated inter-regional similarity in the joint PDs via Jensen-Shannon divergence. We evaluated the method by comparing the resultant MCNs with those built based on different single morphological features in terms of topological organization, test-retest reliability, biological plausibility, and behavioral and cognitive relevance. We found that, compared to MCNs built based on different single morphological features, MCNs derived from multiple morphological features displayed less segregated, but more integrated network architecture and different hubs, had higher test-retest reliability, encompassed larger proportions of inter-hemispheric edges and edges between brain regions within the same cytoarchitectonic class, and explained more inter-individual variance in behavior and cognition. These findings were largely reproducible when different brain atlases were used for cortical parcellation. Further analysis of macaque MCNs revealed weak, but significant correlations with axonal connectivity from tract-tracing, independent of the number of morphological features. Altogether, this paper proposes a new method for integrating different morphological features, which will be beneficial for constructing MCNs.

Silver Surface-Assisted Dehydrobrominative Cross-Coupling between Identical Aryl Bromides.

Cross-coupling reactions represent an indispensable tool in chemical synthesis. An intriguing challenge in this field is to achieve selective cross-coupling between two precursors with similar reactivity or, to the limit, the identical molecules. Here we report an unexpected dehydrobrominative cross-coupling between 1,3,5-tris(2-bromophenyl)benzene molecules on silver surfaces. Using scanning tunneling microscopy, we examine the reaction process at the single-molecular level, quantify the selectivity of the dehydrobrominative cross-coupling, and reveal the modulation of selectivity by substrate lattice-related catalytic activity or molecular assembly effect. Theoretical calculations indicate that the dehydrobrominative cross-coupling proceeds via regioselective C-H bond activation of debrominated TBPB and subsequent highly selective C-C coupling of the radical-based intermediates. The reaction kinetics plays an important role in the selectivity for the cross-coupling. This work not only expands the toolbox for chemical synthesis but also provides important mechanistic insights into the selectivity of coupling reactions on the surface.

Comparative analysis of sleep parameters and structures derived from wearable flexible electrode sleep patches and polysomnography in young adults.

Polysomnography (PSG) is the gold standard for clinical sleep monitoring, but its cost, discomfort, and limited suitability for continuous use present challenges. The flexible electrode sleep patch (FESP) emerges as an economically viable and patient-friendly solution, offering lightweight, simple operation, and self-applicable. Nevertheless, its utilization in young individuals remains uncertain. The objective of this study was to compare sleep data obtained by FESP and PSG in healthy young individuals and analyze agreement for sleep parameters and structure classification. Overnight monitoring with FESP and PSG recordings in 48 participants (mean age: 23 yr) was done. Correlation analysis, Bland-Altman plots, and Cohen's kappa coefficient assessed consistency. Sensitivity, specificity, and predictive values compared classification against PSG. FESP showed strong correlation and consistency with PSG for sleep monitoring. Bland-Altman plots indicated small errors and high consistency. Kappa values (0.70-0.84) suggested substantial agreement for sleep stage classification. Pearson correlation coefficient values for sleep stages (0.75-0.88) and sleep parameters (0.80-0.96) confirm that FESP has a strong application. Intraclass correlation coefficient yielded values between 0.65 and 0.97. In addition, FESP demonstrated an impressive accuracy range of 84.12-93.47% for sleep stage classification. The FESP also features a wearable self-test program with an error rate of no more than 8% for both deep sleep and wake. In young adults, FESP demonstrated reliable monitoring capabilities comparable to PSG. With its low cost and user-friendly design, FESP is a potential alternative for portable sleep assessment in clinical and research applications. Further studies involving larger populations are needed to validate its diagnostic potential.NEW & NOTEWORTHY By comparison with PSG, this study confirmed the reliability of an efficient, objective, low-cost, and noninvasive portable automatic sleep-monitoring device FESP, which provides effective information for long-term family sleep disorder diagnosis and sleep quality monitoring.

Supramolecular Polyurethane "Ligaments" Enabling Room-Temperature Self-Healing Flexible Perovskite Solar Cells and Mini-Modules.

Flexible perovskite solar cells (F-PSCs) have emerged as promising alternatives to conventional silicon solar cells for applications in portable and wearable electronics. However, the mechanical stability of inherently brittle perovskite, due to residual lattice stress and ductile fracture formation, poses significant challenges to the long-term photovoltaic performance and device lifetime. In this paper, to address this issue, a dynamic "ligament" composed of supramolecular poly(dimethylsiloxane) polyurethane (DSSP-PPU) is introduced into the grain boundaries of the PSCs, facilitating the release of residual stress and softening of the grain boundaries. Remarkably, this dynamic "ligament" exhibits excellent self-healing properties and enables the healing of cracks in perovskite films at room temperature. The obtained PSCs have achieved power conversion efficiencies of 23.73% and 22.24% for rigid substrates and flexible substrates, respectively, also 17.32% for flexible mini-modules. Notably, the F-PSCs retain nearly 80% of their initial efficiency even after subjecting the F-PSCs to 8000 bending cycles (r = 2 mm), which can further recover to almost 90% of the initial efficiency through the self-healing process. This remarkable improvement in device stability and longevity holds great promise for extending the overall lifetime of F-PSCs.

A Self-Assembled 3D/0D Quasi-Core-Shell Structure as Internal Encapsulation Layer for Stable and Efficient FAPbI3 Perovskite Solar Cells and Modules.

FAPbI3 perovskites have garnered considerable interest owing to their outstanding thermal stability, along with near-theoretical bandgap and efficiency. However, their inherent phase instability presents a substantial challenge to the long-term stability of devices. Herein, this issue through a dual-strategy of self-assembly 3D/0D quasi-core-shell structure is tackled as an internal encapsulation layer, and in situ introduction of excess PbI2 for surface and grain boundary defects passivating, therefore preventing moisture intrusion into FAPbI3 perovskite films. By utilizing this method alone, not only enhances the stability of the FAPbI3 film but also effectively passivates defects and minimizes non-radiative recombination, ultimately yielding a champion device efficiency of 23.23%. Furthermore, the devices own better moisture resistance, exhibiting a T80 lifetime exceeding 3500 h at 40% relative humidity (RH). Meanwhile, a 19.51% PCE of mini-module (5 × 5 cm2) is demonstrated. This research offers valuable insights and directions for the advancement of stable and highly efficient FAPbI3 perovskite solar cells.

Cluster-in-Molecule Local Correlation Method for Dispersion Interactions in Large Systems and Periodic Systems.

ConspectusThe noncovalent interactions, including dispersion interactions, control the structures and stabilities of complex chemical systems, including host-guest complexes and the adsorption process of molecules on the solid surfaces. The density functional theory (DFT) with empirical dispersion correction is now the working horse in many areas of applications. Post-Hartree-Fock (post-HF) methods have been well recognized to provide more accurate descriptions in a systematic way. However, traditional post-HF methods are mainly limited to small- or medium-sized systems, and their applications to periodic condensed phase systems are still very limited due to their expensive computational costs.To extend post-HF calculations to large molecules, the cluster-in-molecule (CIM) local correlation approach has been established, allowing highly accurate electron correlation calculations that are routinely available for very large systems. In the CIM approach, the electron correlation energy of a large molecule could be obtained from electron correlation calculations on a series of clusters, each of which contains a subset of occupied and virtual localized molecular orbitals. The CIM method could be massively and efficiently parallelized on general computer clusters. The CIM method has been implemented at various electron correlation levels, including second-order MoÌ·ller-Plesset perturbation theory (MP2), coupled cluster singles and doubles (CCSD), CCSD with perturbative triples correction [CCSD(T)], etc. The CIM-MP2 energy gradient algorithm was developed and applied to the geometry optimizations of large systems. The CIM method has also been extended to condensed-phase systems under periodic boundary conditions (PBC-CIM). For periodic systems, the correlation energy per unit cell could be evaluated with correlation energy contributions from a series of clusters that are built with localized Wannier functions.CIM-based electron correlation calculations have been employed to investigate a number of chemical problems in which the dispersion interaction is important. CIM-based post-HF methods including CIM domain-based local pair natural orbital (DLPNO) CCSD(T) are applied to compute the relative or binding energies of biological systems or supramolecular complexes, the reaction barrier in a relatively complex chemical reaction. The CIM-MP2 method is used to obtain the optimized geometry of large systems. CIM-based post-HF calculations have also been used to compute the cohesive energies of molecular crystals and adsorption energies of molecules on the solid surfaces. The CIM and its PBC variant are expected to become a powerful theoretical tool for accurate calculations of the energies and structures for a broad range of large systems and condensed-phase systems with significant dispersion interactions.

Identification of candidate genes for adult plant stripe rust resistance transferred from Aegilops ventricosa 2NvS into wheat via fine mapping and transcriptome analysis.

KEY MESSAGE: An adult plant gene for resistance to stripe rust was narrowed down to the proximal one-third of the 2NvS segment translocated from Aegilops ventricosa to wheat chromosome arm 2AS, and based on the gene expression analysis, two candidate genes were identified showing a stronger response at the adult plant stage compared to the seedling stage. The 2NvS translocation from Aegilops ventricosa, known for its resistance to various diseases, has been pivotal in global wheat breeding for more than three decades. Here, we identified an adult plant resistance (APR) gene in the 2NvS segment in wheat line K13-868. Through fine mapping in a segregating near-isogenic line (NIL) derived population of 6389 plants, the candidate region for the APR gene was narrowed down to between 19.36 Mb and 33 Mb in the Jagger reference genome. Transcriptome analysis in NILs strongly suggested that this APR gene conferred resistance to stripe rust by triggering plant innate immune responses. Based on the gene expression analysis, two disease resistance-associated genes within the candidate region, TraesJAG2A03G00588940 and TraesJAG2A03G00590140, exhibited a stronger response to Puccinia striiformis f. sp. tritici (Pst) infection at the adult plant stage than at the seedling stage, indicating that they could be potential candidates for the resistance gene. Additionally, we developed a co-dominant InDel marker, InDel_31.05, for detecting this APR gene. Applying this marker showed that over one-half of the wheat varieties approved in 2021 and 2022 in Sichuan province, China, carry this gene. Agronomic trait evaluation of NILs indicated that the 2NvS segment effectively mitigated the negative effects of stripe rust on yield without affecting other important agronomic traits. This study provided valuable insights for cloning and breeding through the utilization of the APR gene present in the 2NvS segment.

A crowdsourcing open platform for literature curation in UniProt.

The UniProt knowledgebase is a public database for protein sequence and function, covering the tree of life and over 220 million protein entries. Now, the whole community can use a new crowdsourcing annotation system to help scale up UniProt curation and receive proper attribution for their biocuration work.

Novel protein C6ORF120 promotes liver fibrosis by activating hepatic stellate cells through the PI3K/Akt/mTOR pathway.

BACKGROUND AND AIM: The role of C6ORF120 in promoting CCL4-induced hepatic fibrosis and its possible mechanisms were explored in C6orf120 knockout rats (C6orf120-/-) and LX-2 cells (a type of human hepatic stellate cell line). METHODS: In vivo experiments, wild-type and C6orf120-/- rats were used to investigate the function of C6ORF120. In the in vitro experiments, C6ORF120 recombinant protein (rC6ORF120) at a concentration of 200 ng/mL was used to stimulate LX-2 cells. Sirius Red staining, Masson staining, western blotting, polymerase chain reaction, immunohistochemistry, and immunofluorescence were used to explore fibrosis-associated factors. RESULTS: C6orf120-/- rats showed mild fibrosis and liver injury in the CCL4-induced liver fibrosis model. Furthermore, RNA-seq revealed that C6orf120-/- rats had less extracellular matrix deposition and activated stellate cells. Consistent with the in vivo, the rC6ORF120 induced LX-2 cell activation. Moreover, mechanistic studies revealed that the p-PI3K/PI3K, p-Akt/Akt, and p-mTOR/mTOR levels were significantly elevated and LY294002 (a PI3K/Akt/mTOR typical pathway inhibitor) reversed the function of C6ORF120 in activating LX-2 cells. CONCLUSION: C6ORF120 could activate hepatic stellate cells and promote hepatic fibrosis via the PI3K/Akt/mTOR signaling pathway.

Quantifying uncertainty: Air quality forecasting based on dynamic spatial-temporal denoising diffusion probabilistic model.

Air pollution constitutes a substantial peril to human health, thereby catalyzing the evolution of an array of air quality prediction models. These models span from mechanistic and statistical strategies to machine learning methodologies. The burgeoning field of deep learning has given rise to a plethora of advanced models, which have demonstrated commendable performance. However, previous investigations have overlooked the salience of quantifying prediction uncertainties and potential future interconnections among air monitoring stations. Moreover, prior research typically utilized static predetermined spatial relationships, neglecting dynamic dependencies. To address these limitations, we propose a model named Dynamic Spatial-Temporal Denoising Diffusion Probabilistic Model (DST-DDPM) for air quality prediction. Our model is underpinned by the renowned denoising diffusion model, aiding us in discerning indeterminacy. In order to encapsulate dynamic patterns, we design a dynamic context encoder to generate dynamic adjacency matrices, whilst maintaining static spatial information. Furthermore, we incorporate a spatial-temporal denoising model to concurrently learn both spatial and temporal dependencies. Authenticating our model's performance using a real-world dataset collected in Beijing, the outcomes indicate that our model eclipses other baseline models in terms of both short-term and long-term predictions by 1.36% and 11.62% respectively. Finally, we conduct a case study to exhibit our model's capacity to quantify uncertainties.

A multisystem model for understanding stress and adaptation in ethnically and racially diverse youth.

Contemporary biological and contextually based theoretical frameworks have conceptualized how stress exposure may influence adaptation in youth. However, nearly all of this scholarship neglects the role of specific contextual features and/or biological processes that are involved in ethnic-racial minority youth's responses and adaptation to sociocultural stressors. Drawing on the theoretical principles of the developmental psychopathology framework and contemporary models of stress and adaptation, this article proposes a new multisystem model that explains how multiple levels and systems within and outside of individual youth influence their sociocultural adaptation. We provide empirical evidence to support components of this multisystem model. We propose that research based on our new theoretical framework will capture the sociocultural experiences of ethnic-racial minority youth by centering processes that are relevant to their lived experiences, coping, and adjustment. In doing so, this model will inform psychosocial interventions focused on promoting healthy adaptation among ethnic and racial diverse youth. Finally, we offer recommendations to guide future research on stress and adaptation among ethnic and racial diverse youth, in particular, and developmental psychopathology more broadly.

Effects of adding low-dose esketamine to sufentanil and propofol sedation during cervical conization: a single-centre, randomized controlled trial.

BACKGROUND: Cervical conization is a brief but painful procedure that can be performed under sufficient sedation with propofol and opioids. However, this sedation approach comes with a high risk of sedation-related adverse events (SRAEs). Esketamine, an N-methyl-d-aspartate (NMDA) receptor antagonist, causes less cardiorespiratory depression than opioids. The aim of this study was to assess the efficacy and safety of adding a low dose of esketamine to propofol and sufentanil sedation as an opioid-reduced regimen. METHODS: A total of 122 consecutive patients with ASA I-II, body mass index < 30, and STOP-BANG score < 3 who underwent cervical conization were enrolled and randomly divided into Group S and Group ES. Using a closed-loop target-controlled infusion (TCI) pump with a target bispectral index (BIS) value of 60 ± 5, patients in Group S were sedated with 0.2 mcg·kg-1 sufentanil and propofol, while patients in Group ES were sedated with 0.15 mg·kg-1 esketamine, 0.1 mcg·kg-1 sufentanil and propofol. The primary outcome was the incidence and severity of SRAEs, while the secondary outcomes included effectiveness of sedation, awakening time, psychotomimetic side effects, postoperative pain, postoperative nausea and vomiting, and patient and gynaecologist satisfaction. RESULTS: Data from 120 patients were analysed. The incidence of composite SRAEs was significantly higher in Group S than in Group ES (85.0% vs. 56.7%, P < 0.05). Furthermore, the severity of SRAEs was higher in Group S than in Group ES (P < 0.001). There were no significant differences in the effectiveness of sedation, awakening time, psychotomimetic side effects, postoperative pain, postoperative nausea and vomiting, or patient and gynaecologist satisfaction between the two groups. CONCLUSION: Adding low-dose esketamine to propofol and sufentanil sedation reduces the incidence and severity of SRAEs in patients undergoing cervical conization, with equal sedation efficacy, recovery quality, and no additional psychomimetic side effects. TRIAL REGISTRATION: ChiCTR2000040457 , 28/11/2020.

Biofilm formation of Hafnia paralvei induced by c-di-GMP through facilitating bcsB gene expression promotes spoilage of Yellow River carp (Cyprinus carpio).

Hafnia paralvei, a Gram-negative foodborne pathogen, is found ubiquitously in various aquatic animals and seafoods, which can form biofilm as a dominant virulence factor that contributes to its pathogenesis. However, the biofilm formation mechanism of H. paralvei and its effect on food spoilage has not been fully characterized. Here we show that biofilm formation, is regulated by c-di-GMP which mediated by bcsB, can increase the spoilage ability of H. paralvei. We found that GTP was added exogenously to enhance the synthesis of c-di-GMP, which further promoted biofilm formation. The gene dgcC, one of 11 genes encoding GGDEF domain-containing proteins in H. paralvei, was significantly upregulated with GTP as substrate. The upregulation of dgcC contributes to a significant increase of c-di-GMP and the formation of biofilm. In addition, the overexpression of dgcC induced upregulation of bcsB, a reported effector protein encoding gene, which was further demonstrated that overexpression of bcsB can encourage the synthesis of bacterial cellulose and biofilm formation. The effect of biofilm formation induced by c-di-GMP on spoilage of Yellow River carp (Cyprinus carpio) was evaluated by sensory evaluation, the total viable count, and the total volatile basic nitrogen, which showed that biofilm formation can significantly increase the spoilage ability of H. paralvei on C. carpio. Our findings provide the regulation of c-di-GMP on expression of bcsB, that can contribute to biofilm formation and spoilage ability of H. paralvei, which is favor to understanding the pathogenesis of Hafnia paralvei and its role in food spoilage.

Cardiac Multi-Frequency Vibration Signal Sensor Module and Feature Extraction Method Based on Vibration Modeling.

Cardiovascular diseases pose a long-term risk to human health. This study focuses on the rich-spectrum mechanical vibrations generated during cardiac activity. By combining Fourier series theory, we propose a multi-frequency vibration model for the heart, decomposing cardiac vibration into frequency bands and establishing a systematic interpretation for detecting multi-frequency cardiac vibrations. Based on this, we develop a small multi-frequency vibration sensor module based on flexible polyvinylidene fluoride (PVDF) films, which is capable of synchronously collecting ultra-low-frequency seismocardiography (ULF-SCG), seismocardiography (SCG), and phonocardiography (PCG) signals with high sensitivity. Comparative experiments validate the sensor's performance and we further develop an algorithm framework for feature extraction based on 1D-CNN models, achieving continuous recognition of multiple vibration features. Testing shows that the recognition coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) of the 8 features are 0.95, 2.18 ms, and 4.89 ms, respectively, with an average prediction speed of 60.18 us/point, meeting the re-quirements for online monitoring while ensuring accuracy in extracting multiple feature points. Finally, integrating the vibration model, sensor, and feature extraction algorithm, we propose a dynamic monitoring system for multi-frequency cardiac vibration, which can be applied to portable monitoring devices for daily dynamic cardiac monitoring, providing a new approach for the early diagnosis and prevention of cardiovascular diseases.