Search Results (75)

Background: Urothelial carcinoma requires frequent surveillance because of its high recurrence rate, particularly in patients with non-muscle-invasive disease. Although cystoscopy remains the standard method for diagnosis and follow-up, it is invasive, costly, and associated with patient discomfort. Urinary biomarkers have emerged as potential tools for improving surveillance and reducing unnecessary cystoscopies. Methods: We performed a narrative review of studies published between 2017 and 2026 evaluating urinary biomarkers in urothelial carcinoma. Particular attention was given to assay mechanisms, diagnostic performance, clinical applications, and integration into surveillance techniques. Results: The most extensively studied biomarkers were Xpert Bladder Cancer Monitor, Bladder EpiCheck, ADXBLADDER, and Cxbladder. Most molecular assays demonstrated higher sensitivity than urinary cytology, particularly for the detection of high-grade recurrence. Reported negative predictive values frequently exceeded 95%, suggesting potential utility in identifying patients at low risk of clinically significant recurrence. Xpert Bladder Cancer Monitor and Bladder EpiCheck were supported by the largest body of surveillance evidence, whereas Cxbladder and mutation-enhanced platforms showed promise for risk stratification and individualized follow-up. Evidence supports the use of urinary biomarkers as adjuncts to cystoscopy rather than replacements. Conclusions: Modern urinary biomarkers provide clinically useful information during the surveillance of urothelial carcinoma, especially for excluding high-grade recurrence and assisting the interpretation of equivocal findings. Future biomarker-guided surveillance strategies may reduce the burden of cystoscopy while maintaining oncological safety. Further studies are required to improve specificity and sensitivity in order to fully integrate these biomarkers into diagnostic and follow-up protocols. Full article

Background/Objectives: Copper (Cu²⁺) is an essential trace element that participates as a cofactor in key metabolic enzymes such as cytochrome c oxidase and superoxide dismutase. However, excessive copper exposure can be toxic and disturbances in copper homeostasis have been associated with neurodegenerative diseases including Alzheimer’s and Parkinson’s disease. Despite growing evidence linking copper to neuronal dysfunction, the cellular mechanisms by which Cu²⁺ affects neuronal excitability and neurotransmission remain poorly understood. The aim of this study was to investigate the effects of acute Cu²⁺ exposure on ionic currents involved in cellular excitability and neurotransmitter release in bovine chromaffin cells. Methods: Primary cultures of bovine chromaffin cells were used as a neuroendocrine model to study cellular excitability. Voltage-dependent ionic currents were recorded using the whole-cell patch-clamp technique in voltage-clamp configuration. Catecholamine secretion was monitored by amperometry, and cytosolic Ca²⁺ dynamics were measured in fluo-4-loaded cells during depolarization induced by high K⁺ stimulation. Results: Acute Cu²⁺ exposure produced a concentration-dependent enhancement of depolarization-evoked catecholamine release. In parallel, Cu²⁺ inhibited voltage-dependent calcium (ICa), sodium (INa), potassium (IKv), and calcium/voltage-dependent potassium (IKCa-v) currents in a concentration-dependent and partially reversible manner. In addition, Cu²⁺ increased basal cytosolic Ca²⁺ levels while reducing the amplitude of depolarization-evoked Ca²⁺ transients. Conclusions: Acute Cu²⁺ exposure exerts a dual effect in bovine chromaffin cells, inhibiting the ionic currents that support cellular excitability while potentiating catecholamine secretion. This apparent paradox is consistent with a disruption of intracellular Ca²⁺ homeostasis, in which elevated basal cytosolic Ca²⁺ may facilitate exocytosis despite reduced depolarization-evoked Ca²⁺ entry. These findings provide new insight into the mechanisms by which copper may alter neuronal signaling and contribute to neurotoxicity. Full article

Advances in Industry 4.0 manufacturing have accelerated the adoption of machine learning (ML) for automated classification. Polyester (PES), a widely used synthetic fiber, competes with natural fibers like cotton and other synthetics, highlighting the need for continuous research and improvement. In the textile sector, distinguishing recycled polyester (rPES) from virgin polyester (vPES) remains challenging due to overlapping chemical signatures and material variability. A combination of Fourier transform infrared (FTIR) spectroscopy and ML has not been explored for this purpose. In this study, we evaluated ML models to discriminate three PES fiber types (45 vPES, 65 rPES, and 55 mixed PES) using 165 FTIR spectra across four spectral regions, R1, R2, R3, and R4, as well as their combined representation. Six ML approaches were tested on data reduced with fast independent component analysis (FastICA) (1–30 components) using an 80/20 train–test dataset split. The Decision Tree classifier achieved the highest Accuracy in four of the five spectral evaluations, with classification accuracies ranging from 66.67% to 77.78% for region R4, which also had a balanced classification profile with an area-under-the-curve (AUC) value of 0.81. Notably, despite the moderate overall Accuracy, the model achieved 100% discrimination of rPES when distinguishing it from both mixed and vPES. Mixed fibers remained the most difficult to classify, highlighting the need for improved feature representation. Full article

Dependence on fertilizers limits the sustainability of tropical agriculture. Remineralization using rock byproducts offers a solution that is conditioned by the mineralogical–soil interaction. This study evaluated the agronomic and geochemical potential of a gabbro rock byproduct (GRB) as a bulk amendment in yellow maize (Zea mays L.) cultivation in Atlántico, Colombia. The specific objectives were (1) to characterize the mineralogy and geochemistry of the local GRB; (2) to quantify its neutralizing and fertilizing effect in an acidic Arenosol soil; and (3) to evaluate the biometric response of yellow maize (Zea mays L.) in a field trial. The trial was conducted in an acidic haplic Arenosol (pH 5.4) in 2023, with a 70-day cycle, comparing three management systems: M1 (control), M2 (47 Mg·ha⁻¹ GRB, seed type: ICA-109), and M3 (47 Mg·ha⁻¹ GRB, seed type: V-114). The assessed GRB, with 52.75% SiO₂ and 5.46% CaO, is rich in calcic plagioclase, clinopyroxenes, and zeolites. Application of GRB at 47 Mg·ha⁻¹ in treatment M3 coincided with marked changes in soil properties over the course of the trial, with pH rising from 5.4 to 6.4, cation exchange capacity from 5.0 to 12.1 cmol_c·kg⁻¹, and available phosphorus from 9.8 to 35.0 mg·kg⁻¹. Plants in M3 showed statistically significant increases (p < 0.001) in ear weight (median: 150 g vs. 60.5 g in M1) and in vegetative development. Because the trial was pseudo-replicated, used a high single-dose “shock-loading” rate, involved different maize genotypes across treatments, and covered only one 70-day cycle, these results should be interpreted as exploratory and site-specific. Even so, they indicate that GRB can act as an effective acidity corrector and slow-release multinutrient source under Arenosol conditions, with relevance for circular-economy strategies. Future work should evaluate agronomically doses, include replicated multi-cycle trials, and incorporate comparative and risk-assessment analyses. Full article

The green-making stage is crucial for forming the distinctive aroma and flavor of Tieguanyin tea. Current green-making stage recognition relies on tea makers’ sensory experience, which is labor-intensive and time-consuming. To address these issues, this paper proposes a lightweight automatic recognition model named T-GSR for the accurate and objective identification of Tieguanyin tea green-making stages. First, an extensive set of Tieguanyin tea images at different green-making stages was collected. Subsequently, preprocessing techniques, i.e., multi-color-space fusion and morphological filtering, were applied to enhance the representation of target tea features. Furthermore, three targeted improvements were implemented based on the MobileNet V3 backbone network: (1) an adaptive residual branch was introduced to strengthen feature propagation; (2) the Rectified Linear Unit (ReLU) activation function was replaced with the Gaussian Error Linear Unit (GELU) to improve gradient propagation efficiency; and (3) an Improved Coordinate Attention (ICA) mechanism was adopted to replace the original Squeeze-and-Excitation (SE) module, enabling more accurate capture of complex tea features. Experimental results demonstrate that the T-GSR model outperforms the original MobileNet V3 in both classification performance and model complexity, achieving a recognition accuracy of 93.38%, an F1-score of 93.33%, with only 3.025 M parameters and 0.242 G FLOPs. The proposed model offers an effective solution for the intelligent recognition of Tieguanyin tea green-making stages, facilitating online monitoring and supporting automated tea production. Full article

Current multimodal imaging–based source localization (SoL) methods often rely on synchronously recorded data, and many neural network–driven approaches require large training datasets, conditions rarely met in clinical neuroimaging. To address these limitations, we introduce MieSoL (Multimodal Mutual Information Extraction and Source Localization), a unified framework that fuses EEG and MRI, whether acquired synchronously or asynchronously, to achieve robust cross-modal information extraction and high-accuracy SoL. Targeting neuroimaging applications, MieSoL combines Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG), leveraging their complementary strengths—MRI’s high spatial resolution and EEG’s superior temporal resolution. MieSoL addresses key limitations of existing SoL methods, including poor localization accuracy and an unreliable estimation of the true source number. The framework combines two existing components—Unified Left Eigenvectors (ULeV) and Efficient High-Resolution sLORETA (EHR-sLORETA)—but integrates them in a novel way: ULeV is adapted to extract a noise-resistant shared latent representation across modalities, enabling cross-modal denoising and an improved estimation of the true source number (TSN), while EHR-sLORETA subsequently performs anatomically constrained high-resolution inverse mapping on the purified subspace. While EHR-sLORETA already demonstrates superior localization precision relative to sLORETA, replacing conventional PCA/ICA preprocessing with ULeV provides substantial advantages, particularly when data are scarce or asynchronously recorded. Unlike PCA/ICA approaches, which perform denoising and source selection separately and are limited in capturing shared information, ULeV jointly processes EEG and MRI to perform denoising, dimension reduction, and mutual-information-based feature extraction in a unified step. This coupling directly addresses longstanding challenges in multimodal SoL, including inconsistent noise levels, temporal misalignment, and the inefficiency of traditional PCA-based preprocessing. Consequently, on synthetic datasets, MieSoL achieves 40% improvement in Average Correlation Coefficient (ACC) and 56% reduction in Average Error Estimation (AEE) compared to conventional techniques. Clinical validation involving 26 epilepsy patients further demonstrates the method’s robustness, with automated results aligning closely with expert epileptologist assessments. Overall, MieSoL offers a principled and interpretable multimodal fusion paradigm that enhances the fidelity of EEG source localization, holding significant promise for both clinical and cognitive neuroscience applications. Full article

Background: Staphylococcus aureus is a major zoonotic and foodborne pathogen with substantial One Health implications, yet its prevalence, resistance, and virulence potential within the aquaculture sector in Nigeria remains poorly characterized. Objectives: To supplement existing information, this current study investigated the prevalence, clonal distribution, antimicrobial resistance, and virulence gene profiles of S. aureus isolates from fish, fish water, and occupationally exposed fish handlers in Anambra State, Southeast Nigeria. Methods: A total of 607 samples—comprising 465 surface swabs from raw and processed fish, 36 fish water samples, and 106 nasal swabs from fish handlers—were processed using selective culture, biochemical tests, antimicrobial susceptibility testing, DNA microarray analysis, spa typing, and SCCmec typing. Results: S. aureus was recovered from 16.5% (100/607) of the samples. Fourteen (14%) isolates were methicillin-resistant (MRSA), harboring mecA and SCCmec types IV and V, with a combined MRSA prevalence of 2.3%. Multidrug resistance was observed in 52.2% of isolates (mean Multiple Antimicrobial Resistance index: 0.23), with 19 resistance genes spanning nine antimicrobial classes—including heavy metal and biocide resistance. Twenty-eight spa types across 13 clonal complexes (CCs) were identified, with CC1, CC5, and CC8 predominating. The detection of shared spa types between fish and handlers indicates potential cross-contamination. Detected virulence genes included those for accessory gene regulators (agrI-IV), Pantone–Valentine leucocidin (lukFS-PV), toxic shock syndrome (tsst-1), hemolysins (hla, hlb, hld/hlIII, hlgA), biofilm formation (icaA, icaD), immune evasion (chp, scn, sak), enterotoxins (sea, seb, sec, sed, egc, and others), exfoliative toxins (etA, etB), epidermal cells differentiation (edinA, edinB), and capsular types (cap5, cap8). Conclusions: This study reveals that the aquaculture sector in Southeast Nigeria serves as a significant reservoir of genetically diverse, multidrug-resistant S. aureus strains with robust virulence profiles. These findings highlight the necessity of integrated One Health surveillance and targeted interventions addressing antimicrobial use and hygiene practices within aquatic food systems. Full article

The integration of nanomaterials within hydrogel scaffolds offers significant promise in bone tissue engineering by improving mechanical performance and modulating cellular responses through mechanotransductive and biochemical signaling. Previous studies have demonstrated that nanodiamonds (NDs) incorporated in electrospun microfibrillar meshes enhance cellular adhesion, spreading, and cytoskeletal organization through localized mechanical reinforcement. However, the effects of ND loading into soft, bioinert three-dimensional hydrogel matrices remain underexplored. Here, we developed nanostructured 3D printing inks composed of gellan gum (GG) supplemented with a low content of ND nanoadditive (0–3% w/v). ND integration improved the shear-thinning properties of the formulation, enabling consistent filament formation and reliable extrusion-based 3D printing. Structural and mechanical assessments confirmed enhanced scaffold morphology, reduced deformation, and improved morphostructural integrity under compression and increased local stiffness at 2% ND loading (GG_ND2%). Biological assessments revealed that increasing ND content enhanced murine preosteoblast viability, proliferation, and attachment, particularly in GG_ND2%. Furthermore, bioactivation of the GG_ND2% formulation with icariin (ICA), a bioflavonoid known for its osteogenic and angiogenic activity, amplified the beneficial cellular responses of MG-63 cells to ND loading, promoting enhanced surface mineralization and improved cell–matrix interactions. Collectively, these findings highlight the potential of ND-reinforced GG scaffolds bioactivated with ICA, integrating structural reinforcement and biological functionalities that may support osteogenic responses. Full article

Human embryonic stem cell-derived cardiomyocytes (hESC-CMs) tend to show a mixed population of action potential (AP) types, including atrial-like (A-like) and ventricular-like (V-like) APs. In the present study, we investigated the membrane currents underlying these two AP types in hESC-CMs. These were generated using standard (Std) and retinoic acid (RA)-based differentiation protocols. Patch clamp methodology was used to correlate AP morphology with major cardiac ion currents by applying alternating current and voltage clamp protocols to each cell, and to measure L-type Ca²⁺ current (I_Ca,L) and Na⁺-Ca²⁺ exchange current (I_NCX) in detail, whereas Ca²⁺ transients were measured ratiometrically using Indo-1. A- and V-like APs were found in both Std and RA-treated hESC-CMs and the AP plateau amplitude (AP_plat), as a measure of fast phase-1 repolarization, appeared the best AP criterion to separate these two AP types. Traditional voltage clamp experiments revealed a significantly smaller I_Ca,L density in RA-treated hESC-CMs, as well as larger densities of the transient outward and delayed rectifier K⁺ currents (I_to1 and I_K, respectively), without changes in the inward rectifier K⁺ current (I_K1). The AP_plat showed strong and moderate correlations with the densities of I_Ca,L and I_K, respectively, in the absence of a clear-cut correlation with the density of I_to1. Using pre-recorded, typical A- and V-like APs, AP clamp demonstrated that the I_Ca,L-mediated Ca²⁺ influx during the V-like AP in Std hESC-CMs is 3.15 times larger than the influx during the A-like AP in RA-treated hESC-CMs. Ca²⁺ transients of A-like hESC-CMs have a lower diastolic and systolic level, as well as a lower amplitude, than those of Std hESC-CMs, while their duration is shorter due to enhanced SERCA activity. In conclusion, I_Ca,L is an important determinant of the differently shaped A- and V-like APs in hESC-CMs. Furthermore, the Ca²⁺ homeostasis differs between A- and V-like hESC-CMs due to the smaller I_Ca,L and enhanced SERCA activity during A-like APs, resulting in a strongly reduced Ca²⁺ influx, which will cause a substantial reduction in I_NCX, further contributing to the shorter A-like APs. Full article

Combining antibiotics with propolis is an effective method to combat bacterial drug resistance. Nanoparticles are of interest in the antimicrobial field because of their higher drug stability, solubility, penetration power, and treatment efficacy. In this study, propolis nanoparticles (PNPs) were synthesized, and their antibacterial and anti-biofilm activities against methicillin-resistant Staphylococcus aureus (MRSA) in combination with ampicillin sodium (AS) were analyzed. The PNPs had an average particle diameter of 118.0 nm, a polydispersity index of 0.129, and a zeta potential of −28.2 mV. The fractional inhibitory concentration indices of PNPs and AS against tested MRSA strains highlighted this synergy, ranging between 0.375 and 0.5. Crystal violet staining showed that combined PNPs and AS significantly inhibited biofilm formation and reduced existing biofilm biomass. We then discovered that PNPs inhibited bacterial adhesion, extracellular polysaccharide synthesis, and mecR1, mecA, blaZ, and icaADBC gene expression. These results indicated that PNPs exerted a synergistic antibacterial effect with AS by inhibiting mecR1, mecA, and blaZ gene expressions to reduce the drug resistance of MRSA. Meanwhile, PNPs weakened bacterial adhesion and aggregation by suppressing icaADBC gene expression, allowing antibiotics to penetrate the biofilm, and exhibiting significant synergistic anti-biofilm activity. In summary, PNPs are promising candidates for combating MRSA-related diseases. Full article

L-type Ca²⁺ channels, particularly Ca_V1.2, play a crucial role in cardiac excitation-contraction coupling and are known to exhibit mechanosensitivity. However, the mechanisms regulating their response to mechanical stress remain poorly understood. To investigate the mechanosensitivity and nitric oxide (NO)-dependent regulation of L-type Ca²⁺ channels in rat ventricular cardiomyocytes, we used RNA sequencing to assess isoform expression and whole-cell patch-clamp recordings to measure L-type Ca²⁺ current (I_Ca,L) under controlled mechanical and pharmacological conditions. RNA sequencing revealed predominant expression of Ca_V1.2 (TPM: 0.1170 ± 0.0075) compared to Ca_V1.3 (0.0021 ± 0.0002) and Ca_V1.1 (0.0002 ± 0.0002). Local axial stretch (6–10 μm) consistently reduced I_Ca,L in proportion to stretch magnitude. The NO donor SNAP (200 μM) had variable effects on basal I_Ca,L in unstretched cells (stimulatory, inhibitory, or biphasic) but consistently restored stretch-reduced I_Ca,L to control levels. Ascorbic acid (10 μM), which reduces S-nitrosylation, increased basal I_Ca,L and partially restored the reduction caused by stretch, implicating S-nitrosylation in channel regulation. The sGC inhibitor ODQ (5 μM) decreased I_Ca,L in both stretched and unstretched cells, indicating involvement of the NO–cGMP pathway. Mechanical stress modulates L-type Ca²⁺ channels through a complex interplay between S-nitrosylation and NO–cGMP signaling, with S-nitrosylation playing a predominant role in stretch-induced effects. This mechanism may represent a key component of cardiac mechanotransduction and could be relevant for therapeutic targeting in cardiac pathologies involving mechanically induced dysfunction. Full article

A de novo missense variant in KCNH3 has been identified in a patient with neurological symptoms including seizures. Here, we confirm the previously reported loss-of-function features for the associated Kv12.2 mutant A371V and investigate the underlying mechanism. Loss of function was not rescued by low temperature during channel biogenesis. Elevated external K⁺ reduced the rectification of Kv12.2 conductance as predicted by the GHK current equation, allowing the detection of currents mediated by homomeric A371V Kv12.2 channels and a detailed biophysical analysis of the mutant. Compared to wild-type, the voltage dependences of activation and deactivation of A371V Kv12.2 channels were shifted in the positive direction by 15 to 20 mV. Moreover, A371V Kv12.2 channels exhibited accelerated inactivation kinetics combined with a dramatic negative shift in the voltage dependence of inactivation by more than 100 mV. Even in heteromeric wild-type + A371V Kv12.2 channels, inactivation was enhanced, leading to a significant current reduction at physiological potentials. Our Kv12.2 data show similarities to Kv11 channels regarding C-type inactivation and differences regarding the sensitivity to external K⁺ and pharmacological inhibition of inactivation. The gating modification caused by the A371V amino acid substitution in Kv12.2 renders loss of function voltage-dependent, with a possible impact on neuronal excitability and firing behavior. Full article

Staphylococcus aureus and coagulase-negative staphylococci (CNS) are the main causative agents of mastitis in sheep. Their ability to form biofilms in vivo is considered an important virulence factor underlying mastitis outbreaks refractory to antibiotic treatments. Furthermore, pre- and postdipping immersion during milking in iodine substances could determine the presence of residues in milk and therefore represent a health risk factor for consumers. The aim of this study was to evaluate the antibacterial and biofilm inhibitory activity of Thymus vulgaris L. essential oil (TEO) against staphylococci strains isolated from ovine clinical mastitis. In particular, 3 reference strains (S. aureus 25923 and 11623 and S. epidermidis 12228) and 12 clinical isolates (6 S. aureus and 6 CNS) were used. TEO solutions, from a concentration of 1% (v/v) to 1.25% (v/v), corresponding to 9.28–2.32 mg/mL, were obtained after solubilization in 10% dimethyl sulfoxide (DMSO) and used to evaluate the bacterial time-kill compared to that of an iodine-based solution. Antibacterial efficacy was then assessed by the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC), while biofilm inhibition was assessed by minimum biofilm inhibitory concentration (MBIC) using a spectrophotometer at a wavelength of 570 nm. Additionally, biofilm-associated genes (icaA and icaD) were evaluated in all tested strains by PCR. The tested TEO concentrations were able to significantly and prominently reduce bacterial growth compared to controls, as demonstrated by bacterial time-kills. The MIC value was obtained at a concentration of 0.50% (v/v) for a single coagulation-positive isolate (S. aureus (f)) and at a concentration of 0.25% (v/v) for all other isolates. TEO showed effective bactericidal action with a 99.9% reduction in CFU/mL of all isolates in the MBC test at a concentration of 0.25% (v/v) for most of the tested strains. Furthermore, a marked inhibition in biofilm formation at all tested concentrations was observed, with MBIC value of 0.25%. All S. aureus tested were biofilm-producing strains and positive for icaA and icaD genes, while two CNS biofilm-producing strains were negative for both genes. These preliminary results suggest that TEO could be a promising alternative as an udder disinfectant during milking practices. Although in vivo studies are needed to confirm the efficacy and safety of TEO as an adjuvant in the prevention and treatment of udder infections, TEO could help counteract the emergence of antimicrobial resistance and reduce the potential risk of iodine residues in milk. Full article

Vaccinium corymbosum is one of the main sources of commercialized blueberries across the world. This species has a large number of distinct cultivars, leading to significantly different berries characteristics such as size, sweetness, production rate, and growing season. In this context, accurate cultivar discrimination is of significant relevance, and currently, it is mostly performed through berries examination. In this work, we developed a method to discriminate 19 cultivars from the V. corymbosum species through their leaves’ near-infrared spectra. Spectra were acquired from fresh blueberry leaves collected from two geographic regions and across three seasons. Machine-learning-based models, selected from a pool of 10 classifiers based on their discrimination power under a twofold stratified cross-validation process, were trained/tested with 1 to 20 components obtained by the application of data dimensionality reduction (DDR) techniques (dictionary learning, factor analysis, fast individual component analysis, and principal component analysis) to different near-infrared (NIR) spectra regions’ data, to either analyze a single spectral region and season or combine spectral regions and/or seasons for each side of the blueberry leaf. The percentage of correct cultivar discrimination ranged from 52.27 to 100%, with the best spectral results obtained with the adaxial side of the leaves in the fall (100% $Accuracy$) and the abaxial side of the leaves in the winter (100% $Accuracy$); the fast ICA DDR technique was present in 83.33% of the best analyses (five out of six); and the LinearSVC was present in 66.67% (four out six best analyses). The results obtained in this work denote that near-infrared spectroscopy is a suitable and accurate technique for V. corymbosum cultivar discrimination. Full article

This study seeks to develop and implement a non-enzymatic fluorescent labeling for immunoassay and immunochromatographic assay (ICAs) targeting SARS-CoV-2, to meet the extensive interest and need for effective COVID-19 diagnosis. In this manuscript, we delineate the development, synthesis, and evaluation of a novel quinone polymer zinc hybrid nanoarchitecture, referred to as polymerized alizarin red–inorganic hybrid nanoarchitecture (PARIHN), which integrates an antibody for direct use in fluorescent immunoassays, offering enhanced sensitivity, reduced costs, and improved environmental sustainability. The designed nanoarchitecture can enhance the sensitivity of the immunoassay and enable rapid results without the complexities associated with enzymes, such as their low stability and high cost. At first, a chitosan–alizarin polymer was synthesized utilizing quinone–chitosan conjugation chemistry (QCCC). Then, the chitosan–alizarin polymer was embedded with the detection antibody using zinc ion, forming PARIHN, which was proven to be a stable label with the ability to enhance the assay stability and sensitivity of the immunoassay. PARIHN can react with phenylboronic acid (PBA) or boric acid through its alizarin content to produce fluorescence signals with an LOD of 15.9 and 2.6 pm for PBA and boric acid, respectively, which is the first use of a boric acid derivative in signal generation in the immunoassay. Furthermore, PARIHN demonstrated high practicality in detecting SARS-CoV-2 nucleoprotein in fluorescence (PBA and boric acid) systems with an LOD of 0.76 and 10.85 pm, respectively. Furthermore, owing to the high brightness of our PARIHN fluorogenic reaction, our labeling approach was extended to immunochromatographic assays for SARS-CoV-2 with high sensitivity down to 9.45 pg/mL. Full article