Silk artifacts are commonly dyed with natural dyes, the composition of which reflects their historical context. In this study, silver nanoparticles (AgNPs) were modified with KI solution at room temperature to produce KI-functionalized Surface-enhanced Raman spectroscopy (SERS) substrates. The optimized substrate, prepared at a 3:1 ratio AgNPs-to-KI ratio solution, exhibited superior localized surface plasmon resonance (LSPR) properties, which significantly increased Raman signals of dye molecules while effectively reducing background interference from the substrate. The relative standard deviations (RSD) of alizarin as a molecular probe was 3.47 %, with an enhancement factor (EF) of approximately 6.16 × 10. SERS reference fingerprint spectra were established for five representative anthraquinone natural dyes: dyer's madder (Rubia tinctorum), Indian madder (Rubia cordifolia), Japanese madder (Rubia argyi), lac insect (Kerria lacca) and cochineal (Dactylopius coccus). The method was then applied to analyze dyes in silk artifacts from the collection of the Hungarian Museum of Applied Arts, where alizarin, purpurin, and laccaic acid were detected in a single silk fiber. The proposed KI-AgNPs SERS technique provides a minimally invasive, rapid, reliable and highly specific tool for identifying trace natural dyes in silk artifacts.

Atractylodis Macrocephalae Rhizoma (AMR) is classified as a medicinal and edible homologous food in China. Based on the fusion of multi-source information, this study comprehensively reveals the changing patterns of appearance, texture and composition of AMR during thermal processing. The processing treatments gradually altered the hue (H), saturation (S), and value (V) of the samples, significantly increased the textural heterogeneity of charred samples, and affected the retention or transformation of key components like water and atractylenolide. Additionally, the near-infrared (NIR) spectra showed notable differences in intensity and response patterns between 1550 and 1950 nm. Using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), a separation trend among samples was noted, identifying 8 key variables that differentiate the varieties, including S-value, contrast, atractylenolide II, the 1906.8-1949.2 nm range and etc. After reconstructing composite features using multivariate statistical analysis, the Osprey Optimization Algorithm (OOA) optimized the Back Propagation (BP) model's hyperparameters, resulting in the OOA-BP classification model. This model demonstrated a 100 % accuracy rate in identifying AMR and its thermally processed products across both training and testing datasets. The study provides a scientific foundation and introduces a new framework for medicinal food quality control, improving functionality and enabling quick identification of processed AMR products.

In the field of point-of-care testing (POCT), the rapid and sensitive detection of Mycoplasma pneumoniae is essential for the early diagnosis and prognosis. However, current testing methods are primarily qualitative and require sophisticated instrumentation. Herein, we present a POCT platform that integrates enzymatic recombinase amplification (ERA) and microsphere lateral flow strips (LFS) with high-fluorescence intensity, employing a dual-signal amplification approach to achieve rapid and sensitive detection of Mycoplasma pneumoniae, which is called the Smartphone-based ERA-LFS Integrated Device (SELID). Concurrently, smartphone readout software has been developed to realize image enhancement, as well as the recognition of control and test lines via designed algorithms for quantitative analysis and subsequent data processing. The platform can complete the assay within 25 min, achieving high specificity and sensitivity, with the ability to detect as low as 10 copies/μL. In addition, we added Mycoplasma pneumoniae strains to saliva to simulate clinical samples to verify the detection ability of SELID in real samples. Experimental findings demonstrated strong concordance between SELID and the conventional PCR assay, exhibiting good feasibility and stability. These results indicate that SELID has significant potential as a simple, rapid, and sensitive diagnostic platform for the immediate detection of Mycoplasma pneumoniae and other pathogens.

Microneedles (MNs) have rapidly emerged as powerful tools in wearable biosensing, providing minimally invasive access to interstitial fluid (ISF). Among the neurodegenerative based biomarkers detectable in ISF, phosphorylated Tau at threonine 181 (p-Tau181) is reaching a clinically evaluable significance for Alzheimer's disease (AD) and other tauopathies. Elevated p-Tau181 levels are strongly correlated with abnormal Tau aggregation in the brain and with cognitive decline. Current diagnostic methods rely on invasive cerebrospinal fluid (CSF) sampling or costly laboratory immunoassays and radio-imaging which are unsuitable for routine or point-of-care screening. Here, we present a highly sensitive colorimetric microneedle-based immunosensor designed for non-invasive, transdermal detection of p-Tau181. For the first time, gold nanoparticles (AuNPs) are integrated into a three-dimensional (3D) microneedle geometry, where antibody antigen recognition occurs directly on MN in contact with ISF. The aggregation-induced optical shifts of AuNPs provide an immediate and instrument-free colorimetric signal, while two optimized coating techniques enable uniform immobilization and reproducible performance. The MN-AuNP platform achieves a limit of detection (LoD) of 16 pg/mL, a nearly 30-fold improvement compared to the reported 2D surface (460 pg/mL). This enhancement shoots from the 3D architecture, which offers greater surface area, enhanced probe loading, and improved analyte diffusion. Compared with existing diagnostic approaches, the proposed system offers multiple advantages: non-invasive operation, real-time readout without complex instrumentation, low fabrication cost, and potential integration into wearable or point-of-care formats. Collectively, these results lay the groundwork for advanced MN-based colorimetric biosensors for early Alzheimer's disease detection through accessible and patient-friendly neurodiagnostic technologies.

Doxorubicin, as an anthracycline antibiotic, is a commonly used and effective chemotherapeutic agent for treating various malignancies. However, it has a narrow therapeutic window. Therefore, real-time monitoring of doxorubicin concentration in chemotherapy patients is essential for enhancing treatment efficacy, minimizing side effects, and ensuring patient safety. In this paper, we proposed a TiC MXene-sensitized fiber surface plasmon resonance (SPR) doxorubicin sensor. By covalently functionalizing the reflective SPR sensing structure with TiC MXene, the refractive index sensitivity increased by 60.0 %. Furthermore, by covalently modifying the doxorubicin-specific aptamer, the sensor achieves high sensitivity and high specificity in the detection of doxorubicin. Within the linear range of 10-100 μM, it demonstrates a sensitivity of 0.24 nm/μM and a limit of detection of 2.79 μM. Furthermore, experiments confirmed that the doxorubicin sensor exhibits excellent specificity and can be applied for the detection of doxorubicin in real serum samples. The proposed doxorubicin sensor offers benefits such as high sensitivity, high specificity, fast response, and small size, and has the potential to meet the clinical requirements for monitoring doxorubicin concentration in chemotherapy patients.

Ghrelin, as a hunger hormone and regulator responsible for appetite, is an important biomarker in metabolic research and potentially in clinical diagnostics. The aim of the study was to design and construct a new biosensor which uses a carboxymethyl dextran matrix and a streptavidin/biotin-based capture strategy for selective, label-free detection of ghrelin using SPRi (Surface Plasmon Resonance imaging) technique. Its selectivity, repeatability, and accuracy were verified and proved highly reliable. The analytical performance of the sensor was characterized by a low detection limit (17 pg/mL) and a quantification limit (52 pg/mL). Furthermore, it was tested on serum samples from patients with type 1 diabetes and a healthy control group. The results obtained were compared with the classic ELISA method, showing high consistency and repeatability of measurements. The proposed biosensor represents a "golden mean" between costly (e.g. reduction in analysis time and minimal sample consumption) and technically demanding analyses while still maintaining adequate sensitivity and specificity of the determination methods.

Accurate classification of aluminum alloys with minor compositional differences remains a challenge for laser-induced breakdown spectroscopy (LIBS) due to spectral similarity and matrix effects. Herein, we propose a time-frequency dual-domain enhanced acoustic processing (TFDEAP) model to amplify the subtle physical differences in laser-induced plasma acoustic waves. By fusing TFDEAP-enhanced acoustic features with LIBS spectra, we establish a multimodal classification framework. This method significantly enhances the classification performance of five challenging aluminium alloys, with substantial improvements in classification accuracy. The most notable enhancement was observed with SVM, where accuracy rose from 52.00 % (LIBS-only) to 84.67 %. RF achieved the optimal AUC, increasing from 0.771 to 0.977. Although PLS-DA had already achieved a baseline classification accuracy of 67.33 %, significant improvement was attained following optimization by this method, ultimately yielding a classification accuracy of 82.67 %. The TFDEAP model effectively mitigates spectral confusion by extracting complementary physical information from acoustic signals, providing a robust foundation for high-precision, non-destructive material identification in recycling and manufacturing.

There remain great challenges in improving amplification efficiency and detection specificity of enzymatic biosensing platforms for genetic disease diagnosis. Herein, we constructed a single probe-based intelligent nanomachine (ESINM) to amplify cancer-related nucleic acids through engineered self-driven multiple cycles based on target-mediated knock-on effect. Strategically, to make the most of each base, the well-designed versatile ESINM probe is made up of eight functional regions to implement target and enzyme recognition, intramolecular configuration transformation, signal amplification. The free ESINM probe, like a dormant seed, remains a stable quenching hairpin structure with recognition function and allosteric activity restrained. Once the nicking-mediated cyclical strand-displacement polymerization between the target and ESINM probe is carried out to generate two types of key nicking fragments (NFs), a series of knock-on intermolecular and intramolecular priming-directed strand replication/nicking/displacement circuits spontaneously occur among NFs, ESINM probe, and all other intermediates, in which a dramatic stream of NFs of interest flow out instead of depleting. As a result, fluorescent DNA dendrimer like shining vine is formed. In such a high-efficient magnification way, the target can be tested down to 1 × 10 nM within 80 min with a detection limit of 479 × 10 nM. This one-step, mix-to-detection, one probe-involved biosensor without any wasted species possesses outstanding point mutation recognition ability and practical availability in biological samples, exhibiting great potentials in biochemical analysis and early diagnosis of genetic diseases.

The intake of selenium (Se) is beneficial only in a small range of concentrations, so there is an urgent need for rapid and accurate detection of selenium-enriched agricultural products. The detection of Se by conventional laser-induced breakdown spectroscopy (LIBS) is challenging due to its difficulty to excite and observe. In this work, a method was proposed by integrating a chopper with the photomultiplier tube (PMT), utilizing delayed triggering to achieve precise time control of the signals. This method not only could selectively detect the signals from the plasma, but also could avoid the interference of bremsstrahlung and interfering elements under wide bandpass conditions. The signal with no delay time was determined based on the kurtosis of the output signal from PMT. The ratio of the signal of Se to that of other interfering elements was improved by adjusting the delay time. The quantitative results and stability were greatly improved, with an R of 0.991 and an average relative standard deviation (ARSD) of 14.2 %. For the first time, the limit of detection (LOD) of solid samples was improved to less than 2 ppm, providing a reliable and advanced method for the detection of selenium-enriched agricultural products.

Electronic nose is an emergent technique for noninvasive disease detection via breath analysis, which is, however limited by the sensitivity and selectivity of the sensor array to complex biomarkers. In this study, we developed a hybrid sensor array to identify various biomarkers of different respiratory diseases, providing a rapid and convenient diagnostic method. Five on-chip microsensors were fabricated and combined with 11 commercial sensors to achieve enhanced sensitivity and complementary selectivity for multiple biomarkers. The array performances were significantly improved by globally optimizing the operating temperatures with machine learning, which enabled the precise identification of six key biomarkers (isoprene, n-propanol, toluene, acetaldehyde, acetone, and nitric oxide) from three respiratory diseases (lung cancer, asthma, and COVID-19). The classification mean accuracy for these biomarkers under concentration variations reached 98.9 % with 5-fold cross-validation, and the R values exceeded 97 % for concentration prediction. Furthermore, tests on exhaled breath validated our array's effectiveness on simulated disease diagnosis, achieving mean classification accuracy of 92.1 % with 5-fold cross-validation. The exceptional capability of the hybrid sensor array in gas discrimination and disease-specific pattern recognition highlights its potential for exhaled breath tests in clinical and home healthcare.

As a widely used drug for treating peripheral vascular and ischemic cerebrovascular diseases, the accurate sensing of pentoxifylline (PTX) is crucial for pharmaceutical quality control and therapeutic drug monitoring. In this study, folic acid-functionalized carbon dots (FA-CDs) were synthesized for the "turn-on" fluorescence detection of PTX base on a novel hydrogen bond-mediated surface microenvironment regulation strategy. Upon excitation at 600 nm, the FA-CDs showed maximal fluorescence emission wavelength at 648 nm. The fluorescence of FA-CDs was quenched in aqueous solution with a low quantum yield (QY) of 0.9 %. Upon addition of PTX, the water molecules around FA-CDs were excluded by PTX due to the efficient hydrogen bonds formed between FA-CDs and PTX, resulting in a transition of the surface microenvironment of FA-CDs from water-rich to water-lean state. This change dramatically enhanced the QY of FA-CDs from 0.9 % to 15.85 %. The FA-CDs nanosensor exhibited a fast and selective response to PTX, displaying a good linear range from 0.05 to 1.00 mM and a detection limit of 8.15 μM. Furthermore, the recovery values of this developed method ranged from 95.78 % to 104.06 % in pharmaceuticals, urine and plasma samples, with relative standard deviations ranging from 0.53 % to 4.49 %, indicating this method's high precision and accuracy for PTX detection. This work represents the first example of a fluorescence sensor for PTX detection and provides a promising candidate for practical applications in the field of medicine. The hydrogen bond-mediated surface microenvironment regulation strategy offers an innovative approach for probe design in future.

Long afterglow materials are advantageous for autofluorescence imaging because they do not require real-time excitation. However, long afterglow materials still have limitations, such as uncontrollable size and single luminescent function. It is essential to further design the size and composite structure of long afterglow materials according to specific application requirements. In this study, long afterglow materials were precisely controlled and optimized in terms of their size and luminescence, serving as the core of the imaging carrier (ZGGO) and enhancing the photothermal effect. After further combining with GSH depletion and cuproptosis strategy, a three-layer core-shell structure (ZGGO@SS@Cu/ZIF-8-ICG:DC_AC50@HA, ZSIDH) was formed, measuring less than 200 nm. It is worth mentioning that ZSIDH elicited minimal to no inflammatory response in the eyes of tumor-bearing mice after a 2-week therapy, and the tumors were almost completely cured, highlighting its excellent biocompatibility and therapeutic efficacy in vivo. Comprehensive experimental findings demonstrate that precisely regulated long afterglow materials hold tremendous application potential in tumor therapy, even within the complex structural environment of the eyeball.

Artists commonly use a relatively reduced palette of pigments and mix them in different proportions to increase the gamut of colors present on artworks. In this study, a complete workflow for pigment identification using spectral unmixing of reflectance spectra in the visible and near infrared is presented. The algorithm includes superpixel segmentation as pre-processing to reduce the number of spectra that are unmixed. Then, a pre-extracted set of relevant color instances from the painting is used to build an adaptive subset of candidate pigments from a reference palette, and pigment identification is achieved by superpixel voting within the reduced subsets corresponding to the automatically extracted endmembers presence maps. Two different moments in time of a Maternity of the 16th century (original and restored) and a modern replica of the same painting are used to showcase the performance of the algorithm, which is able to correctly identify 80 % of the pigments present from a reference library of 23 pigments, taking less than three minutes for processing around 7000 spectra.

The non-proteinogenic amino acid β-cyano-l-alanine (AlaCN) is a plant toxin formed during HCN detoxification. The presence of AlaCN and its dipeptide, γ-glutamyl-AlaCN (Glu-AlaCN), in the agriculturally important vetch (Vicia sativa) is a matter of concern, as these compounds can be harmful to animals fed with vetch. In addition, adulteration of lentils with vetch has occurred, posing a risk for human consumers. AlaCN and Glu-AlaCN have been determined by HPLC which, however, does not meet the general need for low-cost, simple analytical methods suitable for developing assay kits or sensors. Therefore, the aim of this study was to propose a simple, rapid and inexpensive colorimetric assay for AlaCN. The assay is based on an artificial cascade reaction catalyzed by nitrilase NIT4 (EC 3.5.5.1), NAD-dependent aspartate dehydrogenase (EC 1.4.1.21) and, optionally, asparaginase (EC 3.5.1.1). The NADH formed in the final step is determined at 460 nm using 2-(2-methoxy-4-nitrophenyl)-3-(4-nitrophenyl)-5-(2,4-disulfophenyl)-2H-tetrazolium monosodium salt (WST-8) and 1-methoxy-5-methylphenazinium methyl sulfate. In summary, the first colorimetric AlaCN test based on a multistep enzymatic reaction was proposed, with parts of it applicable as a colorimetric L-Asp test. Both tests have a limit of detection of approximately 1.4 μM. The AlaCN test enabled us to clearly distinguish between the spiked and non-spiked samples, as well as between lentils and vetch. Future work may focus on optimizing sample preparation and assay conditions to maximize responses and eliminate matrix effects, while saving material and time. This may be extended to the development of a new test for L-Asn, a precursor of acrylamide.

Construction of magnetic nanotubes and transition metal ion generated by acid etching from its own surface (defined as "self-released" systems) can effectively address the issues of complex operation and poor adsorption performance associated with traditional immobilized metal affinity chromatography (IMAC) materials. Based on the magnetic Ni core and polydopamine (PDA) shell, a core-shell structured Ni@PDA magnetic composite nanotubes and their acid-etched product (defined as Ni@PDA-T) were developed and synergistically provided excellent magnetic responsiveness, low cell toxicity and more active sites, enabling efficient magnetic separation and surface Ni self-release. Surface self-released Ni enabled coordinate capture of histidine-rich proteins without requiring exogenous metal ion supplementation after fixed onto PDA with pH 8.0, simplifying operation and enhancing adsorption efficiency. Given the differences in histidine content among Bovine hemoglobin (BHb), Bovine serum albumin (BSA), and Lysozyme (LYZ), Ni@PDA-T exhibited a maximum adsorption capacity of 4556 mg g for BHb, which is rich in histidine residues. Density functional theory (DFT) calculations indicate that p-d orbital coordination interactions dominate the Histidine (His) protein's immobilization onto the Ni site and result in superior adsorption behavior for the His protein by DOPAm-Ni functional group. SDS-PAGE analysis of mixed protein systems and actual bovine blood samples further confirmed the selective adsorption of BHb by Ni@PDA-T. Chelator-free blood purification was achieved through synergistic coordination between self-released Ni and histidine residues, overcoming the reliance on traditional chelating agents.

Accurate and rapid on-site detection of cadmium (Ⅱ) ions (Cd) in environment is crucial for protecting ecological environment and human health. This study developed an electrochemical sensor for Cd detection, based on a laser-induced aramid nanofiber (ANF) film for the in-situ generation of three-dimensional porous graphene. This ANF-based graphene, obtained through precise control of two-step laser process using 450 nm laser, exhibits enhanced graphitization, a denser structure, and superior electrochemical properties. On the basic of laser-induced graphene (LIG) technology, the resulting electrochemical sensor demonstrated excellent performance in detecting trace Cd. The sensor showed a linear detection range of 1.0-100.0 μg L and a detection limit of 0.37 μg L for Cd (S/N = 3), along with good stability and reproducibility. Furthermore, when applied to the detection of Cd in actual lake water samples, the sensor exhibited satisfactory recovery rates ranging from 95.21 % to 98.24 %. These results demonstrate the successful fabrication of a portable, highly sensitive LIG electrochemical sensor based on ANF. The resulting sensor exhibits excellent electrochemical performance, enabling high sensitivity for Cd detection. Beyond its analytical capabilities, this work signifies a notable advancement in LIG preparation methods using ANF. This innovative approach provides a novel pathway for developing high-performance and on-site detection devices.

Radiocarbon (C) is one of the key isotopes in the field of nuclear environmental protection. This difficult-to-measure isotope constitutes a substantial proportion of the nuclear industry's dose contribution, underscoring the imperative for precise measurement in regions loaded by C emissions. The currently used technologies such as accelerator mass spectrometry (AMS) and liquid scintillation counting (LSC) techniques are capable of determining the exact C content or ratio of C-enriched samples. However, the evolving, laser-based spectroscopic methods, such as Saturated-absorption CAvity Ring-down (SCAR) technology, may offer a fast, reliable, and cost-effective alternative for the analysis of lightly labeled carbonaceous materials or slightly C-enriched environmental and plant samples. The C-enriched plant samples examined in the study demonstrated that the SCAR method is capable of reproducing AMS measurement results with a difference of less than 4 % when measured from the same gas after δC correction. This study constitutes the inaugural demonstration and practical exemplification of subsamples formed from the same CO gas, after the combustion, being measured by AMS, SCAR, and Isotope Ratio Mass Spectrometry (IRMS) for C/C and C/C isotope ratios. The comparative study demonstrates that SCAR is capable of measuring the C/C ratio of plant samples between 115 and 2600 pMC with sufficient accuracy and linearity, providing a new alternative for nuclear environmental protection and research in the case of organic samples exceeding the natural environmental level (∼100 pMC).

Phenol is a vital chemical precursor in modern industry; however, the dominant cumene process for its production generates wastewater laden with complex organic compounds, making the accurate detection of phenol critically important. Traditional spectroscopic methods struggle with this challenge due to severe spectral overlap among the components. To overcome this analytical bottleneck, we introduce a novel framework that integrates chemical modulation with a custom-built, multidimensional sensor array for the highly selective and sensitive monitoring of such complex industrial effluents. At the core of our system is a bespoke U-shaped cuvette that permits the optical path length to be dynamically adjusted from 1 to 10 cm, thereby introducing a critical physical dimension to the dataset. By capturing the high-dimensional optical response of the sample before and after a selective bromination reaction-a process that specifically eliminates the spectral signature of phenol-we constructed an information-rich differential dataset that provides distinctive features for resolving the phenol signal from a convoluted background. This dataset was modeled using various machine learning algorithms, among which the Random Forest (RF) model yielded the best performance, achieving a coefficient of determination (R) of 0.99826. Critically, our dynamic path length strategy lowered the limit of detection (LOD) to 0.0709 mg/L, a greater than five-fold enhancement in sensitivity over conventional fixed-pathlength methods. The robustness of this approach was thoroughly validated in authentic river and marine water matrices, where spike-and-recovery experiments produced ideal results, with recovery rates consistently falling within the 95 %-105 % range.

Flexible stretchable sensors have a wide range of applications in fields such as health monitoring and human-computer interaction. However, developing stretchable sensors that combine high sensitivity with linearity remains a significant challenge. Here, we are inspired by spider crack bionics and adopt gradient stiffness design, and successfully prepare flexible stretchable sensors with excellent performance based on MXene/graphene oxide nanocomposites. The sensor achieves a sensitivity of 51.36, a linearity of 0.999, a fast response time of 60 ms, and a strain detection lower limit of 0.1 %. The study demonstrates the successful application of stretchable sensors for monitoring human movement, recognizing handwriting, and interpreting sign language. Therefore, the flexible stretchable sensor proposed in this study holds great promise for human motion detection, wearable electronics, and human-computer interaction.

Detection of antibodies in allergy diagnostics requires allergens to be immobilized, e.g., on microtiter plates; thereby, immobilization without capturing antibodies remains a challenge. An immobilization platform, based on the material-binding peptide Snakin-1, addresses the outlined challenge for ELISA-based allergy detection on the example of Bet v 1 from birch pollen. Bet v 1 from birch pollen is the main cause of allergic rhinitis in Europe. Snakin-1 was selected among five material-binding peptides due to its polystyrene (PS)-binding properties, productive immobilization in a fusion protein with Bet v 1, and lack of interference with the primary and secondary antibody of the assay. The developed ELISA covers the whole range of antibody detection in diagnostics of the anti-Bet v 1 antibody. The reached sensitivity of the Bet v 1-Snakin-1 ELISA on standard PS plates is comparable to the Bet v 1 signal on high-binding PS plates, and the Bet v 1-Snakin-1 ELISA outperforms the Bet v 1 ELISA on high-binding plates (1.3-fold). SPR measurements of binding Bet v 1 and Bet v 1-Snakin-1 to PS, as well as subsequent antibody detection, confirm the role of Snakin-1 in productive immobilization of the Bet v 1 allergen on PS. The necessity to block the microtiter plate with BSA could be omitted, and a detection limit of at least 0.333 ng/mL (0.14 kU/L) sIgE in serum was achieved. The latter results make the scalable coating of allergens on untreated PS plates from aqueous solutions, in combination with ELISA, a highly attractive platform for allergy diagnostics.

Carbazole-chalcone derivative fluorescent chemosensor (CRB1) was successfully synthesized and characterized to recognize the effect on OH ion. CRB1 showed an "on-off-on" specific response towards OH among different competing cations and anions. The detection process of orange color of sensor CRB1 selectively quenching at 563 nm in the presence of OH anion was monitored. Sensor CRB1 was observed to realize the lowest detection limit of 0.19 μM and the binding constant of 4.91 × 10 M for the detection of OH. The binding ability of sensor CRB1 with OH was demonstrated using fluorometric, UV-Vis, and H NMR titrations, reversibility with EDTA, Job's plot, docking study, and density functional theory studies (DFT). Furthermore, selectivity experiments of OH anion were performed, test strips, real food sample, and environmental analysis to determine the practical applicability of the sensor. Additionally, the activities of CRB1 in three different cell lines (MCF-7, MDA-MB-231, and WI-38) were examined.