DNA extraction is a critical prerequisite for reliable downstream analyses such as Polymerase Chain Reaction (PCR), sequencing, and genotyping. Conventional methods often require labor-intensive protocols, large sample volumes, or costly automation. Microfluidic approaches offer an alternative by reducing reagent consumption and enabling faster, more integrated workflows. Here, we present a passive lab-on-a-chip device that performs DNA extraction from complex biological media and enables subsequent on-chip single-molecule analysis. The chip integrates a magnetophoresis-based solid-phase extraction module with a fluorescence detection section capable of quantifying DNA molecules in microchannels and visualizing stretched molecules in nanochannels. The multi-level micro/nanofluidic architecture is fabricated in polymer using a single-step nanoimprinting process with a total manufacturing time of two minutes per chip, enabling scalable production. As a proof of concept, the device extracted DNA from samples spiked into buffer or plasma. On-chip transfer efficiency of DNA-bead complexes to the elution buffer reached 86%, and quantitative analysis of the recovered liquid showed an overall extraction efficiency of 40% (including DNA recovery off-chip), with intact 48 kbp DNA confirmed in both micro- and nanochannel measurements. This platform offers a promising foundation for point-of-care and point-of-interest applications, where integrated DNA extraction and analysis can reduce sample loss and support streamlined, automated workflows.
Glioblastoma (GBM) is one of the most aggressive human cancers, with therapeutic failure driven by pronounced intratumoral heterogeneity, microenvironmental plasticity, immune suppression, blood-brain barrier (BBB)-related pharmacological constraints, and adaptive resistance mechanisms. A major limitation in GBM research is the lack of a human-relevant experimental system able to reproduce these dynamic features while generating interpretable, multimodal datasets. In this context, we propose a testable organ-on-chip (OoC)-extracellular vesicle (EV)-deep learning (DL) framework in which patient-derived GBM cells, endothelial cells, astrocytes, pericytes, stromal cells, and immune components are organized within perfused microphysiological systems. EVs are selectively and temporally harvested from defined compartments, and imaging, barrier-function, sensor, and EV-cargo data are integrated through modality-specific and multimodal DL architectures. This framework is intended not as an immediately validated clinical tool but as an experimental roadmap for linking EV-mediated communication to measurable phenotypes such as BBB disruption, invasion, immune reprogramming, and drug response. We critically discuss the technical requirements of BBB-on-chip systems, EV source attribution, immune-component integration, DL model selection, data scarcity, overfitting, batch effects, domain shift, regulatory barriers, cost, throughput, and reproducibility. By repositioning OoC-EV-DL integration as a staged translational strategy rather than a clinically established solution, this work aims to define a realistic and biologically grounded route for advancing precision oncology in GBM.
Brain-on-a-chip (BOC) refers to a miniaturized in vitro platform that integrates living neuronal networks on a micro-engineered chip, enabling the simulation of brain functions, neural activities and physiological responses. BOC technology is an advanced evolution of microphysiological systems (MPS) and Lab-on-a-Chip platforms, providing novel paradigms for in vitro modeling and exploring early-stage biocomputing by interfacing living neural networks with engineered electronics. Microelectrode arrays (MEAs) serve as the critical physical interface for bidirectional communication in these systems. In this review, we systematically examine the technological landscape and engineering requirements of MEAs tailored for BOC applications, evaluating them across electrical characteristics, structural properties, and biocompatibility. Two primary classes of current MEA technologies, including planar arrays for 2D neural cultures and 3D flexible arrays for brain organoids, are discussed in detail. We highlight the transition from passive planar electrodes to high-density active CMOS and TFT-based arrays, and detail how 3D flexible MEAs utilize endogenous integration and exogenous wrapping strategies to overcome tissue-mechanics mismatches. Furthermore, the integration of MEAs with microfluidics, optoelectronics, and electrochemical sensors to enable multimodal monitoring is explored. With the advantages of the various MEAs, the application of MEAs for BOC, particularly in biological computing and network plasticity research, is discussed. Finally, future technological developments in scalability bottlenecks, chronic stability, and the incorporation of artificial intelligence for MEAs of BOC are prospected.
Atherosclerosis begins with endothelial dysfunction, inflammatory activation, and immune-cell recruitment within a spatially organized vascular wall. Conventional static cultures and Transwell systems are advantageous for isolated readouts, but they fail to effectively recapitulate multicellular compartmentalization, extracellular matrix support, and dynamic perfusion within a singular platform. Here, we present a four-channel microfluidic vascular-wall chip designed to reconstitute an endothelial cell-extracellular matrix-smooth muscle cell arrangement and to model early atherosclerosis-related inflammatory endothelial dysfunction. The device comprises a perfusable endothelial channel, a collagen I hydrogel region embedded with human aortic smooth muscle cells, a cell-free matrix region, and a culture-medium supply channel. Under physiological conditions, HUVECs formed a ZO-1-positive endothelial barrier and maintained high cellular viability. Stimulation with TNF-α and IL-1β (10 ng/mL each) elevated IL-6 secretion, promoted the recruitment of THP-1-derived M0-like macrophages, disrupted ZO-1 continuity, and increased FITC-dextran permeability without causing extensive cell death. The chip was subsequently utilized to evaluate metformin and atorvastatin therapies. The combinational treatment produced a more pronounced attenuation of MCP-1 secretion than either monotherapy under the inflammatory background. While this platform does not recapitulate advanced plaque formation, lipid deposition, foam-cell formation, or disturbed arterial shear, it successfully provides a microfluidic model of early inflammatory endothelial dysfunction to facilitate mechanistic studies and preliminary anti-inflammatory drug evaluation.
Most organ-on-chip models focus on parenchymal cell function, overlooking the critical role of endothelial-immune interactions in metabolic disease pathophysiology. Drugs for metabolic conditions, such as SGLT2 inhibitors, provide not only metabolic improvements but also vascular-protective effects, underscoring the need for human platforms that capture immunovascular dynamics. Here, we developed a human endothelial-immune cells-on-chip system integrating patient-derived blood outgrowth endothelial cells, T cells, and hepatocytes to model the liver sinusoidal microenvironment. Using plasma from type 2 diabetes patients treated with dapagliflozin, the platform revealed reduced endothelial inflammatory activation, attenuated T cell migration, and decreased hepatocyte lipid accumulation, indicating systemic modulation of vascular and hepatic phenotypes. Despite the presence of endothelial SGLT2 protein expression, glucose uptake in vitro was unaltered by dapagliflozin, suggesting these beneficial effects might occur indirectly via plasma factors. Our multiplexed, human-relevant cellular platform enables simultaneous assessment of endothelial, immune, and hepatic responses, offering a versatile tool for personalized plasma-based drug screening and preclinical evaluation of vascular-protective therapies in metabolic diseases.
Physical damage to smartphones creates a persistent bottleneck in mobile forensic practice: once a device can no longer be accessed through its operating system, conventional logical acquisition fails, and investigators face a choice between accepting data loss and escalating to hardware-level intervention. This paper describes an integrated forensic workflow that addresses this gap by combining In-System Programming (ISP) and Chip-Off memory extraction with an AI-assisted artifact localization and prioritization layer. The workflow was evaluated on 18 physically damaged Android smartphones for which all standard acquisition paths were unavailable. Hardware extraction produced verified binary memory images from all 18 devices. A 1D-CNN localization classifier subsequently screened those images, achieving F1-score = 0.88 and ROC-AUC = 0.94 on the synthetic test partition. Prioritization of candidate windows reduced manual review volume by 78%, cut total expert review time by 63%, and shortened the time to first relevant artifact from 42 to 14 min relative to unassisted examination (indicative estimates based on three examiner sessions; no inferential statistical test was performed). The study contributes a formalized, criteria-driven decision model for selecting between ISP and Chip-Off, which are experimentally validated thermal extraction profiles for eMMC, UFS, and PoP/RAM memory.
Neutrophils are crucial players in the fight against infections. Unfortunately, dysregulated neutrophil function contributes to the pathogenesis of diseases, including cancer, fibrosis, and atherosclerosis, that leave those afflicted vulnerable to severe infections. Many of these diseases are accompanied by differential lysyl oxidase (LOX) activity. The LOX enzyme crosslinks collagen and elastin, two highly expressed proteins in the extracellular matrix (ECM), altering the ECM's mechanical properties. While it is known ECM mechanical properties regulate neutrophil function, the role of LOX crosslinking of collagen on the neutrophil response is unclear. This study uses a microfluidic "infection-on-a-chip". This device consists of a model blood vessel endothelium embedded in an ECM mimic to investigate the how LOX crosslinking of collagen affects neutrophil function in response to infection. Interestingly, LOX-crosslinking of collagen deceases neutrophil extravasation through an endothelium in response to Pseudomonas aeruginosa compared to uncrosslinked collagen hydrogels. Critically, endothelial cells in devices with LOX-crosslinked collagen exhibited increased VE-cadherin expression compared to those seeded in uncrosslinked collagen gels, which is hypothesized to restrict neutrophil extravasation. These data demonstrate the regulatory capability of LOX over the neutrophil response, providing a potential therapeutic pathway for diseases associated with neutrophil dysregulation and LOX activity that merits further investigation.
Electrospinning is a highly versatile technique for fabricating nanofibrous membranes with high surface-area-to-volume ratios and tunable porosity. Although polycaprolactone (PCL) is widely utilized in biomedical engineering due to its biocompatibility, its electrospinning traditionally relies on hazardous organic solvents like dichloromethane (DCM) and N,N-dimethylformamide (DMF). This paper details the development of a fully sustainable, green electrospinning process for PCL using a bio-derived binary mixture of acetic acid and formic acid. Processing parameters (applied voltage, tip-to-collector distance, and flow rate) were systematically optimized using a Design of Experiments (DoE) response surface methodology. Scanning electron microscopy (SEM) confirmed the successful fabrication of uniform, bead-free nanofibers with a mean diameter of 247 nm, representing a 37.3% reduction compared to conventional DCM:DMF-spun matrices. Fourier-transform infrared spectroscopy (FTIR) verified complete solvent evaporates.
To investigate the role and molecular mechanism of the NECTIN3-TIGIT axis in melanoma lymph node metastasis. Single-cell RNA sequencing was performed on human primary melanoma and lymph node metastatic tissues. A tumor lymph node metastasis-on-a-chip model incorporating vascular, lymphatic, and dual-tumor modules was constructed, along with in vitro coculture systems using CD8+ T cells and regulatory T cells. Functional blockade was achieved via NECTIN3 knockdown, TIGIT inhibitor (Tiragolumab), and combined antiPD1 therapy. The NECTIN3-TIGIT axis was identified as a core immune ligand-receptor pair in the highmetastasis subgroup, associated with increased regulatory T cell infiltration and CD8+ T cell exhaustion. Both NECTIN3 and TIGIT expression were significantly elevated in metastatic lesions and correlated with reduced overall survival. The chip model recapitulated melanoma lymphatic migration and confirmed the immunosuppressive microenvironment. Mechanistically, the NECTIN3-TIGIT axis induced CD8+ T cell exhaustion via the SHIP-1/TRAF6 pathway and promoted regulatory T cell activation by inhibiting AKT/mTORC1 signaling. NECTIN3 knockdown or Tiragolumab treatment suppressed tumor lymphatic migration, while combined antiPD1 and Tiragolumab most effectively reversed T cell exhaustion, impaired regulatory T cell function, and reduced metastasis. The NECTIN3-TIGIT axis promotes melanoma lymph node metastasis by remodeling the immunosuppressive microenvironment. Combined blockade of NECTIN3-TIGIT and PD1 pathways represents a promising therapeutic strategy.
Background: Clonal hematopoiesis of indeterminate potential (CHIP) can lead to adverse outcomes and may begin early in life. This study aimed to investigate the association between early-life events and CHIP. Methods: In total, 456,658 participants from U.K. Biobank without baseline hematologic malignancies were enrolled. Exposures included 17 early-life events, including reproductive, childhood adversity, and pre-adulthood development factors. CHIP was derived from whole-exome sequencing for mutations in 74 driver genes. Logistic regressions were used to estimate associations between early-life events and the presence of any CHIP or gene-specific CHIP mutations. Results: Overall, 17,513 (3.8%) individuals with any CHIP were identified, among which the most common subtype was DNMT3A (2.4%), followed by TET2 (0.6%) and ASXL1 (0.4%). Compared with participants without sexual abuse in childhood, those who experienced such abuse were positively associated with CHIP (OR 1.35, 95% CI 1.02-1.80), especially among ASXL1, JAK2, and TP53 mutations. Long-term/recurrent antibiotic use as a child or teenager was positively associated with CHIP (OR 1.11, 95% CI 1.02-1.21), especially among DNMT3A, ASXL1, and EP300 mutations. Sex-specific differences were observed, including sexual abuse associated with ASXL1-CHIP in males and JAK2/TP53-CHIP in females and long-term/recurrent antibiotic use associated with DNMT3A/EP300-CHIP in males and ASXL1-CHIP in females. Furthermore, we identified circulating proteomic biomarkers shared by six pairs of early-life factors and gene-specific CHIP mutations, including B2M for sexual abuse and JAK2-CHIP. Conclusions: Early-life factors, especially sexual abuse and long-term/recurrent antibiotic use, were positively associated with the presence of CHIP, particularly among specific gene mutations, offering potential targets for susceptibility and pathogenesis exploration.
Clonal hematopoiesis of indeterminate potential (CHIP) and the gut microbiota-derived metabolite trimethylamine N-oxide (TMAO) are both linked to NLRP3-mediated cardiovascular inflammation, but their interaction has not previously been explored. This work proposes the CHIDT axis (clonal hematopoiesis-dysbiosis-TMAO), a feed-forward mechanism in which TET2 loss-of-function CHIP- and TMAO-generating Gram-negative gut dysbiosis mutually enhance cardiovascular risk. The model proceeds in three nodes. CHIP-associated intestinal immune dysregulation promotes luminal expansion of Gammaproteobacteria, which produce both trimethylamine via CntA/CntB-mediated L-carnitine oxidation and ADP-heptose as an obligate LPS biosynthetic intermediate. TMAO amplifies NLRP3 inflammasome activation through the SIRT3 → SOD2 → mtROS pathway. The evidence base of the CHIDT model is strongest for TET2-CHIP; the proposed extension to DNMT3A-CHIP rests on indirect, associative data and requires dedicated experimental confirmation before it can be considered established. TXNIP cascade, with predicted disproportionate potency in macrophages epigenetically primed by TET2 haploinsufficiency. High concentrations of TMAO have also been shown to suppress TET2 expression in endothelial cells through CYTB promoter hypermethylation, inducing NLRP3-GSDMD-dependent pyroptosis, although it remains unclear whether physiological TMAO levels can trigger this effect. Concurrently, ADP-heptose activates the ALPK1-TIFA-NF-κB pathway in bone marrow progenitors, favoring the expansion of mutant hematopoietic stem and progenitor cells. The model identifies three potential therapeutic strategies: NLRP3 inhibition, microbial TMA lyase inhibition, and microbiome-targeted reduction in Gram-negative bacteria. None has been tested in CHIP carriers stratified by plasma TMAO. Further studies in preclinical models and human cohorts integrating CHIP genotyping and TMAO quantification are needed to validate the CHIDT axis as a target for precision cardiovascular prevention.
Systemic lupus erythematosus (SLE) is an established, independent risk factor for cardiovascular disease (CVD), most notably premature atherosclerotic cardiovascular disease (ASCVD). This association is thought to relate to chronic immune mediated inflammation. Clonal expansion of haematopoietic stem and progenitor cells (HSPCs) with acquired mutations, but no evidence of a blood disorder, is known as clonal haematopoiesis of indeterminate potential (CHIP). CHIP is associated with a pro-inflammatory immune phenotype, driven predominantly by mutant myeloid cells, and is similarly strongly associated with ASCVD. When SLE and CHIP co-occur, there may be synergy of their canonical cellular and molecular inflammatory pathways or even convergence of pathways through shared mechanisms of immune dysregulation, which accelerate CVD. Furthermore, enrichment of HSPC clones carrying CHIP driver mutations has been observed in chronic inflammatory conditions, including SLE. In this review, we explore the emerging role of CHIP in the relationship between SLE and ASCVD, proposing it as a pathogenic nexus in a triangular inflammatory network. Defining these relationships will help early identification of high-risk individuals and facilitate therapeutic targeting of CHIP to mitigate ASCVD complications in SLE patients.
Accurate measurement of the temperature in the cutting zone is essential for closed-loop machining. However, it remains difficult due to the small size of the tool-chip contact area, its partial concealment by chips and the steep thermal gradients present. This study presents an integrated framework that combines a thin-film thermocouple (TFTC) on the rake face of a polycrystalline cubic boron nitride (PCBN) tool with a thermo-mechanical wear-coupled simulation in order to monitor cutting temperature and predict tool wear. The three-dimensional finite-element turning model includes a moving heat source that represents plastic and frictional heat at the tool-chip interface, as well as an Archard-type wear law that is enhanced by a temperature correction factor. The TFTC is fabricated by magnetron sputtering NiCr and NiSi films onto an insulating layer, after which it is embedded in the tool as a minimally intrusive in situ sensor. Turning experiments on AISI 1045 steel were performed at spindle speeds of 1000-3000 rpm, feeds of 0.05-0.20 mm/rev and depths of cut ranging from 0.3 to 1.0 mm under dry, wet (emulsion) and cryogenic (liquid nitrogen) cooling conditions. Simulated temperature fields reveal strong localisation at the tool-chip contact and a nonlinear increase in peak rake-face temperature with spindle speed, which fits a quadratic regression with R2 = 0.99. The TFTC shows a response time of around 0.3 s with less than 5% overshoot, and its thermoelectric voltage is almost perfectly linear with temperature (R2 = 1), with a sensitivity of approximately 12 µV/°C. During cutting, TFTC readings agree with infrared measurements within ±3 °C and demonstrate improved robustness in occluded zones. The coupled wear model replicates the observed wear growth trend with the compact expression VB = 0.0001·t0.8. Sensitivity tests indicate that thermo-mechanical coupling increases wear rates compared to single-factor models, and that cooling reduces thermal loads by approximately 15% (wet) and 25% (cryogenic).
The purpose of side-channel leakage detection is to determine whether or not there is side-channel leakage in the target cryptographic chip. The application of grouping (i.e., dividing the collected power traces into groups based on a property of the intermediate value, such as the Hamming weight of a byte or the bit value of an S-box output) in side-channel leakage detection is a research hotspot. The bit-level grouping mode and the byte-value grouping mode are proposed by previous scholars. However, the bit-level grouping mode does not match the byte operation architecture of cryptographic chips, resulting in an overly fine detection granularity and a high computational complexity. Although the byte-value grouping mode takes into account the byte operation architecture of cryptographic chips, it will cause unequal sizes of traces contained in two groups, reducing the test efficiency. In light of this, we propose the Interval-Optimized Hamming-Weight-Oriented Grouping (IHOG) Mode. IHOG groups data according to the Hamming weight (HW) of byte, dividing them into two groups with Hamming weights of {0, 1, 2, 3} and {5, 6, 7, 8}. In this way, it solves the problem of overly fine detection granularity and high computational complexity caused by bit-level grouping, and it also addresses the issue of unequal sample sizes and low test efficiency caused by the byte-value grouping mode. This paper verifies the effectiveness of the proposed IHOG method using four datasets, namely DPA v4, AES HD, Custom Dataset 1, and Custom Dataset 2. The results show that, compared with three existing grouping schemes such as HW value, bit value, and byte value, the IHOG scheme proposed in this paper increases the accuracy of leakage detection by 37.2%, 18.5%, and 146.3% respectively at the selected leakage points.
While ovarian cancer screening is not recommended in the general population, attention has shifted to screening women with elevated hereditary risks. Although germline BRCA 1/2 pathogenic variants account for 40% of inherited ovarian cancer risk and family history (FH) remains important, known germline variants alone do not fully explain familial ovarian cancer risk. Whole-exome sequencing (WES) was performed on blood samples taken from 231 individuals, including 39 patients with high-grade serous ovarian cancer (HGSOC) and 192 healthy controls (HCs) stratified by FH. We analyzed pathogenic or likely pathogenic (P/LP) germline variants in cancer-related genes and assessed their association with family cancer history. Additionally, we performed somatic variant comparisons using 1:4 propensity score matching and analyzed clonal hematopoiesis of indeterminate potential (CHIP)-related somatic variants. P/LP germline variants were detected in 56.4% of HGSOC patients, 49.4% of controls with FH, and 33.3% without. The HGSOC group and controls with FH exhibited similar P/LP germline mutation patterns in ovarian cancer-related genes. From CHIP analysis, somatic CHIP mutations were detected in 6.3% of the HGSOC group and 8.5% in HCs. Our findings demonstrate genomic overlap between ovarian cancer patients and FH-positive individuals. Therefore, germline variant screening could be considered to facilitate early diagnosis.
The contamination by foodborne pathogens posed a significant health threat and huge economic burden. Traditional detection methods were limited by cumbersome and time-consuming procedures, low automation, and reliance on expensive instrumentation, making them inadequate for on-site detection. This paper presented a centrifugal microfluidic chip that integrated sample pretreatment, nucleic acid extraction, amplification reaction, and signal detection. The chip featured an innovative design that combined a bursting valve with the siphon channel and employed a dual-channel configuration for splitting and directing the flow of different reagents, thereby overcoming the instability issue of unintended pre-activation or interruption that often occurred in the cascade design of multilevel siphon channels. Moreover, by synergistically combining with immunomagnetic separation as well as multi-enzyme isothermal rapid amplification, a portable, easy, rapid, high-sensitivity, and low-cost point-of-care testing (POCT) system for foodborne pathogens was developed. Under optimized conditions, the system enabled detection of Salmonella in spiked milk samples at 10 CFU/mL in 1 h. The recoveries ranged from 83.22% to 127.60%, with relative standard deviations of ≤13.7%, indicating that this system had great potential for rapid and high-sensitivity detection of foodborne pathogens in resource-limited settings.
Objectives: To investigate the potential mechanisms of maternal pregestational diabetes-induced neural tube defects (NTDs) by integrating proteomic data and histone H4 lysine 5 acetylation (H4K5ac) ChIP-seq data from the mouse model. Methods: The diabetic mouse model was established by intraperitoneal injection of streptozotocin (STZ) into female friend leukemia virus B strain (FVB) mice, with subsequent blood glucose monitoring. Diabetic females were then mated with healthy males, and embryonic tissues were collected on embryonic day 9.5. Among the embryos obtained from diabetic pregnancies, six NTDs embryos and six control embryos were selected for protein expression profiling using tandem mass tag (TMT)-labeled liquid chromatography-tandem mass spectrometry (LC-MS/MS), as well as for assessment of H4K5ac modification by ChIP-seq. Multi-omics integration was performed to identify common differentially expressed genes, followed by functional enrichment analysis. Key genes were validated using RT-qPCR. Results: Proteomic analysis revealed that differentially expressed proteins were significantly enriched in focal adhesion pathway. Protein-protein interaction (PPI) network analysis indicated that these proteins (e.g., Integrin alpha 3 (Itga3), glycogen synthase kinase 3 beta (Gsk3b), mitogen-activated protein kinase 9 (Mapk9)) were associated with focal adhesion and cytoskeletal functions. Integrated multi-omics analysis identified 923 common differentially expressed genes, which were also significantly enriched in focal adhesion pathway. Within this pathway, the protein expression levels of Itga3, Gsk3b, and Mapk9 exhibited a consistent co-variation trend with H4K5ac enrichment. RT-qPCR results confirmed that Itga3 was significantly up-regulated, while Gsk3b was down-regulated in the NTDs group (p < 0.05). Conclusions: Maternal pregestational diabetes may contribute to NTDs by disrupting cytoskeletal reorganization, cell adhesion, and migration processes. This disruption is likely mediated through H4K5ac-regulated expression of key focal adhesion pathway genes such as Itga3 and Gsk3b.
To investigate how the process parameters of ultra-thin diamond grinding wheel dicing affect the dicing quality of silicon carbide (SiC) wafers, single-factor experiments were designed. This study examined the influence of key process parameters, including spindle speed, feed rate, and first dicing depth, on the maximum chip width on the front side W1 and the maximum chip width on the back side W2, thereby determining their optimal parameter ranges. Subsequently, a quadratic polynomial prediction model was established using response surface analysis to analyze the interactive effects among the grinding wheel dicing process parameters. Finally, the prediction model was optimized using the genetic algorithm NSGA-II, and the optimal parameter combination for the two response variables was determined: a spindle speed of 31,960 r/min, a feed rate of 2.0019 mm/s, and a first dicing depth of 197.51 μm, yielding an average W1 of 4.8852 μm and W2 of 18.5360 μm. The relative errors between the predicted and average experimental values are 2.83% for W1 and 4.43% for W2. Both errors are below 5%, confirming the validity of the model. Therefore, the model serves as a practical reference for planning subsequent dicing processes using ultra-thin diamond grinding wheels.
The intractability of diabetic bone defects mainly results from derailed inflammation. While peripheral neuropathy is a common comorbidity, whether sensory dysfunction contributes to uncontrolled inflammation in diabetes is poorly understood. Here, within diabetic bone defects, we show that diminished sensory innervation is coupled with disrupted immune dynamics, characterized by both delayed neutrophil chemotaxis and abnormal neutrophil retention that resulted from impaired macrophage efferocytosis. Therefore, we design a chocolate chip cookie-like scaffold, in which the surface-embedded microspheres function as "chips" enabling burst interleukin-8 (IL-8) release, while the surrounding matrix provides sustained nerve growth factor release from silk fibroin matrix. Timely neutrophil chemotaxis induced by IL-8 triggers bone healing via stem cell recruitment, which is reinforced by sensory innervation by inducing neutrophil N2 polarization. Notably, macrophages preferentially established intimate physical proximity to outgrowing neurites to form a synapse-like structure, where they restore efferocytosis driven by neuronal Galectin-3. Moreover, spatiotemporally regulating neuroimmune circuit enhances mandibular bone regeneration in diabetic rats, highlighting the therapeutic potential of neuroimmune interaction in programming diabetic inflammation resolution.
G-quadruplex (DG4) is folded in guanine-rich DNA sequences and regulates DNA replication and transcription. Although bioinformatics analyses have predicted the presence of DG4 in maize, its biological functions remain largely unexplored. In this study, we treated maize seedlings with 0, 100, 200, and 300 μM TMPyP4, a DG4-stabilizing ligand, and observed that TMPyP4 inhibits radicle growth by increasing reactive oxygen species (ROS) levels and inducing DNA fragmentation in radicle cells. Transcriptomic RNA-seq revealed that TMPyP4 modulated the expression of 1614 genes in maize radicle cells, which were predominantly associated with redox reactions, membrane components, and secondary metabolic pathways. BG4-ChIP-seq analysis demonstrated that DG4 structures are evenly distributed across the ten chromosomes of the maize genome, occupying 22,449 loci and showing significant enrichment for specific DG4-binding motifs. Integrative analysis of RNA-seq data and BG4-ChIP-seq identified 944 differentially expressed genes, which were significantly enriched in pathways related to redox reactions and secondary metabolism. Collectively, these findings suggest that DG4-stabilizing ligands regulate maize radicle growth by modulating ROS homeostasis, providing critical insights into the functional roles of DG4s in maize.