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.

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.

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.

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.

Automated sample preparation systems, by virtue of their high-throughput characteristics, provide efficient solutions for large-scale biological sample analysis. They currently demonstrate significant advantages in complex experimental systems involving multi-parameter detection and real-time process monitoring. This review provides a short overview of the latest advances in high-throughput automated sample preparation technologies. It primarily encompasses the advantages and applications of robot-based automated liquid handling systems, solid-phase extraction technology and microfluidics in bioanalysis. It also addresses the main technical breakthroughs and existing challenges in high-throughput automated sample analysis. This review aims to provide a reference for promoting the precision and practicality of automated sample preparation methods in the field of high-throughput bioanalysis.

Ensuring consumers' safety and maintaining regulatory compliance requires assessing the presence of pesticide residues in agricultural products. While sulfoxaflor, a widely used sulfoximine insecticide, is effective in pest control, its environmental impact has been increasingly scrutinized. Concerns over sulfoxaflor's harm to pollinators have led to its prohibition in the EU as of 2022, making its detection a critical aspect of environmental and food safety monitoring. Here, we present an innovative, highly sensitive, semi-quantitative indirect competitive lateral flow immunoassay (icLFIA) for detecting sulfoxaflor in flower leaves. This icLFIA achieves a visual limit of detection of 4 μg/L in plant extracts by implementing a highly specific monoclonal antibody. Moreover, it has demonstrated great reproducibility, making it an eco-conscious test for routine analysis at the point of need using a simple hot water extraction and incorporating sustainable packaging. The icLFIA has been tested on commercially available ornamental flowers and critically compared against an in-house confirmatory liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. This development offers a cost-effective and reliable solution for sulfoxaflor residue assessment. The combination with a straightforward and simplified extraction protocol for flower leaves, makes it accessible to non-experts (e.g. beekeepers).

Alzheimer's disease (AD) has early symptoms that are subtle and easily confused with other brain disorders, necessitating the development of precise diagnostic technologies for AD. This study reported novel tandem detection molecular probes (HCys) for two key pathological markers in the AD process, namely butyrylcholinesterase (BChE) and β-amyloid (A β). The probe undergoes BChE-specific esterase hydrolysis, resulting in a 48-fold enhancement of fluorescence. After hydrolysis, the probe formed could further bind to A β aggregates and triggered a 6-7-fold fluorescence enhancement, establishing an "enzyme-activated" cascade detection mechanism. In ex vivo brain tissue experiments, the probe successfully visualized the spatial distribution of BChE in the brains of AD mice, and the hydrolyzed probe specifically labeled A β plaques in the brains of AD mice. The low molecular weight of the probes HCys enable it to rapidly cross the blood-brain barrier (BBB) and identify both early and late-stage AD models. This study is the first time to report near-infrared fluorescent probes targeting BChE and A β aggregates, providing a new tool for the early diagnosis of AD.

In the previous few years, it has been observed that zeolitic imidazolate framework (ZIF) based materials are promising catalytic materials for various applications such as catalysis, electrocatalysis, and energy storage oxygen or hydrogen evolution reactions. In particular, cobalt based ZIF materials have been extensively used in electrochemical applications due to its larger surface area, high porosity, and catalytic properties. The ZIF-67 is cobalt based ZIF material which was explored in the development of various electrochemical sensors for environmental monitoring and clinical diagnosis applications. This review article summarizes the progress in the formation of ZIF-67 based hybrid materials with graphene, carbon nanotubes, metal oxides, and MXenes etc for electrochemical sensing applications. The limitations, challenges and future perspectives for ZIF-67 based materials for electrochemical sensing applications have been discussed. It is expected that present review article would be beneficial for the researchers working on ZIF-67 based electrochemical sensors for environmental monitoring and healthcare system.

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.

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).

Capillary electrophoresis (CE) is a powerful tool to separate complex mixtures which includes mixtures of intact and viable organisms, a promising new area to improve analysis of microbiomes. CE requires an injection block or autosampler to load samples for separation. Neither of these sample introduction systems offer ease-of-use and cost efficiency with aseptic injection for analysis of microbiota. We developed a manual injection block to facilitate sterile analysis of organisms via CE. The system replaces traditional clamped blocks with an internally threaded collar. The capillary and electrode are recessed within the collar, preventing external contamination while preserving means to sterilize between analyses. A cylindrical vial holder is externally threaded and accommodates an autoclavable 200 μL polypropylene tube for sample, background electrolyte, and wash solutions. We evaluated performance of the new injector using capillary zone electrophoresis (CZE) on a CE system with laser-induced fluorescence detection of fluorescein and subsequent injection of viable Escherichia coli. Analyses of fluorescence produce a linear response across at least four orders of magnitude for hydrodynamically injected samples with LLOD of 6 pM and electrokinetically injected samples with LLOD of 8 pM. Performance for organismal separations coupled with automated fraction collection was evaluated using a standard laboratory strain of E. coli. We demonstrate four-fold improvement in zone width of E. coli using the new injector. Migration times for E. coli were comparable to previous designs; 133.7 ± 2.8 s and 129.8 ± 2.8 s, respectively.

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.

Dopamine (DA) is a common neurotransmitter in living organisms, which is involved in a variety of physiological functions and behavioral responses, making the monitoring of its level crucial. Herein, a novel dual-signal sensing strategy based on a silver-based bifunctional nanozymes (Ag-HA) has been proposed for sensitive detection of DA concentration. The prepared Ag-HA exhibited both blue fluorescence and peroxidase-like activity. In the presence of HO, Ag-HA could catalyze the generation of reactive oxygen species radicals, effectively oxidizing the colorless chromogenic substrate o-phenylenediamine (OPD) into the yellow oxidized product 2,3-diaminophenazine (DAP), which exhibited fluorescence emission at 570 nm and had a characteristic absorption peak at 415 nm. Meanwhile, due to the inner filter effect (IFE), DAP could quench the blue fluorescence of Ag-HA. The addition of DA hindered the oxidation of OPD, thereby reducing DAP formation and consequently decreasing its fluorescence and absorption signals, while recovering the blue fluorescence of Ag-HA in the system. Thus, a dual-signal detection platform was established for the determination of DA concentration by monitoring changes in the fluorescence intensity ratio (F/F) and colorimetric signal, with detection limits (LOD) of 0.035 μM and 0.23 μM, respectively. In addition, the proposed dual-mode strategy has achieved good practicability and application prospects in agarose hydrogel-smartphone visualization for detecting DA.

Estradiol (E2) is a vital hormone and recognized endocrine disruptor that necessitates sensitive monitoring at trace concentrations. While existing analytical methods provide high accuracy, their cost and operational complexity emphasize the need for simpler, yet sensitive alternatives. Here, we report a colorimetric assay for the sensitive detection of E2 by integrating duplex-specific nuclease (DSN) activity with split aptamer recognition and gold nanoparticle (AuNP) growth. In this design, E2 induces the hybridization of split aptamer fragments on AuNP surfaces, which are subsequently cleaved by DSN, leading to shortened surface DNA strands and altered nanoparticle passivation. This process induces heterogeneous gold growth upon gold (III) reduction, producing distinct colorimetric shifts that can be observed visually and quantified spectroscopically. Under optimized conditions, the assay exhibited a linear response in the range of 1-400 ng/mL with a detection limit of 1 ng/mL. This platform exhibited good selectivity against structurally related hormones and other potential interferents. Measurements in spiked human serum showed good agreement with commercial ELISA results, yielding a Pearson correlation coefficient of 0.91. This DSN-assisted split aptamer-AuNP strategy offers a straightforward and sensitive approach for detecting small molecules, with promising potential for clinical 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.

Cancer is a disease that begins with genetic and epigenetic alterations occurring in specific cells, some of which can spread and migrate to other tissues. Prostate cancer ranks as one of the most prevalent malignancies among men globally, particularly in regions with high human development indices. The disease often progresses silently in its early stages, underscoring the critical need for timely screening and awareness. importance of early detection and the role of prostate specific antigen (PSA) testing, digital rectal examinations (DRE), and biopsy methods in guiding clinical decision-making. Molecular mechanism underlying prostate cancer involve pathology, epidemiologic factors like diet, physical activities, chemical exposure and etiology of prostate cancer also disrupted signaling pathway, including DNA repair pathway, PI3K/AKT/mTOR, Wnt/β-catenin and AR pathway. Early diagnosis remains challenging, as most cases are detected at advanced stages, limiting curative treatment options. The integration of omics technologies and molecular biomarkers has refined early detection and risk stratification. Emerging strategies, including molecular targeted therapies, immunotherapies, and stem cell research, are transforming treatment approaches beyond traditional methods like surgery and radiotherapy. The present paper includes risk factors, genetic influences, screening protocols, and treatment options including surgery, radiation therapy, hormone therapy, and chemotherapy. The review also includes the application of artificial intelligence in improving diagnostic precision and personalized care. Additionally, recent advancements in targeted therapies and the molecular basis of disease progression are also discussed.

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.