Diabetic Foot Ulcers (DFUs) are among the most feared complications of Diabetes Mellitus (DM). The management of DFUs emphasises limb salvage, and to achieve this, clinical tools are utilised to identify patients who may require a more aggressive initial approach. Current clinical prediction models fail to account for variability in ulcer characteristics and patient-specific comorbidities, limiting their precision in individualising outcome prediction. This review explores the emerging role of molecular biomarkers in personalising DFU outcome prediction. The pathophysiology of DFUs is examined with an emphasis on disruptions in wound healing specific to DM, focusing on biomarkers involved at different stages of wound healing. This review highlights studies that have shown predictive potential of several biomarkers in a variety of biological samples from patients with DFUs. Despite promising findings, challenges remain in their clinical adoption. Larger studies and the development of accessible, biomarker-based diagnostics are essential to translate this approach into clinical settings and ultimately reduce the global burden of DFUs through personalised therapy, which would considerably increase the quality of life of people with DM.

Digital loop-mediated isothermal amplification based on turbidity (digital LAMP) is a nucleic acid detection technique that combines high sensitivity and specificity with low cost, offering substantial potential for deployment in resource-limited settings. However, endpoint interpretation relying on bright-field microscopic imaging commonly suffers from insufficient contrast, blurred target boundaries, and pronounced noise interference, which severely hampers automated and large-scale identification of positive reaction units. To address these challenges, we propose NanoFuse-YOLO11, an object detection model tailored for weak-contrast microscopic turbidity images. The model incorporates a Dynamic Feature Representation (DFR) module to enhance structural perception in low-contrast regions, while integrating an Adaptive Multi-Scale Spectral Attention (AMSA) module to effectively suppress background noise and emphasize critical diagnostic features. In addition, the WIoUv3 regression loss is employed to improve localization accuracy and stability under high IoU thresholds. Experimental results on a self-constructed turbidity-based dLAMP dataset demonstrate that the proposed method achieves 99.3% mAP@0.5 and 89.6% mAP@0.5:0.95, substantially outperforming YOLO variants and several mainstream object detection models, while maintaining favorable real-time inference performance with controlled model size and computational overhead. Overall, NanoFuse-YOLO11 serves as a reliable automated analysis tool for endpoint interpretation of bright-field turbidity-based digital LAMP, providing critical technical support for fluorescence-free, low-cost digital nucleic acid quantification and offering a generalizable modeling paradigm for other weak-contrast microscopic imaging detection tasks.

Accurate and rapid detection of biomolecules is pivotal for medical diagnosis, healthcare, and biological research. However, most existing biosensing methods fail to simultaneously achieve high sensitivity, low cost, rapid response, and simple operation. Lateral flow assays (LFAs) are widely used point-of-care testing (POCT) tools, featuring low cost, ease of use, and results within minutes, but LFA performance is often constrained by insufficient signal generation. Two-dimensional (2D) materials, endowed with a large surface area-to-volume ratio, tunable physicochemical properties, and versatile surface chemistry, hold great promise for advancing biosensing technologies. Nevertheless, the application of 2D materials in LFAs remains limited and lacks systematic compilation. In this review, we summarize the main synthesis methods, processing conditions, and key properties of typical 2D materials, with a focus on their biointeraction behaviors and biosensing performance. We then introduce the basic structure and working principle of LFAs, and elaborate on how the intrinsic properties of 2D materials can be harnessed to enhance signal output across different components of LFA strips. Finally, we discuss the core challenges and future directions, aiming to provide support for the design of more reliable and sensitive LFA systems tailored for practical POCT applications.

With the maturation and standardization of antibody discovery technologies, the core competitive advantage of diagnostic antibodies is shifting from discovery to design. Traditionally, antibody development has emphasized molecular recognition performance, with value defined by static parameters such as affinity, specificity, and stability. However, the emergence of mass spectrometry–based reverse development, deep single B-cell screening, and AI-driven antibody design has transformed antibody identification into a standardized capability. As a result, antibodies are no longer scarce resources, and their differentiated value is reflected in their behavioral attributes rather than mere recognition strength. Here, we propose a new paradigm in which diagnostic antibodies evolve from passive molecular recognition elements into structurally intelligent units. In this framework, antibody capabilities shift from being “stronger” to being “smarter, programmable, and capable of expressing system-level behaviors.” We define four key ability dimensions underlying this transformation: affinity stratification, conformational logic, functional coupling, and system behavior. Through practical examples, we demonstrate that the future value of diagnostic antibodies lies in their capacity to actively shape diagnostic systems, rather than simply participate as interchangeable reagents. As antibodies progressively acquire intrinsic decision-making logic and structural control properties, they will emerge as the primary intelligent units of in vitro diagnostic systems. Consequently, the ultimate goal of diagnostic antibody development is no longer the infinite optimization of recognition efficiency, the rational design of structural logic and functional programmability. This paradigm shift will fundamentally reshape diagnostic technologies and drive clinical testing from quantitative signal interpretation toward an emerging discipline of in vitro immune cognition.

Bone defect repair remains a significant challenge in clinical orthopedics, primarily due to the limitations of traditional techniques, such as insufficient osteogenic efficiency and non-functional bone regeneration. Recently, the regulation of energy metabolism has emerged as a promising avenue for bone regeneration. This review systematically examines the critical yet underexplored role of energy metabolism in bone regeneration, focusing on the dynamic regulatory mechanisms in osteoblasts and bone marrow mesenchymal stem cells across various metabolic pathways, and clarifies the influence of glucose metabolism and mitochondrial function on cellular proliferation and differentiation. Besides, three complementary strategies are proposed: leveraging cell derivatives (e.g., mitochondria, exosomes) to provide metabolic support; employing active factors (e.g., ions, enzymes) to target key metabolic pathways; and designing biomimetic scaffolds to reconstruct a favorable metabolic microenvironment. Furthermore, deficiencies in current research—such as the lack of systematic analysis of metabolic networks, clinical validation, and multidisciplinary collaborative innovation—are noted. Future directions should explore the interplay between metabolism and epigenetics, the development of responsive metabolic regulatory materials, and advancements in clinical translation, ultimately advocating for a new paradigm in precise bone defect repair to significantly enhance patient outcomes.

Ageing, as a gradual and largely irreversible biological process, characterised by declining organismal vitality and multi-organ functional impairment. While research on ageing constitutes a major scientific focus, current efforts concentrate on two domains: elucidating fundamental mechanisms of ageing and developing anti-ageing strategies, and addressing the social management of ageing populations. A critical gap persists in the clinical understanding and management of ageing itself. Specifically, there is insufficient recognition and structured approach towards ageing within clinical practice. To address this, we propose a novel clinical staging system for ageing, which based on manifestations observed by distinct stages. For each stage, we delineate the clinical presentations, biological phenomena, theoretical underpinnings, and key management priorities. This framework aims to bridge the current void in the clinical conceptualization and stage-specific management of ageing, establishing a novel foundation for a structured, staged management model. We anticipate this framework will contribute significantly to advancing the goal of healthy aging.

During the launch phase prior to microgravity stage, hypergravity and vibration can potentially damage cell models used in space medical research, compromising the success of subsequent missions. Bioinks and bioprinting play a pivotal role in the successful delivery of cell models and the fabrication of tissue models for space biomedicine research. In order to streamline the process and conserve valuable resources, it is crucial to examine the storability of bioink and high survival human cells under space conditions. This study investigated the effects of hypergravity and vibration on blood brain barrier (BBB) related cells in 2D monolayers and 3D decellularized matrices, assessing proliferation, viability, and gene expression. The study confirmed 3D embedded cells showed marked tolerance to launch-associated mechanical factors, contrasting with the disruption on 2D adherent cells. In addition, the present study provided methods for storing hybrid bioink (decellularized extracellular matrix of mammalian soft tissue) and high viability of cells loaded in bioink under the existing storage conditions of space station. Printability, rheological property and ultrastructure of bioink is maintained after storage in 4 ℃ for 4 Weeks. Three types of BBB related cells can maintain their viability and function under the cryopreservation of preservatives. This study verified the feasibility of bioink and cell storage in the low-temperature environment available on orbit, addressing the challenges of maintaining cell viability, short experimental window, and susceptibility to launch processes in cell experiments conducted in space, and providing a promising foundation on efficient and reproducible complex bioprinting in space.

Protein sensors are key tools for infectious disease diagnosis and monitoring. The medical diagnostics field is now rapidly identifying key protein markers for the detection of a range of conditions, from early cancer development through to assessment of dementia risk a decade prior to symptoms onset. Many point-of-use diagnostic tools form part of standard protocols for small molecule sensing in healthcare, including glucose and ketone body sensors. Label-free optical biosensors have emerged as reliable detection tools that provide high versatility and adaptability to detect a broad range of target analytes. Herein, we combined nanoporous anodic alumina (NAA) photonic chip technology with tailor-engineered ‘nanobodies’—recombinant variable domains of heavy-chain-only antibodies—to achieve high affinity binding to human serum albumin (HSA). We monitored dynamic shifts in the optical fingerprint of nanobody-conjugated NAA platforms in real time when these were exposed to target proteins, through reflectometric interference spectroscopy (RIfS). We performed a comprehensive characterisation of the sensing performance, where binding mechanisms were elucidated through kinetic profiles. The nanobody-conjugated NAA protein sensor demonstrated good affinity, selectivity, and sensitivity towards HSA. Our analysis revealed a sensitivity of 27.3 ± 3.2 nm µM–1 and low limit of detection of 16.3 ± 1.6 µM, which are well-below the ranges for diagnosis of medical conditions such as nephrotic syndrome. The obtained results revealed that the RIfS-based protein sensor integrated with nanobody-modified NAA has promising potential to develop point-of-care platforms for clinical diagnosis of diseases.

Cholesterol is currently one of the main biomarkers for the assessment of cardiovascular diseases risk, with low-density and high-density lipoprotein measured in the global cardiovascular risk assessment. Nevertheless, the detection of these molecules still relies on traditional methods, which can be resource intensive. Research has been focusing on developing more rapid techniques for cholesterol detection, often emphasizing technologies suitable for point-of-care use to facilitate screening and diagnosis in decentralized or underserved settings. This review begins with an overview of cholesterol metabolism and biology, followed by an in-depth examination of the various sensor technologies reported in the literature for detecting cholesterol in its different forms, including free (non-esterified), esterified, and lipoprotein-bound, ranging from enzymatic to non-enzymatic approaches, such as molecularly imprinted polymers. The functioning mechanism, advantages, and limitations of each type of sensors are discussed, leading to the final recommendations. Enzymatic sensors could prove preferrable in the detection of free or esterified cholesterol, given their selectivity, while molecularly imprinted polymers seem to have the edge in the detection of lipoproteins, with different studies demonstrating their applicability in human serum.

Bony materials are biogenic composites of protein fibers and mineral that create hierarchical structures. In the case of teeth, dentin is the main component and similar to other bones, it contains porosity at multiple length scales. It is traversed by micron-sized hollow channels known as dentinal tubules, essential for temperature and pain sensation. Tubule density and thus porosity vary throughout the macroscopic 3D structure, with porosity increasing towards the pulp. The different densities in teeth are easily revealed non-destructively in 3D by X-ray imaging using computer tomography (CT). Yet elemental composition analysis is more difficult to obtain from within the cm-sized heterogeneous bulk material. We describe an approach of merging CT measurements of young, healthy, intact bovine teeth with micro-X-ray fluorescence (micro-XRF) images of serially sectioned slices. Through the combination of multi-resolution CT measurements with elemental concentration quantification, gradients in density and element distributions such as calcium (Ca), phosphorus (P) and zinc (Zn) are revealed in 3D. While the main constituents (Ca and P) are homogeneously distributed in the structure, Zn concentration increases significantly and exponentially towards the pulp. We find an inverse association between dentin tissue density and Zn concentration localizing this element in or around tubules.

Due to the concealed location of the nasopharynx, early diagnosis and treatment of nasopharyngeal carcinoma are relatively difficult. Although nasopharyngeal carcinoma is sensitive to radiation, normal tissues and organs are inevitably damaged by radiation. Patients who cannot tolerate radiation often need to be treated with chemotherapy drugs. Thus, how to improve the sensitivity of chemoradiotherapy and reduce the toxicity of chemoradiotherapy is an urgent need for us to study. In this study, we designed bionic nanobombs with a core-shell structure (Nm-pAu/CP/KU): PEGylated gold nanoparticles (pAu) were loaded with cisplatin (CP) and a radiochemotherapy sensitizer (KU-60019) to form core pAu/CP/KU, and homologous nasopharyngeal carcinoma cell membrane vesicles (Nm) were used as the shell. Nm endows pAu/CP/KU with good biocompatibility and immune escape function. Through adhesion molecules, Nm-pAu/CP/KU showed targeted aggregation in nasopharyngeal carcinoma sites. In the acidic tumor microenvironment, after PEG detachment, cisplatin and KU-60019 were released. AuNPs promoted X-ray absorption at the tumor site and combined with cisplatin to induce DNA breakage. KU-60019, as a specific inhibitor of ATM proteins, inhibited ATM-mediated DNA damage repair and enhanced radiochemotherapy sensitivity to X-ray and cisplatin treatment. Nm-pAu/CP/KU provides a promising therapeutic strategy for targeted dual sensitization to radiochemotherapy in nasopharyngeal carcinoma.

Background: The diagnostic performance of ultra-high-field ²³Na MRI in predicting the P53 phenotype and Ki-67 labeling index (LI) in adult-type diffuse gliomas is still unknown.No studies have compared its diagnostic efficacy with DWI for distinguishing isocitrate dehydrogenase (IDH) genotype, Ki-67 LI, and P53 phenotype. ̵‌Purpose:‌ To determine whether ²³Na MRI at 7 Tesla (7T) field can accurately predict IDH genotype, Ki-67 LI, and P53 phenotype in adult-type diffuse gliomas and compare efficacy of ²³Na MRI with that of DWI. ̵‌Materials and Methods:‌ 36 glioma patients underwent preoperative ²³Na MRI on a 7T scanner (Siemens Healthcare, Erlangen, Germany). Total sodium concentration (TSC) and apparent diffusion coefficient (ADC), relative ADC (rADC) and relative TSC (rTSC) were acquired. ANOVA was used to compare differences in TSC, ADC, rTSC and rADC within groups. Receiver operating characteristic (ROC) curves and area under the curve (AUCs) were used to evaluate diagnostic performance. ̵‌Results:‌The TSC and rTSC of P53 mutant-type, high Ki-67 LI and IDH mutant-type were higher than that of P53 wild-type, low Ki-67 LI and IDH wild-type, respectively (p=0.009, =0.012, <0.001, <0.001, 0.025, <0.001). rTSC had highest diagnostic efficacy (AUC=0.862) in distinguishing gliomas with different Ki-67 LI. To distinguish different IDH genotype, rTSC had highest diagnostic efficacy (AUC=0.837). rTSC had high diagnostic efficacy (AUC=0.750) when distinguishing gliomas with different P53 phenotype. ̵‌Conclusions: 7T‌ ²³Na MRI can non-invasively distinguish adult-type diffuse glioma with different IDH genotype, P53 phenotype and Ki-67 LI. Compared with DWI (0, 1000 s/mm2), 7T 23Na MRI can have superior diagnostic performance.

Masticatory dysfunction induces astrocyte hyperplasia and disrupts brain cholesterol homeostasis, but the specific mechanism by which unilateral mastication drives cognitive decline remains unclear. A rat model of experimental unilateral mastication (EUM) was established via unilateral maxillary anterior and posterior tooth extraction, char-acterized by asymmetric masseter electromyography, muscle fiber type distribution, and acetylcholinesterase activity. Behavioral tests assessed learning and memory. Hippocampal changes were analyzed for astrocyte reactivity and synaptic integrity. Targeted cholesterol metabolomics profiled cholesterol species, with correlation anal-yses exploring links between metabolic perturbations and synaptic dysfunction. EUM rats showed accelerated learning deficits and memory decline. Hippocampal analyses revealed reactive astrocytosis and synaptic degeneration. Metabolomics identified hippocampal cholesterol ester accumulation, with dysregulated biosynthesis and ef-flux/metabolism pathways. Correlation analyses linked cholesterol dysregulation to synaptic impairment, with reduced 24-hydroxycholesterol (24-OHC) as a key mediator. Unilateral mastication impacts brain health via hippocampal cholesterol dysregulation, suggesting targeting cholesterol metabolism may mitigate associated cognitive decline. These findings highlight a potential connection between masticatory dysfunction and cognitive decline mediated by cholesterol metabolic pathways, providing mechanistic insights into oral-brain axis interactions with implications for preventing cognitive impairment.

Efficient lung targeting is the criterion for nanomedicines to treat pulmonary diseases. The low delivery of payloads to lung parenchyma is due to the elimination of reticuloendothelial system (RES) and the inhibition of pulmonary endothelial cell barriers (ECB). In this study, we discovered the efficient lung-targeting capability of dendritic-linear-dendritic polymer hybridized LNP@780 (DLD-HLNP@IR780) nanoparticles to achieve high lung/liver ratios ranging from 20-30. The exploration of targeting mechanism revealed that the IR780 iodide possessed high affinity to CD300LF and MRC1, which was specifically expressed on pulmonary ECs (endothelial cells) and macrophages. The CD300LF mediated the DLD-HLNP@IR780 nanoparticles to traverse ECs and macrophages and aggregate in lung parenchyma. The DLD-HLNP@IR780 nanoparticles loaded with pirfenidone (DLD-HLNP/P@IR780) were adopted to achieve lung-parenchyma-targeted realese of pirfenidone to treat idiopathic pulmonary fibrosis (IPF) and exhibited efficiently attenuated IPF progression. It provided an easy and potent strategy for fabricating lung-targeting nanomedicines to treat multiple pulmonary diseases.

Photoacoustic imaging is an advanced biomedical imaging technique that combines optical excitation and ultrasound detection to provide molecular functional information of biological tissues in vivo. From the underlying principles, the spatial resolution and imaging depth of the photoacoustic imaging system can be adjusted. In recent years, photoacoustic imaging has gained increasing attention for its potential in high-resolution microscopy, particularly in the context of cellular visualization. A wide range of techniques, including laser scanning, wavelength tuning, transducer design, and data acquisition strategy, have been explored to enhance resolution in photoacoustic imaging. These advances have enabled detailed imaging of cell nuclei, organelles, chromophores, and molecular distributions. This review highlights recent advancements in high-resolution photoacoustic imaging techniques aimed at visualizing cellular structures. We explore key system configurations, imaging methodologies, and representative biomedical applications, including label-free histopathological imaging, biochemical mapping, deep-tissue microscopy, and super-resolution imaging techniques. By summarizing these achievements, we aim to highlight the current state and future potential of photoacoustic imaging as a critical tool in cellular and molecular biomedical research.

Background: Circulating tumour DNA (ctDNA) is a promising minimally invasive biomarker for monitoring treatment response in cancer patients. In this study, we developed a tumour-informed workflow to enhance the detection of recurrence in head and neck cancer (HNC) patients, addressing challenges of low ctDNA tumour fractions and heterogeneity. Method: Patient-derived tumour tissues (N=12), peripheral blood cells, and 41 blood samples at baseline and post-treatment (3, 6, 12 and 24 months) were collected. Tumoral DNA and germline DNA underwent whole exome sequencing (WES) to identify somatic mutations, enabling the creation of individualized assays targeting up to 150 variants per patient. Supernatants from two HNC cell lines (CAL27 and SCC15) were used to evaluate assay sensitivity, which detected ctDNA levels as low as 2 parts in 100,000. Results: Baseline ctDNA was detectable in all patients (100%, 12/12). While baseline ctDNA mutations did not predict outcomes, post-treatment ctDNA strongly correlated with disease progression. A ctDNA threshold of 1 part in 10,000 distinguished relapse events from non-relapse cases. Patients with ctDNA positivity at 3- and 6-month follow-ups had poorer event-free survival (EFS). Conclusions: Our tumour-informed ctDNA workflow demonstrates high analytical sensitivity and specificity, offering a transformative approach for HNC management by enabling treatment de-escalation based on precise response measurements.

Outer membrane vesicles (OMVs) are nanoscale particles with intercellular communication functions, emerging as promising therapeutic methods in bone tissue engineering. In the bone healing and remodeling microenvironment, some OMVs can act on osteoblasts to regulate bone regeneration. This study reports that OMVs derived from the Gram-positive bacterium Lactobacillus reuteri (LrEVs) successfully accelerated the healing of critical-sized calvarial defects in rats by binding to polydopamine (pDA)-collagen membranes. Macrophages play a crucial role in bone regeneration, so we investigated the effect of LrEVs on the polarization of RAW264.7 macrophages in vitro and further examined the impact of macrophage polarization on the osteogenic differentiation of mouse bone marrow mesenchymal stem cells. The results showed that LrEVs regulated the bone immune microenvironment by promoting M2 macrophage polarization, thereby accelerating the healing of critical-sized calvarial defects in rats. We further confirmed that LrEVs induced macrophage transformation to the M2 type by stimulating the SPP1-JAK1-STAT3 signaling pathway. Thus, our study provides novel insights and potential applications of LrEVs in bone regeneration.

Background Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide. Helicobacter pylori (H. pylori) infection is a crucial initiative factor for the Correa cascade occurrence of GC. However, the immunological mechanisms of H. pylori-induced GC remain incompletely understood, particularly at the single-cell RNA sequencing (scRNA-seq) level. Methods We established a scRNA-seq atlas of gastric tumor, with a focus on T-cell-related genes for trajectory analysis,cell-cell communication analysis,and transcription factor regulatory network analysis. The results were validated by immunofluorescence staining of gastric tumors. Results We collected 63,603 cells from ten human gastric tissues and identified 20 distinct clusters, annotating 14 cell types based on canonical markers.In-depth dissection disclosed seven T cell subtypes in H. pylori positive gastric tumors. We further revealed two types of exhausted T cells CD4-C2-TIGIT(Tex)and CD8-C3-PDCD1(Tex). Among them, CD4-C2-TIGIT accounted for the highest proportion in H. pylori positive GC, from which we screened that the gene FYB1 was significantly correlated with prognosis. Immunofluorescence staining verified the localized expression of FYB1 in the T cell-rich areas of H. pylori positive tumors, further substantiating their role in the tumor immune landscape. Moreover, network interaction analysis demonstrated that immune cells, stromal cells, and epithelial cells interact in the tumor microenvironment (TME). Conclusion Our study constructs a comprehensive T cell atlas of GC, delineating T cell heterogeneity and their functional interactions within the H. pylori-driven TME. These findings highlight the prognostic potential of FYB1 in tumor immunity and provide new insights into the immunological mechanisms driving GC progression.