An in situ nuclear magnetic resonance (NMR) tube extraction coupled with fluorine-19 (19F) NMR spectroscopy was developed to quantify extracted fluorine. A solid-liquid extraction of Viton A was performed in situ in an NMR tube whereby an organic solvent was added to solid cross-linked Viton A (10 mg) that was positioned below the detection region of the NMR probe. The extracted fluorine was measured while relying on diffusion of fluorine-containing molecules from the fluoropolymer into the solvent. The in situ approach was used to correlate extraction efficiency as a function of polymer swelling. Permeation, calculated from swelling, was 2-fold greater using acetone compared to methanol. Acetone greater extracted fluorine concentration (ng F/g fluoropolymer) after 302 min of extraction. This method was also applied to a Viton A cord, a Viton O-ring, and polytetrafluoroethylene. Analysis by 19F diffusion-ordered spectroscopy NMR indicated that the extracted fluorine observed by 19F NMR was composed of non-cross-linked Viton A liberated from the polymer matrix. For individual PFAS analysis, liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF) showed increased extraction of perfluorooctanoic acid (PFOA) and perfluorohexanoic acid (PFHxA) as a function of time and swelling. Although it appeared that acetone extracted PFOA and PFHxA with greater efficiency than methanol, concentrations were not statistically significantly different. Thus, swelling with methanol was sufficient for extracting nonpolymeric molecules from Viton A. Therefore, measures of extracted fluorine by 19F NMR or other nondiscriminatory methods should not be interpreted as individual PFAS, without LC-QTOF confirmation. Our in situ approach minimizes the need for ex situ sample preparation and can be applied to other in situ NMR experiments such as solid leaching or solid-liquid partitioning.

Ruthenium(II)-dipyrido[3,2-a:2',3'-c] phenazine (dppz) complexes (Ru-dppz complexes) can function as the molecular light switches for DNA assay, but their applications to protein detection remain a challenge because proteins possess more structural complexity than nucleic acids. Herein, we develop for the first time a computational virtual screening strategy to screen light switches for protein detection. We find that the binding affinity between Ru-dppz complexes and proteins relies on the structure and ratio of auxiliary and dppz ligands, and it plays a key role in light-switching performance. We discover that [Ru(dppz)2dip]2+ (dip = 4,7-diphenyl-1,10-phenanthroline) can function as the human serum albumin (HSA) light switch, and it exhibits strong hydrophobic and π-cation interactions with HSA to achieve a 280.0-fold luminescence enhancement, which is 2 orders of magnitude higher than the parent complex [Ru(dip)3]2+. Moreover, [Ru(dppz)2dip]2+ displays a rapid response time (<1 s), a large Stokes shift, and high sensitivity for HSA assay with a limit of detection of 0.0093 mg/L. We further develop a smartphone-integrated point-of-care device based on [Ru(dppz)2dip]2+ for rapid detection of HSA. Notably, this strategy can be extended to screen the β-lactoglobulin light switch that exhibits a 346.1-fold luminescence enhancement. This research provides a universal approach for the discovery of high-performance protein light switches with promising applications in biomedical research and clinical diagnostics.

The reaction of horseradish peroxidase (HRP) and its fluorogenic substrate enables the sensitive analysis of various targets, making it frequently used in high-throughput techniques. Fluorescence-activated droplet sorting (FADS) is an ultrahigh-throughput analytical method that shows great potential in single-cell analysis and enzyme engineering. However, the application of HRP fluorescence assays in FADS has encountered difficulties due to the defects of nonspecific reactivity and relatively poor droplet retention of traditional HRP substrates. In this study, a new HRP fluorescent substrate, AQHR, was constructed via modifying the resorufin scaffold. Compared with the commercial substrate ADHP, AQHR has enhanced hydrophilicity and red-shifted absorption and emission spectra . In addition, AQHR exhibited excellent reactivity to HRP/H2O2 and greatly elevated anti-interference capability in comparison with ADHP. In the present study, the advantages of AQHR were confirmed by multienzyme cascade fluorescence assays and FADS screening of carboxylesterase (CES) mutants. AQHR is expected to become a promising substrate for HRP and be widely used in FADS and other analytical fields.

In the least-squares fitting of data of varying precision to functions that are algebraically linear in the adjustable parameters, the correct weights for obtaining optimal results are the pointwise inverse variances σi-2. These have often been obtained from the sampling statistics of replicate measurements of the uncertain quantity y, a procedure that has come to define weighted least-squares (WLS) calibration fitting. Unfortunately, such variance estimates are notoriously imprecise, and in a long-ago Monte Carlo study involving a linear response function and weights ranging over a factor of 5, ordinary least squares (OLS) outperformed WLS for almost every tested set of calibration x values and replicates. But there is a better way of obtaining the weights: variance-function estimation. This method relies on the fact that the variances for most physical data follow simple, smooth functions having two or three terms proportional to a constant, y, and y2. Since the replicate data are used collectively to estimate the variance function, the number of statistical degrees of freedom is large enough to achieve good precision in the calibration weights. When variance-function weighting is included in the aforementioned OLS-vs-WLS comparisons, it wins over OLS for almost every combination with m = 4-8 x values and n = 3-5 replicates. Further, of the four ways of weighting in the variance-function fitting, the iterative reweighting method gives the best results, in support of earlier findings.

The existing studies regarding the evaluation of antioxidant capacity frequently concentrate solely on a single aspect, either stoichiometry or kinetics. And limited research has focused on elucidating antioxidant behavior of antioxidants within mixtures. In this study, we selected 12 phenolic compounds and formulated mixtures with both uniform and varying concentrations for antiradical assay. The change curves of compounds eliminated in response to variations in DPPH and ABTS concentrations were determined by UHPLC-UV-HRMS. An intriguing observation was that the change curves of compounds eliminated in response to variations in DPPH or ABTS concentrations exhibited high similarity across mixtures of varying compositions and concentrations. To better characterize antiradical efficiency, a new parameter (antiradical efficiency (ARE)) was proposed. This parameter integrates both the scavenging capacity and kinetic factors and can be simply evaluated based on the priority and quantity of its elimination within the mixture. Furthermore, when we conducted an experiment to test the DPPH resistance of actual samples (mixed vitamin E capsules), we found that the antioxidants with higher ARE values were more capable of protecting VE from being eliminated by DPPH.

Acute kidney injury (AKI) caused by cisplatin (Cis) is still a clinical challenge that frequently leads to irreversible renal function decline. In situ monitoring of nitrosative/oxidative stress associated with early stage injury in AKI is essential for early AKI detection and elucidation of autophagy-related mechanisms. Targeted detection of peroxynitrite (ONOO-)/hypochlorous acid (HClO) within the kidneys may provide crucial insights for early diagnosis and therapeutic intervention of AKI. Fluorescence imaging, known for its excellent spatial resolution, sensitivity, and noninvasive nature, has demonstrated significant promise in biomedicine. This study developed a renal-clearable near-infrared (NIR) fluorescent probe (KNOP) capable of sequential recognition of ONOO-/HClO with high sensitivity and a rapid response. And this "sequential-lock" mechanism effectively reduces the false-positive results from single marker detection. KNOP allowed for sensitive monitoring of abnormal changes in ONOO-/HClO during both the induction and treatment of AKI with a good biocompatibility and was applied to monitoring autophagy in Cis-induced AKI. Furthermore, KNOP exhibited favorable renal clearance and high imaging contrast, enabling successful in situ visualization of these reactive species during AKI progression and therapeutic intervention. More significantly, the probe KNOP effectively identified patients with renal injury in clinical serum samples, as well. These findings demonstrate that KNOP serves as an effective renal-clearable tool for understanding nitrosative/oxidative stress and autophagy mechanisms while also underscoring the potential value of ONOO-/HClO as promising biomarkers for early AKI recognition and intervention.

Inducing cell surface receptor clustering to mediate downstream signaling and reverse drug resistance has become a core cancer therapeutic strategy. However, controllable in situ formation of receptor superclusters remains a key bottleneck. To address these issues, a programmable DNA self-assembly strategy was established by integrating three units of rolling circle amplification (RCA) vector unit, two long DNA strands loaded with aptamer recognition units and the hairpin assembly unit. Fluorescence imaging analysis demonstrated that targeting binding to protein tyrosine kinase 7 (PTK7) can trigger the release of an initiator strand, which in turn activated CHA-driven DNA network formation on the cell membrane. This network induced in situ, self-driven clustering of PTK7 receptors, leading to decreased intracellular calcium levels, loss of mitochondrial membrane potential, and activation of the mitochondrial-mediated intrinsic apoptosis pathway. Ultimately, this process promoted tumor cell apoptosis and downregulated the expression of the resistance-related protein P-glycoprotein (P-gp). This study provides a novel tool for drug-resistant tumor therapy and lays a foundation for antitumor therapy innovation.

Complex-valued chemometrics offers a promising extension of classical regression methods by exploiting both real and imaginary spectral components. Here, we show that conventional absorbance (χ(1)) and Raman (χ(3)) spectra can be transformed into complex-valued forms by combining the measured intensities as imaginary parts with their Kramers-Kronig-derived real parts. We benchmark four regression methods─classical least squares (CLS), inverse least squares (ILS), principal component regression (PCR), and partial least-squares regression (PLSR)─across four representative systems: the quasi-ideal benzene-toluene and benzene-cyclohexane mixtures, the nonideal acetone-chloroform mixture, and blood plasma spiked with glucose and urea. Compared to conventional chemometrics, complex-valued approaches consistently reduce prediction errors (MAE, RMSE, and R2). Implementation is computationally inexpensive, since the Kramers-Kronig transform of absorbance or Raman spectra can be obtained within seconds using FFT-based routines, even for large data sets. Software implementation is straightforward, and programs can be adapted within minutes using standard environments such as Mathematica. Surprisingly, complex-valued ILS matches or surpasses complex-valued PLSR, echoing earlier results in infrared spectroscopy, using the complex refractive index function, and suggesting a re-evaluation of regression hierarchies when complex spectra are available. These findings demonstrate that complex-valued chemometrics is broadly applicable, physically grounded, and capable of enhancing both classical and modern regression strategies in analytical spectroscopy.

Copper (Cu) electroplating has been rising once again due to the giant industrial demands for metal interconnectors in the integrated circuit and the current collector in the lithium-ion battery. If the current acidic Cu(II) electroplating were replaced by the alkaline Cu(I) electroplating, it would reduce electricity consumption by at least 50%, not to mention the environmental friendliness. The bottleneck for alkaline electroplating is the complexation to stabilize the Cu(I) cations in solution. To this end, we developed a novel alkaline Cu(I) electroplating system and studied the complexation mechanism by both ex situ and in situ UV-visible spectroscopy. The results demonstrated that succinimide (SM) is a stronger complexant than sulfite and forms a stable [Cu(SM)2]- ion, which was further stabilized by maltose. The sulfite acted as no longer a complexant but a reductant. Thus, a high-quality Cu-plating layer was obtained with excellent metallographic structure and mechanical performance. The work demonstrates the vital capability of UV-visible spectroscopy in investigations on the action mechanisms of electroplating additives.