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Electrokinetic force has been the major choice for driving the translocation of molecules through a nanopore. However, the use of this approach is limited by an uncontrollable translocation speed, resulting in non-uniform conductance signals with low conformational sensitivity, which hinders the accurate discrimination of the molecules. Here, we show the use of inertial-kinetic translocation induced by spinning an in-tube micro-pyramidal silicon nanopore fabricated using photovoltaic electrochemical etch-stop technique for biomolecular sensing. By adjusting the kinetic properties of a funnel-shaped centrifugal force field while maintaining a counter-balanced state of electrophoretic and electroosmotic effect in the nanopore, we achieved regulated translocation of proteins and obtained stable signals of long and adjustable dwell times and high conformational sensitivity. Moreover, we demonstrated instantaneous sensing and discrimination of molecular conformations and longitudinal monitoring of molecular reactions and conformation changes by wirelessly measuring characteristic features in current blockade readouts using the in-tube nanopore device. The authors report a strategy to achieve high S/N ratio signal readout in single molecule sensing by incorporating the inertial forces as a new channel for independently controlling the translocation parameters with high precision.

Background Nanoplastics have been recently found widely distributed in our natural environment where ubiquitously bacteria are major participants in various material cycles. Understanding how nanoplastics interact with bacterial cell membrane is critical to grasp their uptake processes as well as to analyze their associated risks in ecosystems and human microflora. However, little is known about the detailed interaction of differentially charged nanoplastics with bacteria. The present work experimentally and theoretically demonstrated that nanoplastics enter into bacteria depending on the surface charges and cell envelope structural features, and proved the shielding role of membrane lipids against nanoplastics. Results Positively charged polystyrene nanoplastics (PS-NH 2 , 80 nm) can efficiently translocate across cell membranes, while negatively charged PS (PS-COOH) and neutral PS show almost no or much less efficacy in translocation. Molecular dynamics simulations revealed that the PS-NH 2 displayed more favourable electrostatic interactions with bacterial membranes and was subjected to internalisation through membrane penetration. The positively charged nanoplastics destroy cell envelope of Gram-positive B. subtilis by forming membrane pore, while enter into the Gram-negative E. coli with a relatively intact envelope. The accumulated positively charged nanoplastics conveyed more cell stress by inducing a higher level of reactive oxygen species (ROS). However, the subsequently released membrane lipid-coated nanoplastics were nearly nontoxic to cells, and like wise, stealthy bacteria wrapped up with artifical lipid layers became less sensitive to the positively charged nanoplastics, thereby illustrating that the membrane lipid can shield the strong interaction between the positively charged nanoplastics and cells. Conclusions Our findings elucidated the molecular mechanism of nanoplastics’ interaction and accumulation within bacteria, and implied the shielding and internalization effect of membrane lipid on toxic nanoplastics could promote bacteria for potential plastic bioremediation. Graphical Abstract

HighlightsA zero-reflection-induced phase singularity is achieved through precisely controlling the resonance characteristics using two-dimensional nanomaterials.An atomically thin nano-layer having a high absorption coefficient is exploited to enhance the zero-reflection dip, which has led to the subsequent phase singularity and thus a giant lateral position shift.We have improved the detection limit of low molecular weight molecules by more than three orders of magnitude compared to current state-of-art nanomaterial-enhanced plasmonic sensors.Detection of small cancer biomarkers with low molecular weight and a low concentration range has always been challenging yet urgent in many clinical applications such as diagnosing early-stage cancer, monitoring treatment and detecting relapse. Here, a highly enhanced plasmonic biosensor that can overcome this challenge is developed using atomically thin two-dimensional phase change nanomaterial. By precisely engineering the configuration with atomically thin materials, the phase singularity has been successfully achieved with a significantly enhanced lateral position shift effect. Based on our knowledge, it is the first experimental demonstration of a lateral position signal change > 340 μm at a sensing interface from all optical techniques. With this enhanced plasmonic effect, the detection limit has been experimentally demonstrated to be 10–15 mol L−1 for TNF-α cancer marker, which has been found in various human diseases including inflammatory diseases and different kinds of cancer. The as-reported novel integration of atomically thin Ge2Sb2Te5 with plasmonic substrate, which results in a phase singularity and thus a giant lateral position shift, enables the detection of cancer markers with low molecular weight at femtomolar level. These results will definitely hold promising potential in biomedical application and clinical diagnostics.

Nanoplastics are emerging pollutants of global concern. Agricultural soil is becoming a primary sink for nanoplastics generated from plastic debris. The uptake and accumulation of nanoplastics by crops contaminate the food chain and pose unexpected risks to human health. However, whether nanoplastics can enter grains and their impact on the grains of crop grown in contaminated soil is still unknown. Here, the translocation of polystyrene nanoplastics (PS‐NPs) in crops, including peanut (Arachis hypogaea L.) and rice (Oryza sativa L.) is investigated. It is demonstrated PS‐NPs translocation from the root and accumulation in the grains at the maturation stage. The treatment with PS‐NPs (250 mg kg−1) increases the empty‐shell numbers of rice grain by 35.45%, thereby decreasing the seed‐setting rate of rice by 3.02%, and also decreases the average seed weight of peanuts by 3.45%. Moreover, PS‐NPs exerted adverse effects on nutritional quality, such as decreasing the content of mineral elements, amino acids, and unsaturated fatty acids. To the knowledge, this is the first report of the presence of nanoplastics in the grains of crop plants grown in soil containing nanoplastics, and the results highlight the impact of nanoplastics on the yield and nutritional quality of crop grains. This study demonstrates that polystyrene nanoplastics could accumulate in crop grains, and pose adverse effects on nutritional quality of crop grains. Considering the ubiquitous distribution of plastic debris, the uptake and accumulation of nanoplastics by crops can contaminate the food chain, pose negative impacts on the crop economy and also may bring unexpected risks to human health.

Vessels encapsulating tumor clusters (VETC) are significantly associated with poor prognosis in hepatocellular carcinoma (HCC). However, identifying VETC early remains challenging. Recently, machine learning has shown promise for VETC detection, but their diagnostic accuracy lacks systematic validation. This meta-analysis aimed to systematically evaluate the diagnostic accuracy of machine learning models for detecting VETC in patients with HCC. The Cochrane Library, Embase, Web of Science, and PubMed were searched up to June 21, 2025. Eligible studies focused on machine learning models for HCC VETC diagnosis. Studies that merely analyzed risk factors or lacked outcome measures were excluded. The Prediction Model Risk of Bias Assessment Tool was used to evaluate the risk of bias. A bivariate mixed-effects model was used for a meta-analysis based on 2×2 diagnostic tables. Subgroup analyses were performed according to modeling variables (nonradiomic vs radiomic features) and model types (traditional machine learning vs deep learning). This meta-analysis included 31 studies comprising 6755 patients with HCC (2699 VETC-positive). Nineteen studies used machine learning models based on nonradiomic features, and 12 used radiomic features (including deep learning). In the validation set, the nonradiomic model demonstrated a pooled sensitivity of 0.72 (95% CI 0.66-0.78), specificity of 0.74 (95% CI 0.68-0.80), and an area under the summary receiver operating characteristic curve (SROC AUC) of 0.80 (95% CI 0.76-0.83). The radiomic model showed sensitivity of 0.81 (95% CI 0.73-0.87), specificity of 0.73 (95% CI 0.67-0.79), and SROC AUC of 0.84 (95% CI 0.80-0.87). Traditional machine learning achieved sensitivity of 0.84 (95% CI 0.71-0.92), specificity of 0.75 (95% CI 0.67-0.81), and SROC AUC of 0.83 (95% CI 0.80-0.86). Deep learning exhibited sensitivity of 0.77 (95% CI 0.69-0.84), specificity of 0.70 (95% CI 0.59-0.79), and SROC AUC of 0.81 (95% CI 0.77-0.85). This meta-analysis is the first to quantitatively assess the efficacy of machine learning models in HCC VETC diagnosis, addressing an evidence gap in this field. Unlike previous descriptive reviews, this analysis provides the first quantitative evidence revealing the potential value of machine learning in detecting HCC VETC. The findings provide a foundation for developing and refining subsequent intelligent detection tools. Despite their promising prospects, machine learning models have not yet reached the maturity required for clinical translation, owing to methodological heterogeneity, limited validation, and a high risk of bias. Future research should focus on conducting multicenter, large-sample, standardized, prospective studies to advance clinical translation. PROSPERO CRD420251084894; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251084894.

Protocell fitness under extreme prebiotic conditions is critical in understanding the origin of life. However, little is known about protocell’s survival and fitness under prebiotic radiations. Here we present a radioresistant protocell model based on assembly of two types of coacervate droplets, which are formed through interactions of inorganic polyphosphate (polyP) with divalent metal cation and cationic tripeptide, respectively. Among the coacervate droplets, only the polyP-Mn droplet is radiotolerant and provides strong protection for recruited proteins. The radiosensitive polyP-tripeptide droplet sequestered with both proteins and DNA could be encapsulated inside the polyP-Mn droplet, and form into a compartmentalized protocell. The protocell protects the inner nucleoid-like condensate through efficient reactive oxygen species’ scavenging capacity of intracellular nonenzymic antioxidants including Mn-phosphate and Mn-peptide. Our results demonstrate a radioresistant protocell model with redox reaction system in response to ionizing radiation, which might enable the protocell fitness to prebiotic radiation on the primitive Earth preceding the emergence of enzyme-based fitness. This protocell might also provide applications in synthetic biology as bioreactor or drug delivery system. Protocell’s survival and fitness under prebiotic radiations are elusive. Here, the authors present a radioresistant protocell model based on the assembly of two types of coacervate droplets, formed through interactions of inorganic polyphosphate with manganese and cationic tripeptide, respectively, and show that nonenzymatic Mn antioxidants are essential for its resistance to radiation.

Digital droplet PCR (ddPCR) is a powerful amplification technique for absolute quantification of viral nucleic acids. Although commercial ddPCR devices are effective in the lab bench tests, they cannot meet current urgent requirements for on-site and rapid screening for patients. Here, we have developed a portable and fully integrated lab-on-a-disc (LOAD) device for quantitively screening infectious disease agents. Our designed LOAD device has integrated (i) microfluidics chips, (ii) a transparent circulating oil-based heat exchanger, and (iii) an on-disc transmitted-light fluorescent imaging system into one compact and portable box. Thus, droplet generation, PCR thermocycling, and analysis can be achieved in a single LOAD device. This feature is a significant attribute for the current clinical application of disease screening. For this custom-built ddPCR setup, we have first demonstrated the loading and ddPCR amplification ability by using influenza A virus-specific DNA fragments with different concentrations (diluted from the original concentration to 107 times), followed by analyzing the droplets with an external fluorescence microscope as a standard calibration test. The measured DNA concentration is linearly related to the gradient–dilution factor, which validated the precise quantification for the samples. In addition to the calibration tests using DNA fragments, we also employed this ddPCR-LOAD device for clinical samples with different viruses. Infectious samples containing five different viruses, including influenza A virus (IAV), respiratory syncytial virus (RSV), varicella zoster virus (VZV), Zika virus (ZIKV), and adenovirus (ADV), were injected into the device, followed by analyzing the droplets with an external fluorescence microscope with the lowest detected concentration of 20.24 copies/µL. Finally, we demonstrated the proof-of-concept detection of clinical samples of IAV using the on-disc fluorescence imaging system in our fully integrated device, which proves the capability of this device in clinical sample detection. We anticipate that this integrated ddPCR-LOAD device will become a flexible tool for on-site disease detection.

Circulating tumor cells (CTCs) are single cancer cells or cancer cell clusters that are present in the circulatory system. Assessing CTC levels in patients can aid in the early detection of cancer metastasis and is essential for the purposes of accurate cancer prognosis. However, current in vitro blood tests are limited by the insufficient blood samples and low concentration levels of CTCs, which presents a major challenge for practical biosensing devices. In this work, we propose the first surface plasmon resonance (SPR) fiber probe to work intravenously, which offers a real-time detection of CTCs in bloodstreams. By exposing the protein-functionalized fiber probe to circulating blood, a continuous capture of CTCs ensures a constant increase in enrichment and hence greatly enhances enumeration accuracy. The performance of our plasmonic fiber probe was demonstrated to specifically detect Michigan Cancer Foundation-7 (MCF-7) breast cancer cells in flowing whole mouse blood. Further, a detection limit of ~1.4 cells per microliter was achieved by using an epithelial cell adhesion molecule (EpCAM) antibody-based receptor layer and a 15 min enrichment period. This pilot study validates real-time CTC detection directly in the bloodstream by using plasmonic fiber probes, which exhibit promising clinical potential for in vivo diagnostic tests involving low concentration biomarkers in circulating blood.

Living organisms ranging from bacteria to animals have developed their own ways to accumulate and store phosphate during evolution, in particular as the polyphosphate (polyP) granules in bacteria. Degradation of polyP into phosphate is involved in phosphorus cycling, and exopolyphosphatase (PPX) is the key enzyme for polyP degradation in bacteria. Thus, understanding the structure basis of PPX is crucial to reveal the polyP degradation mechanism. Here, it is found that PPX structure varies in the length of ɑ‐helical interdomain linker (ɑ‐linker) across various bacteria, which is negatively correlated with their enzymatic activity and thermostability – those with shorter ɑ‐linkers demonstrate higher polyP degradation ability. Moreover, the artificial DrPPX mutants with shorter ɑ‐linker tend to have more compact pockets for polyP binding and stronger subunit interactions, as well as higher enzymatic efficiency (kcat/Km) than that of DrPPX wild type. In Deinococcus‐Thermus, the PPXs from thermophilic species possess a shorter ɑ‐linker and retain their catalytic ability at high temperatures (70 °C), which may facilitate the thermophilic species to utilize polyP in high‐temperature environments. These findings provide insights into the interdomain linker length‐dependent evolution of PPXs, which shed light on enzymatic adaption for phosphorus cycling during natural evolution and rational design of enzyme. This study demonstrates an interdomain linker‐based exopolyphosphatase (PPX) structural evolution in bacteria. The length of ɑ‐linker in PPX, which involves phosphate cycling, is varied among bacteria and has impacts on protein's conformation and quaternary structure, thus posing an impact on enzyme activity and thermostability. These results suggest a potential relationship between PPX structural evolution and bacterial environmental adaptability.

Plasmalogens are a special class of polar glycerolipids containing a vinyl-ether bond and an ester bond at sn-1 and sn-2 positions of the glycerol backbone, respectively. In animals, impaired biosynthesis and regulation of plasmalogens may lead to certain neurological and metabolic diseases. Plasmalogens deficiency was proposed to be strongly associated with neurodegenerative and metabolic diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), and appropriate supplement of plasmalogens could help to prevent and possibly provide therapy of these diseases. Plasmalogens evolved first in anaerobic bacteria with an anaerobic biosynthetic pathway. Later, an oxygen-dependent biosynthesis of plasmalogens appeared in animal cells. This review summarizes and updates current knowledge of anaerobic and aerobic pathways of plasmalogens biosynthesis, including the enzymes involved, steps and aspects of the regulation of these processes. Strategies for increasing the expression of plasmalogen synthetic genes using synthetic biology techniques under specific conditions are discussed. Deep understanding of plasmalogens biosynthesis will provide the bases for the use of plasmalogens and their precursors as potential therapeutic regimens for age-related degenerative and metabolic diseases.