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Due to the complexity and faintness of the detection wave patterns obtained by air-coupled transducers, if it is possible to effectively separate the various modes and obtain non-dispersive signals for more accurate detection and positioning, it will help to improve the accuracy and reliability of air-coupled ultrasonic Lamb wave detection, providing better technical support for the application and development of related fields. Because of the increased complexity of air-coupled signals, there is no definite theoretical formula to describe the mode changes of air-coupled signals, so the method based on blind separation has unique value. To address these challenges, the paper proposes a single-channel blind source separation (SCBSS) method. The effectiveness of this method is evaluated through simulations and experiments, demonstrating favorable separation results and efficient computational speed. This work first conducts an in-depth analysis of the signal characteristics of air-coupled ultrasonic non-destructive testing, and simulates the ultrasonic excitation conditions of air-coupled sensors through finite element software. The study of modal changes and multipath effects caused by the variation of the incidence angle of the ACT signal is carried out, and the situation of the Lamb wave signal excited by ACT at the receiving end is analyzed. By combining ACT with PZT signals, the ultrasonic signals of air-coupled Lamb waves are compared and studied, and their modal purification is carried out.

Cell–cell interactions, which allow cells to communicate with each other through molecules in their microenvironment, are critical for the growth, health, and functions of cells. Previous studies show that drug-resistant cells can interact with drug-sensitive cells to elevate their drug resistance level, which is partially responsible for cancer recurrence. Studying protein targets and pathways involved in cell–cell communication provides essential information for fundamental cell biology studies and therapeutics of human diseases. In the current studies, we performed direct coculture and indirect coculture of drug-resistant and drug-sensitive cell lines, aiming to investigate intracellular proteins responsible for cell communication. Comparative studies were carried out using monoculture cells. Shotgun bottom-up proteomics results indicate that the P53 signaling pathway has a strong association with drug resistance mechanisms, and multiple TP53-related proteins were upregulated in both direct and indirect coculture systems. In addition, cell–cell communication pathways, including the phagosome and the HIF-signaling pathway, contribute to both direct and indirect coculture systems. Consequently, AK3 and H3–3A proteins were identified as potential targets for cell–cell interactions that are relevant to drug resistance mechanisms. We propose that the P53 signaling pathway, in which mitochondrial proteins play an important role, is responsible for inducing drug resistance through communication between drug-resistant and drug-sensitive cancer cells.

The semihydrogenation of dimethyl oxalate (DMO) into methyl glycolate (MG) has garnered increasing attention in the production of the biodegradable polymer material, polyglycolic acid (PGA). Developing an appropriate descriptor to facilitate the design of copper-based catalysts for the efficient synthesis of MG faces significant challenges. Herein, we used single-atom Cu supported by different materials as catalyst models to investigate the relationship between the electronic structure of active sites and MG selectivity by using density functional theory (DFT) calculations. Calculated results indicated that carriers can effectively modulate the electronic structure of Cu and affect the adsorption and further hydrogenation of MG to ethylene glycol (EG) through metal–support interactions. The dissociative pathway and the direct hydrogenation pathway were investigated to gain insights into the key role of two reaction mechanisms in the semihydrogenation of DMO. It is demonstrated that the energy difference between the activation barrier of further hydrogenation of MG to EG and the desorption energy for MG based on the direct hydrogenation pathway can serve as a rapid catalyst screening benchmark and provides the description for product distribution in the DMO hydrogenation. Furthermore, we successfully correlated the Bader charge of the Cu atom with the strength of the copper–support interaction and observed that as the Cu–support interaction weakened, the selectivity of MG increased. This research provided valuable insights for the design and synthesis of efficient and stable Cu-based catalysts for the selective hydrogenation of DMO to produce MG.

Bioceramics, as one of the typical functional materials, find extensive use in the field of tissue regeneration due to their excellent biocompatibility and bioactivity. However, the high-temperature sintering process and the intrinsic brittleness of bioceramics significantly constrain their manufacturing processes, mechanical performance, and clinical applications. In this context, we have developed an innovative biomass recycling approach to fabricate flexible bioceramics using discarded natural sponge Euplectella aspergillum. By employing a simple, low-energy hydrothermal mineralization process, we transform low-cost natural sponge skeletons into high-value bioceramic scaffolds for tissue regeneration. The naturally derived bioceramic scaffolds exhibit excellent flexibility and machinability and high mechanical strength, far exceeding traditional sintered bioceramics. Furthermore, these scaffolds demonstrate excellent osteogenic and angiogenic capabilities, showcasing significant potential in the repair of flat bones, such as the calvarial and orbital bones. Our work represents a simple and efficient pathway toward the manufacturing of advanced functional bioceramics by repurposing underutilized natural resources.

Efficient line spectral estimation methods applicable to sub-Nyquist sampling are drawing considerable attention in both academia and industry. In this letter, we propose an enhanced compressed sensing (CS) framework for line spectral estimation, termed sparsity-based compressed covariance sensing (SCCS). In terms of sampling, SCCS is implemented by periodic non-uniform sampling; In terms of recovery, SCCS focuses on compressed line spectral recovery using covariance information. Due to the dual priors on sparsity and structure, SCCS theoretically performs better than CS in compressed line spectral estimation. We explain this superiority from the mutual incoherence perspective: the sensing matrix in SCCS has a lower mutual coherence than that in classic CS. Extensive experimental results show a high consistency with the theoretical inference. All in all, SCCS opens many avenues for line spectral estimation.

With the advantages of noncontact and the characteristic of the whole circumferential blade measurement, blade tip timing (BTT) technology shows vast potential for blade vibration monitoring. However, the frequency aliasing and nonuniformity in BTT signals remain the core challenges for accurate blade vibration reconstruction from BTT signals. In this study, a single-probe-based method that can extract the natural frequency of the rotating blade rapidly and accurately without considering the layout and number of the probes was proposed. First, a virtual signal is generated based on the BTT signal. Then, the two signals are multiplied and FFT is performed. By searching for peaks to find specific frequencies in the spectrum, de-aliasing can be achieved based on the frequency components in the product signal, and ultimately the natural frequency of the blade is obtained. The numerical and experimental results have verified the effectiveness of the method. The potential of the proposed method for small sample signal analysis and online blade health monitoring has also been demonstrated.

Subspace methods are widely used in statistical signal processing owing to their super-resolution. Conventional subspace methods, such as multiple signal classification (MUSIC) identify parameters containing frequency and direction of arrival by calculating pseudospectra without physical amplitudes. However, the real value of amplitude plays a significant role in fault diagnosis and condition monitoring. Additionally, due to hardware limitations and increased frequency, uniform (Nyquist) sampling becomes challenging. Nonuniform sampling, an alternative to high-rate sampling is common in practice. Consequently, nonuniform (sub-Nyquist) signal processing methods are urgently required. In this article, a generalized subspace method (GSM) is proposed to bridge the pseudospectrum with the real spectrum. The proposed method is a supplement to the existing subspace methods and is applicable to both uniform and nonuniform sampling. In the GSM, the Fourier coefficient of the autocorrelation function is derived by signal subspace from the perspective of basis matching. Then, an alias-free real power spectrum is obtained by combining the power spectrum reconstructed by GSM with the classical pseudospectrum. Finally, simulation and experiment demonstrate the performance of the proposed method in power spectrum reconstruction. Even under the dual influence of undersampled and nonuniform, the proposed method is still effective.

As the frequencies increase, the Nyquist rate is difficult to reach in certain applications. Consequently, alternatives to high-rate sampling are drawing considerable attention. In this letter, we propose a novel sub-Nyquist sampling scheme for noisy multi-sinusoidal signal (MSS), termed delay coprime sampling (DCS). In terms of structure, DCS is the simplest deterministic compressive blind sampling. Specifically, DCS is a periodic non-uniform sampling of order 2 with coprime delays. To estimate the frequency or power spectrum from extremely undersampled samples from DCS, we construct a new function, termed $n$th-fold correlation, which carries the same frequency set as the MSS. Remarkably, we find the $n$th-fold correlation samples with consecutive lags are available through step-by-step operations and then the power spectrum or characteristic frequency can be efficiently estimated. Extensive simulations are provided to verify the effectiveness of DCS. By comparing it with popular sub-Nyquist schemes, DCS shows advantages in reducing sampling rate/channel while simplifying the hardware configuration.

Carbon fiber-reinforced polymer (CFRP) composites are widely used in aerospace due to their outstanding mechanical properties. However, composite damage detection and localization techniques based on minimal actuator–receiver sensing pairs are still challenging. Based on Lamb wave (LW), current damage detection and localization methods rely on numerous sensors and baseline signals to extract damage information. This study introduces a novel approach for damage detection and localization in CFRP composites using a multimodal gated recurrent unit neural network (MGNN) model. The local maximum energy of the LW is obtained through the continuous wavelet transform (CWT) using complex Morlet wavelets. MGNN combines the time-domain LW-based and CWT-energy signals as an input, dramatically improving the anti-interference and damage feature extraction accuracy. In the MGNN framework, multiple feature mappings are aggregated to establish correlations between damage coordinates and features. This enables damage assessment of composite panels even with a limited dataset, utilizing a minimal sensing actuator–receiver pair configuration. Numerous experiments demonstrate the superior performance of the proposed method compared to other current models. Additionally, anti-interference and ablation experiments substantiate the effectiveness and more robust anti-interference capability of the proposed method. These findings reduce the complexity of sensing networks and detection costs for LW-based methods, thereby significantly improving the accuracy and reliability of composite damage detection.

Nitric oxide (NO) is a small molecule that plays important roles in biological systems and human diseases. The abundance of intracellular NO is tightly related to numerous biological processes. Due to cell heterogeneity, the intracellular NO amounts significantly vary from cell to cell, and therefore, any meaningful studies need to be conducted at the single-cell level. However, measuring NO in single cells is very challenging, primarily due to the extremely small size of single cells and reactive nature of NO. In the current studies, the quantitative reaction between NO and amlodipine, a compound containing the Hantzsch ester group, was performed in live cells. The product dehydro amlodipine was then detected by the Single-probe single-cell mass spectrometry technique to quantify NO in single cells. The experimental results indicated heterogeneous distributions of intracellular NO amounts in single cells with the existence of subpopulations.

Mass spectrometry (MS) has become an indispensable tool for metabolomics studies. However, due to the lack of applicable experimental platforms, suitable algorithm, software, and quantitative analyses of cell heterogeneity and subpopulations, investigating global metabolomics profiling at the single cell level remains challenging. We combined the Single-probe single cell MS (SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation. As proof of principle studies, two melanoma cancer cell lines, the primary (WM115; with a lower drug resistance) and the metastatic (WM266-4; with a higher drug resistance), were used as models. Our results indicate that after the treatment of the anticancer drug vemurafenib, a new subpopulation emerged in WM115 cells, while the proportion of the existing subpopulations was changed in the WM266-4 cells. In addition, metabolites for each subpopulation can be prioritized. Combining the SCMS experimental technique with a bioinformatics tool, our label-free approach can be applied to quantitatively study cell heterogeneity, prioritize markers for further investigation, and improve the understanding of cell metabolism in human diseases and response to therapy.

Blade-health monitoring is intensely required for turbomachinery because of the high failure risk of rotating blades. Blade-Tip Timing (BTT) is considered as the most promising technique for operational blade-vibration monitoring, which obtains the parameters that characterize the blade condition from recorded signals. However, its application is hindered by severe undersampling and stringent probe layouts. An inappropriate probe layout can make most of the existing methods invalid or inaccurate. Additionally, a general conflict arises between the allowed and required layouts because of arrangement restrictions. For the sake of economy and safety, parameter identification based on fewer probes has been preferred by users. In this work, a spatial-transformation-based method for parameter identification is proposed based on a single-probe BTT measurement. To present the general Sampling-Aliasing Frequency (SAFE) map definition, the traditional time–frequency analysis methods are extended to a time-sampling frequency. Then, a SAFE map is projected onto a parameter space using spatial transformation to extract the slope and intercept parameters, which can be physically interpreted as an engine order and a natural frequency using coordinate transformation. Finally, the effectiveness and robustness of the proposed method are verified by simulations and experiments under uniformly and nonuniformly variable speed conditions.

Rotor blades are widely used in large turbine equipment such as aero-engines and gas turbines. The stable operation of these machines is largely dependent on the condition of the blades. In gas turbines and compressors, blade failure is mostly caused by foreign object damage (FOD), manufacturing defects and material defects. To ensure the rationality of blade design and the stability of the whole system, reliable blade on-line monitoring is the foundation [1]. Blade tip timing (BTT) is a potential method of blade vibration monitoring. It does not need to contact the blade, which can realize the whole-stage blade vibration monitoring by a few numbers of probes. The traditional method of vibration monitoring with strain gauges requires the complex telemetry system and even adjustment of the rotor structure. In contrast, the BTT method is simple and efficient; however, the disadvantage is that the signal is under-sampled. Various methods have been developed in recent decades to overcome undersampling. In this article, you will see how to sample blade tip displacement using the BTT method, what constitutes a BTT measurement system, and how to overcome undersampling and extract the vibration parameters from BTT signals.

Measuring blade displacement using blade tip timing (BTT) enables nonintrusive monitoring of rotating blades and their vibration frequencies. The average sampling frequency of BTT is the product of the number of measurement probes and rotational frequency, which is usually far less than the blade natural frequency due to the limited number of probes. The pattern of the aliasing that arises from under-sampling is rather complex under uneven probe placement. In this article, we consider a probe placement design that is based on minimizing the maximum sidelobe level of the spectral window to suppress the aliasing frequencies in the spectrum. Based on a signal model containing both asynchronous and synchronous sinusoids, we then develop an extended version of the RELAX method (ERELAX) to estimate their parameters simultaneously. Model order selection rules are also used to determine the number of asynchronous sinusoids. The frequency ambiguity that arises from periodic nonuniform sampling (PNS) is also discussed based on the convolution in the frequency domain. Numerical simulations and results of a curved-blade experiment show that the proposed method has a mean squared estimation error less than 25% of that of two state-of-the-art methods (Block-OMP and MUSIC), requires 40% of the data length needed by the latter methods to achieve the same estimation accuracy, and has the smallest standard deviation of the reconstruction errors. Simulation codes are available at https://github.com/superjdg/RELAX_BTT.

Despite the development of various methods and commercial kits, site-directed mutagenesis of large plasmids remains a challenge in many laboratories. A site-directed mutagenesis method was developed for large plasmids by directly transforming two overlapping PCR fragments into Escherichia coli. This method successfully generated mutations for plasmids of 8.3 kb and 11.0 kb with high efficiencies. The method only requires Q5 DNA polymerase and DpnI, which greatly reduces costs. The procedure is simple, including PCR reaction, DpnItreatment and transformation. This simple, efficient and economical site-directed mutagenesis method for large plasmids is likely to be widely applied in the future.

The introduction of ultrasonic vibration in the grinding process of γ-TiAl intermetallic compounds can significantly reduce its processing difficulty. It is of great significance to understand the grinding mechanism of γ-TiAl intermetallic compounds and improve the processing efficiency by studying the mechanism of ordinary grinding of abrasive grains. Based on this, this study proposes a grinding force prediction model based on single-grain ultrasonic assisted grinding (UAG) chip formation mechanism. First, the prediction model of grinding force is established based on the chip formation mechanism of abrasive sliding ordinary grinding and the theory of ultrasonic assisted machining, considering the plastic deformation and shear effect in the process of material processing. Second, the UAG experiment of γ-TiAl intermetallic compounds was carried out by using diamond grinding wheel, and the unknown coefficient in the model was determined. Finally, the predicted values and experimental values of grinding force under different parameters were compared to verify the rationality of the model. It was found that the maximum deviation between the predicted value of tangential force and the actual value is 23%, and the maximum deviation between the predicted value of normal force and the actual value is 21.7%. In addition, by changing the relevant parameters, the model can predict the grinding force of different metal materials under different processing parameters, which is helpful for optimizing the UAG parameters and improving the processing efficiency.

In this article, the laser-assisted ultrasonic vibration dressing technique was applied to the cubic boron nitride (CBN) grinding wheel to study the effect of various process parameters (namely, laser power, dressing depth, feed rate, and grinding wheel speed) on the grinding force, surface quality, and morphological evolution of CBN abrasive particles. The results showed that abrasive particles’ morphology mainly undergoes micro-crushing, local crushing, large-area crushing, macro-crushing, and other morphological changes. The dressing force can be effectively reduced by controlling the dressing process parameters. Besides, grinding tests are performed on the grinding wheel after dressing to reveal specimens’ surface quality. Excellent grinding characteristics and grinding quality of the grinding wheel were obtained by the proposed technique with the optimized process parameters.

Single cell MS (SCMS) techniques are under rapid development for molecular analysis of individual cells among heterogeneous populations. Lipids are basic cellular constituents playing essential functions in energy storage and the cellular signaling processes of cells. Unsaturated lipids are characterized with one or multiple carbon–carbon double (C═C) bonds, and they are critical for cell functions and human diseases. Characterizing unsaturated lipids in single cells allows for better understanding of metabolomic biomarkers and therapeutic targets of rare cells (e.g., cancer stem cells); however, these studies remain challenging. We developed a new technique using a micropipette needle, in which Paternò-Büchi (PB) reactions at C═C bond can be induced, to determine locations of C═C bonds in unsaturated lipids at the single-cell level. The micropipette needle is produced by combining a pulled glass capillary needle with a fused silica capillary. Cell lysis solvent and PB reagent (acetone or benzophenone) are delivered into the micropipette needle (tip size ≈ 15 um) through a fused silica capillary. The capillary needle plays multiple functions (i.e., single cell sampling probe, cell lysis container, microreactor, and nano-ESI emitter) in the experiments. Both regular (no reaction) and reactive (with PB reaction) SCMS analyses of the same cell can be achieved. C═C bond locations were determined from MS scan and MS/MS of PB products assisted by Python programs. This technique can potentially be used for other reactive SCMS studies to enhance molecular analysis for broad ranges of single cells.

ABSTRACTPsoriasis is an immune-mediated chronic inflammatory skin disease. Keratinocyte hyperproliferation has been regarded as a significant event in psoriasis pathogenesis. Considering the vital role of miRNA-mediated mRNA repression in psoriasis pathogenesis, in the present study, we attempted to investigate the mechanism of keratinocyte overproliferation from the point of miRNA-mRNA regulation. Both online microarray expression profiles and experimental results indicated that the expression of LXR-α and PPAR-γ was downregulated in psoriasis lesion skin. LXR-α or PPAR-γ overexpression alone was sufficient to inhibit keratinocyte proliferation, decrease KRT5 and KRT14 protein levels and increase KRT1 and KRT10 protein levels. miR-203 negatively regulated LXR-α and PPAR-γ expression through direct targeting. miR-203 inhibition exerted the opposite effects to LXR-α or PPAR-γ overexpression on HaCaT cells. More importantly, LXR-α or PPAR-γ overexpression could markedly remarkably attenuate the effects of miR-203 overexpression in keratinocytes, indicating that miR-203 promotes keratinocyte proliferation by targeting LXR-α and PPAR-γ. In conclusion, the miR-203-LXR-α/PPAR-γ axis modulates the proliferation of keratinocytes and might be a novel target for psoriasis treatment, which needs further in vivo investigation.

ABSTRACTMelanin metabolism disorders may cause severe impacts on the psychological and social activities of patients. Different from the other two steps of melanin metabolism, namely synthesis and transport, little has been known about the mechanism of melanin degradation. Isoimperatorin (ISO) suppressed the activity of tyrosinase, an essential enzyme in melanin biosynthesis, hence, we investigated the effects and mechanism of ISO in melanin reduction. ISO stimulation significantly reduces the melanin contents and PMEL 17 protein levels; meanwhile, the activity and the protein levels of two critical lysosomal enzymes, Cathepsin B and Cathepsin D, can be significantly increased by ISO treatment. MiR-3619 inhibited the expression of CSTB and CSTD, therefore affecting ISO-induced degradation of melanin. In summary, ISO reduces the melanin content via miR-3619/CSTB and miR-3619/CSTD axes. ISO could be a potent skin-whitening agent, which needs further in vivoand clinical investigation.

Melanin metabolism disorders may cause severe impacts on the psychological and social activities of patients. Different from the other two steps of melanin metabolism, namely synthesis and transport, little has been known about the mechanism of melanin degradation. Isoimperatorin (ISO) suppressed the activity of tyrosinase, an essential enzyme in melanin biosynthesis, hence, we investigated the effects and mechanism of ISO in melanin reduction. ISO stimulation significantly reduces the melanin contents and PMEL 17 protein levels; meanwhile, the activity and the protein levels of two critical lysosomal enzymes, Cathepsin B and Cathepsin D, can be significantly increased by ISO treatment. MiR-3619 inhibited the expression of CSTB and CSTD, therefore affecting ISO-induced degradation of melanin. In summary, ISO reduces the melanin content via miR-3619/CSTB and miR-3619/CSTD axes. ISO could be a potent skin-whitening agent, which needs further in vivoand clinical investigation.

As a key factor, the accuracy of the instantaneous undeformed thickness model determines the force-predicting precision and further affects workpiece machining precision in the micro-milling process. The runout with five parameters affects the machining process more significantly compared with macro-milling. Furthermore, modern industry uses cutters with non-uniform pitch and helix angles more and more common for their excellent properties. In this article, an instantaneous undeformed thickness model is presented regarding cutter runout, variable pitch, and helix angles in the micro-milling process. The cutter edge with the cutter runout effect is modeled. Then, the intersecting ellipse between the plane vertical to the spindle axis and the cutter surface which is a cylinder can be gained. Based on this, the points, which are used to remove the material, on the ellipse as well as cutter edges are calculated. The true trochoid trajectory for each cutting point along the tool path is built. Finally, the instantaneous undeformed thickness values are computed using a numerical algorithm. In addition, this article analyzes runout parameters’ effects on the instantaneous undeformed thickness values. After that, helix and pitch angles’ effects on the instantaneous undeformed thickness are studied. Ultimately, the last section verifies the correctness and validity of the instantaneous undeformed thickness model based on the experiment conducted in the literature.

Laser-assisted ultrasonic dressing (LUD) of the removal behavior of diamond wheel material is investigated by simulation and experimental method. The finite element model of diamond wheel is constructed for simulation during LUD. The effect of parameters of LUD process on the dressing force is discussed according to the simulation results. LUD experiments of diamond wheels are carried out after obtaining optimization of parameter. The dressing force obtained from simulation and experiments are compared. It is found that the variation tendency of simulated dressing force is in agreement with the experimental result. This indicates that the simulation results can be effectively used for the selection of process’ parameters.

Mung bean contains up to 32.6% protein and is one of the great sources of plant-based protein. Because many allergens also function as defense-related proteins, it is important to determine their abundance levels in the high-yielding, disease-resistant cultivars. In this study, for the first time, we compared the seed proteome of high-yielding mung bean cultivars developed by a conventional breeding approach. Using a label-free quantitative proteomic platform, we successfully identified and quantified a total of 1373 proteins. Comparative analysis between the high-yielding disease-resistant cultivar (MC5) and the other three cultivars showed that a total of 69 common proteins were significantly altered in their abundances across all cultivars. Bioinformatic analysis of these altered proteins demonstrated that PDF1 (a defensin-like protein) exhibited high sequence similarity and epitope matching with the established peanut allergens, indicating a potential mung bean allergen that showed a cultivar-specific response. Conversely, known mung bean allergen proteins such as PR-2/PR-10 (Vig r 1), Vig r 2, Vig r 4, LTP1, β-conglycinin, and glycinin G4 showed no alternation in the MC5 compared to other cultivars. Taken together, our findings suggest that the known allergen profiles may not be impacted by the conventional plant breeding method to develop improved mung bean cultivars.

The growth of all-inorganic perovskite single-crystal microstructures on substrates is a promising approach for constructing photonic and electronic microdevices. However, current preparation methods typically involve direct control of ions or atoms, which often depends on specific lattice-matched substrates for epitaxial growth and other stringent conditions that limit the mild preparation and flexibility of device integration. Herein, we present the on-substrate fabrication of CsPbBr3single-crystal microstructures obtained via a nanoparticle self-assembly assisted low-temperature sintering (NSALS) method. Sintering guided by self-assembled atomically oriented superlattice embryos facilitated the formation of single-crystal microstructures under mild conditions without substrate dependence. The as-prepared on-substrate microstructures exhibited a consistent out-of-plane orientation with a carrier lifetime of up to 82.7 ns. Photodetectors fabricated by using these microstructures exhibited an excellent photoresponse of 9.15 A/W, and the dynamic optical response had a relative standard deviation as low as 0.1831%. The discrete photosensor microarray chip with 174000 pixels in a 100 mm2area showed a response difference of less than 6%. This method of nanoscale particle-controlled single crystal growth on a substrate offers a perspective for mild-condition preparation and in siturepair of crystals of various types. This advancement can propel the flexible integration and widespread application of perovskite devices.

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases. The formation of amyloid plaques by aggregated amyloid beta (Aβ) peptides is a primary event in AD pathology. Understanding the metabolomic features and related pathways is critical for studying plaque-related pathological events (e.g., cell death and neuron dysfunction). Mass spectrometry imaging (MSI), due to its high sensitivity and ability to obtain the spatial distribution of metabolites, has been applied to AD studies. However, limited studies of metabolites in amyloid plaques have been performed due to the drawbacks of the commonly used techniques such as matrix-assisted laser desorption/ionization MSI. In the current study, we obtained high spatial resolution (∼17 μm) MS images of the AD mouse brain using the Single-probe, a microscale sampling and ionization device, coupled to a mass spectrometer under ambient conditions. The adjacent slices were used to obtain fluorescence microscopy images to locate amyloid plaques. The MS image and the fluorescence microscopy image were fused to spatially correlate histological protein hallmarks with metabolomic features. The fused images produced significantly improved spatial resolution (∼5 μm), allowing for the determination of fine structures in MS images and metabolomic biomarkers representing amyloid plaques.

Single-atomic-layer gold nanosheets have been synthesized on the Au(111) substrate guided by vertical molecular channels confined by an octanethiolate (OT) surfactant, in great contrast to the typical hexagonal or triangular islands observed in homoepitaxy on the (111) plane of fcc metals. This anomalous growth mode shows a strong dependence on the coverage of the surfactant and hence demonstrates the possibility of using the surfactant coverage as a useful control parameter in fine-tuning the shape and aspect ratio for the growth of metal nanorods. The Au sheet grows preferentially in the ⟨112̅⟩ direction, and its width changes in a quantized manner in steps of 6.5a(∼1.85 nm), where ais the nearest-neighbor distance for Au atoms. This unexpected symmetry-breaking growth mode is proposed to arise from the interaction between the edges of the growing Au sheet and the OT overlayer, which behaves as a molecular carpet covering both the Au(111) substrate and the Au sheet. The growth of the Au sheet deforms the molecular carpet. Due to the crystalline structure of the OT layer, the energy involved in distorting the molecular carpet is directionally anisotropic. This hinders the growth of the Au sheet in certain directions leading to the symmetry-breaking growth. Direct comparison with an ethanethiol monolayer confirms the importance of the length of the alkyl chain in controlling the shape of the Au sheet.

Analyzing cellular constituents on the single-cell level through mass spectrometry (MS) allows for a wide range of compounds to be studied simultaneously. However, there is a need for quantitative single-cell mass spectrometry (qSCMS) methods to fully characterize drug efficacy from individual cells within cell populations. In this study, qSCMS experiments were carried out using the Single-probe MS technique. The method was successfully used to perform rapid absolute quantifications of the anticancer drug irinotecan in individual mammalian cancer cells under ambient conditions in real time. Traditional liquid chromatography/mass spectrometry (LC/MS) quantifications of irinotecan in cell lysate samples were used to compare the results from Single-probe qSCMS. This technique showcases heterogeneity of drug efficacy on the single-cell level.