In this study, we adapted an HP D100 Single Cell Dispenser - a novel low-cost thermal inkjet (TIJ) platform with impedance-based single cell detection - for dispensing of individual cells and one-pot sample preparation. We repeatedly achieved label-free identification of up to 1,300 proteins from a single cell in a single run using an Orbitrap Fusion Lumos Mass Spectrometer coupled to either an Acquity UPLC M-class system or a Vanquish Neo UHPLC system. The developed sample processing workflow is highly reproducible, robust, and applicable to standardized 384- and 1536-well microplates, as well as glass LC vials. We demonstrate the applicability of the method for proteomics of single cells from multiple cell lines, mixed cell suspensions, and glioblastoma tumor spheroids. As additional proof of robustness, we monitored the results of genetic manipulations and the expression of engineered proteins in individual cells. Our cost-effective and robust single-cell proteomics workflow can be transferred to other labs interested in studying cells at the individual cell level.

This work investigated the functional changes in whey proteins obtained from goat milk subject to various temperature treatments. Ultra-high temperature instantaneous sterilization (UHTIS) caused less damage than the common low-temperature, whereas spray-drying treatment had the opposite effect. A total of 426 proteins were identified in UHTIS and control treatment groups, including 386 common proteins and 16 and 14 unique proteins. The UHTIS treatment upregulated 55 whey proteins while down-regulated 98. The UHTIS-treated whey proteins may upregulate three metabolic pathways but downregulate one. Overall, UHTIS only slightly impacted the composition and functions of whey proteins from goat milk compared to the common low-temperature treatments.

Leveraging the fluorescence enhancement effect of the G-triplex (G3)/thioflavin T (ThT) catalyzed by the adjacent double-stranded DNA positioned at the 5\' terminus of the G3, the G3-specific oligonucleotide (G3MB6) was utilized to facilitate the rapid detection of mercury (Hg(II)) through thymine-Hg(II)-thymine (T-Hg(II)-T) interactions. G3MB6 adopted a hairpin structure in which partially complementary strands could be disrupted with the presence of Hg(II). It prompted the formation of double-stranded DNA by T-Hg(II)-T, inducing the unbound single strand of G3MB6 to spontaneously form a parallel G3 structure, producing a solid fluorescence signal by ThT. Conversely, fluorescence was absent without Hg(II), since no double strand and formation of G3 occurred. The fluorescence intensity of G3MB6 exhibited a positive correlation with Hg(II) concentrations from 17.72 to 300 nM (R2 = 0.9954), boasting a notably low quality of limitation (LOQ) of 17.72 nM. Additionally, it demonstrated remarkable selectivity for detecting Hg(II). Upon application to detect Hg(II) in milk samples, the recovery rates went from 100.3% to 103.2%.

Reconfiguration of chemical sensors, intended as the capacity of the sensor to adapt to novel operational scenarios, e.g., new target analytes, is potentially game changing and would enable rapid and cost-effective reaction to dynamic changes occurring at healthcare, environmental, and industrial levels. Yet, it is still a challenge, and rare examples of sensor reconfiguration have been reported to date. Here, we report on a reconfigurable label-free optical sensor leveraging the versatile immobilization of metal ions through a chelating agent on a nanostructured porous silica (PSiO2) optical transducer for the detection of different biomolecules. First, we show the reversible grafting of different metal ions on the PSiO2 surface, namely, Ni2+, Cu2+, Zn2+, and Fe3+, which can mediate the interaction with different biomolecules and be switched under mild conditions. Then, we demonstrate reconfiguration of the sensor at two levels: 1) switching of the metal ions on the PSiO2 surface from Cu2+ to Zn2+ and testing the ability of Cu2+-functionalized and Zn2+-reconfigured devices for the sensing of the dipeptide carnosine (CAR), leveraging the well-known chelating ability of CAR toward divalent metal ions; and 2) reconfiguration of the Cu2+-functionalized PSiO2 sensor for a different target analyte, namely, the nucleotide adenosine triphosphate (ATP), switching Cu2+ with Fe3+ ions to exploit the interaction with ATP through phosphate groups. The Cu2+-functionalized and Zn2+-reconfigured sensors show effective sensing performance in CAR detection, also evaluated in tissue samples from murine brain, and so does the Fe3+-reconfigured sensor toward ATP, thus demonstrating effective reconfiguration of the sensor with the proposed surface chemistry.

In the field of biomedicine, efficiently and non-invasively isolating target cells has always been one of the core challenges. Optical fiber tweezers offer precise and non-invasive manipulation of cells within a medium and can be easily integrated with microfluidic systems. Therefore, this paper investigated the mechanism of cell manipulation using scattering force with optical fiber tweezers. We employed flat-ended single-mode fiber to drive and sort cells and derived the corresponding scattering force formula based on the T-matrix model. A single-mode optical tweezers system for cell sorting was developed, and an optofluidic experimental platform was constructed that effectively integrates the optical system with microfluidic chips. The chip, featuring an expanded cross-channel design, successfully achieved continuous separation of yeast cells (8~10 µm in diameter) and polystyrene microspheres (15~20 µm in diameter), with a sorting efficiency of up to 86% and maintaining viability in approximately 90% of the yeast cells. Compared to other sorting systems, this system does not require labeling and can achieve continuous sorting with cell viability at a lower cost of instrumentation.

Cell dielectric property measurement holds significant potential for application in cell detection and diagnosis due to its label-free and noninvasive nature. In this study, we developed a biosensor designed to measure the permittivity of liquid samples, particularly cell suspensions at the nanoliter scale, utilizing microwave and millimeter wave coplanar waveguides in conjunction with a microchannel. This biosensor facilitates the measurement of scattering parameters within a frequency domain ranging from 1 GHz to 110 GHz. The obtained scattering parameters are then converted into dielectric constants using specific algorithms. A cell capture structure within the microchannel ensures that cell suspensions remain stable within the measurement zone. The feasibility of this biosensor was confirmed by comparison with a commercial Keysight probe. We measured the dielectric constants of three different cell suspensions (HepG2, A549, MCF-7) using our biosensor. We also counted the number of cells captured in multiple measurements for each cell type and compared the corresponding changes in permittivity. The results indicated that the real part of the permittivity of HepG2 cells is 0.2-0.8 lower than that of the other two cell types. The difference between A549 and MCF-7 was relatively minor, only 0.2-0.4. The fluctuations in the dielectric spectrum caused by changes in cell numbers during measurements were smaller than the differences observed between different cell types. Thus, the sensor is suitable for measuring cell suspensions and can be utilized for label-free, noninvasive studies in identifying biological cell suspensions.

Chronic liver disease, a long-term condition resulting from various causes such as alcohol abuse, metabolic disorders, and viral hepatitis, is becoming a significant global health challenge. Gypenosides (GPs), derived from the traditional Chinese medicine Gynostemma pentaphyllum (Thunb.) Makino, exhibited hepatoprotective properties in recent years, yet the precise therapeutic mechanism remains unclear. In this study, label-free and parallel reaction monitoring (PRM) proteomics were used to elucidate the hepatoprotective mechanism of GPs in liver injury rats. Through label-free proteomics, we identified 2104 differentially expressed proteins (DEPs) associated with liver injury, along with 1974 DEPs related to the effects of GPs. Bioinformatics analysis revealed that GPs primarily restored metabolic processes involving valine, leucine, and isoleucine degradation, as well as propanoate and butanoate metabolism, and steroid hormone biosynthesis during liver injury. Subsequently, overlapping the two groups of DEPs identified 1508 proteins reversed following GPs treatment, with key targets further validated by PRM. Eight target proteins were identified for GPs treatment of liver injury, including Lgals3, Psat1, Phgdh, Cyp3a9, Cyp2c11, Cyp4a2, Glul, and Ces1d. These findings not only elucidated the hepatoprotective mechanism of GPs, but may also serve as potential therapeutic targets of chronic liver disease.

White blood cell (WBC) classification is a valuable diagnostic approach for identifying diseases. However, conventional methods for WBC detection, such as flow cytometers, have limitations in terms of their high cost, large system size, and laborious staining procedures. As a result, deep learning-based label-free WBC image analysis methods are gaining popularity. Nevertheless, most existing deep learning WBC classification techniques fail to effectively utilize the subtle differences in the internal structures of WBCs observed under a microscope. To address this issue, we propose a neural network with feature fusion in this study, which enables the detection of label-free WBCs. Unlike conventional convolutional neural networks (CNNs), our approach combines low-level features extracted by shallow layers with high-level features extracted by deep layers, generating fused features for accurate bright-field WBC identification. Our method achieves an accuracy of 80.3 % on the testing set, demonstrating a potential solution for deep-learning-based biomedical diagnoses. Considering the proposed method simplifies the cell detection process and eliminates the need for complex operations like fluorescent staining, we anticipate that this automatic and label-free WBC classification network could facilitate more precise and effective analysis, and it could contribute to the future adoption of miniatured flow cytometers for point-of-care (POC) diagnostics applications.

UNASSIGNED: Spectroscopic single-molecule localization microscopy (sSMLM) takes advantage of nanoscopy and spectroscopy, enabling sub-10 nm resolution as well as simultaneous multicolor imaging of multi-labeled samples. Reconstruction of raw sSMLM data using deep learning is a promising approach for visualizing the subcellular structures at the nanoscale.
UNASSIGNED: Develop a novel computational approach leveraging deep learning to reconstruct both label-free and fluorescence-labeled sSMLM imaging data.
UNASSIGNED: We developed a two-network-model based deep learning algorithm, termed DsSMLM, to reconstruct sSMLM data. The effectiveness of DsSMLM was assessed by conducting imaging experiments on diverse samples, including label-free single-stranded DNA (ssDNA) fiber, fluorescence-labeled histone markers on COS-7 and U2OS cells, and simultaneous multicolor imaging of synthetic DNA origami nanoruler.
UNASSIGNED: For label-free imaging, a spatial resolution of 6.22 nm was achieved on ssDNA fiber; for fluorescence-labeled imaging, DsSMLM revealed the distribution of chromatin-rich and chromatin-poor regions defined by histone markers on the cell nucleus and also offered simultaneous multicolor imaging of nanoruler samples, distinguishing two dyes labeled in three emitting points with a separation distance of 40 nm. With DsSMLM, we observed enhanced spectral profiles with 8.8% higher localization detection for single-color imaging and up to 5.05% higher localization detection for simultaneous two-color imaging.
UNASSIGNED: We demonstrate the feasibility of deep learning-based reconstruction for sSMLM imaging applicable to label-free and fluorescence-labeled sSMLM imaging data. We anticipate our technique will be a valuable tool for high-quality super-resolution imaging for a deeper understanding of DNA molecules\' photophysics and will facilitate the investigation of multiple nanoscopic cellular structures and their interactions.

The prostaglandin transporter (PGT, SLCO2A1) mediates transport of prostanoids (a.o. prostaglandin E2 (PGE2)) into cells and thereby promotes their degradation. Overexpression of PGT leads to low extracellular PGE2 levels and has been linked to impaired wound healing of diabetic foot ulcers. Inhibition of PGT could thus be beneficial, however, no PGT inhibitors are currently on the market and drug discovery efforts are hampered by lack of high-through screening assays for this transporter. Here we report on a label-free impedance-based assay for PGT that measures transport activity through receptor activation (TRACT) utilizing prostaglandin E2 receptor subtype EP3 and EP4 that are activated by PGE2. We found that induction of PGT expression on HEK293-JumpIn-SLCO2A1 cells that also express EP3 and EP4 leads to an over 10-fold reduction in agonistic potency of PGE2. PGE2 potency could be recovered upon inhibition of PGT-mediated PGE2 uptake with PGT inhibitors olmesartan and T26A, the potency of which could be established as well. Moreover, the TRACT assay enabled the assessment of transport function of PGT natural variants. Lastly, HUVEC cells endogenously expressing prostanoid receptors and PGT were exploited to study wound healing properties of PGE2 and T26A in real-time using a novel impedance-based scratch-induced wound healing assay. These novel impedance-based assays will advance PGT drug discovery efforts and pave the way for the development of PGT-based therapies.