Automated apoptosis identification in fluorescence imaging of nucleus based on histogram of oriented gradients of high-frequency wavelet coefficients

The automatic and accurate identification of apoptosis facilitates large-scale cell analysis.Most identification approaches using nucleus fluorescence imaging are based on specific morphological parameters.However,these parameters cannot completely describe nuclear morphology,thus limiting the identification accuracy of models.This paper proposes a new feature extraction method to improve the performance of the model for apoptosis identification.The proposed method uses a histogram of oriented gradient(HOG)of high-frequency wavelet coefficients to extract internal and edge texture information.The HOG vectors are classified using support vector machine.The experimental results demonstrate that the proposed feature extraction method well performs apoptosis identification,attaining 95:7% accuracy with low cost in terms of time.We confirmed that our method has potential applications to cell biology research.

Rapid label-free SERS detection of foodborne pathogenic bacteria based on hafnium ditelluride-Au nanocomposites

Two-dimensional(2D)nanomaterials have captured an increasing attention in biophotonics owing to their excellent optical features.Herein,2D hafnium ditelluride(HfTe_(2)),a new member of transition metal tellurides,is exploited to support gold nanoparticles fabricating HfTe_(2)-Au nanocomposites.The nanohybrids can serve as novel 2D surface-enhanced Raman scattering(SERS)substrate for the label-free detection of analyte with high sensitivity and reproducibility.Chemical mechanism originated from HfTe_(2) nanosheets and the electromagnetic enhancement induced by the hot spots on the nano-hybrids may largely contribute to the superior SERS effect of HfTe_(2)-Au nanocomposites.Finally,HfTe_(2)-Au nanocomposites are utilized for the label-free SERS analysis of foodborne pathogenic bac-teria,which realize the rapid and ultrasensitive Raman test of Escherichia coli,Listeria mono-cytogenes,Staphylococcus aureus and Salmonella with the limit of detection of 10 CFU/mL and the maximum Raman enhancement factor up to 1.7×10^(8).Combined with principal component analysis,HfTe_(2)-Au-based SERS analysis also completes the bacterial classification without extra treatment.

Instantaneous preparation of gold-carbon dot nanocomposites for on-site SERS identification of pathogens in diverse interfaces

Rapid detection of pathogens present on contaminated surfaces is crucial for food safety and public health due to the high morbidity and mortality of bacterial infections.Herein,a sensitive and efficient method for on-site identification of foodborne pathogens on anisotropic surfaces was developed by using an in situ instantaneously prepared surface-enhanced Raman scattering(SERS)platform.To achieve this,molybdenum-doped gallic acidderived carbon dots(MCDs)are utilized as the reductant for synthesizing Au@MCDs nanohybrids within just 3 s at ambient temperature.The synergistic effect of the electromagnetic enhancement and charge transfer of Au@MCDs enables excellent SERS performance 10 times stronger than bare Au NPs.The bioassay platform requires less than 5 min to complete the quantitative detection of foodborne pathogens on various microbial-contaminated interfaces with a sensitivity of 10 CFU/m L.This innovative strategy breaks the long-standing limitations of SERS substrates in practical use,such as the time-consuming process,interference of residual surfactants,poor surface stability,and few application scenarios,providing a promising tool for widespread applications in biomedical research and clinical diagnostics.

High-fidelity SIM reconstruction-based super-resolution quantitative FRET imaging

Structured illumination-based super-resolution Förster resonance energy transfer microscopy(SIM-FRET)provides an approach to resolving molecular behavior localized in intricate biological structures in living cells.However,SIM reconstruction artifacts will decrease the quantitative analysis fidelity of SIMFRET signals.To address these issues,we have developed a method called HiFi spectrum optimization SIM-FRET(HiFi-SO-SIM-FRET),which uses optimized Wiener parameters in the two-step spectrum optimization to suppress sidelobe artifacts and achieve super-resolution quantitative SIM-FRET.We validated our method by demonstrating its ability to reduce reconstruction artifacts while maintaining the accuracy of FRET signals in both simulated FRET models and live-cell FRET-standard construct samples.In summary,HiFi-SO-SIM-FRET provides a promising solution for achieving high spatial resolution and reducing SIM reconstruction artifacts in quantitative FRET imaging.

Lamellar hafnium ditelluride as an ultrasensitive surface-enhanced Raman scattering platform for label-free detection of uric acid

The development of two-dimensional(2D)transition metal dichalcogenides has been in a rapid growth phase for the utilization in surface-enhanced Raman scattering(SERS)analysis.Here,we report a promising 2D transition metal tellurides(TMTs)material,hafnium ditelluride(HfTe2),as an ultrasensitive platform for Raman identification of trace molecules,which demonstrates extraordinary SERS activity in sensitivity,uniformity,and reproducibility.The highest Raman enhancement factor of 2.32×10^(6)is attained for a rhodamine 6G molecule through the highly efficient charge transfer process at the interface between the HfTe2 layered structure and the adsorbed molecules.At the same time,we provide an effective route for large-scale preparation of SERS substrates in practical applications via a facile stripping strategy.Further application of the nanosheets for reliable,rapid,and label-free SERS fingerprint analysis of uric acid molecules,one of the biomarkers associated with gout disease,is performed,which indicates arresting SERS signals with the limits of detection as low as 0.1 mmol/L.The study based on this type of 2D SERS substrate not only reveals the feasibility of applying TMTs to SERS analysis,but also paves the way for nanodiagnostics,especially early marker detection.

Structured illumination-based super-resolution live-cell quantitative FRET imaging

Forster resonance energy transfer(FRET)microscopy provides unique insight into the functionality of biological systems via imaging the spatiotemporal interactions and functional state of proteins.Distinguishing FRET signals from sub-diffraction regions requires super-resolution(SR)FRET imaging,yet is challenging to achieve from living cells.Here,we present an SR FRET method named SIM-FRET that combines SR structured illumination microscopy(SIM)imaging and acceptor sensitized emission FRET imaging for live-cell quantitative SR FRET imaging.Leveraging the robust co-localization prior of donor and accepter during FRET,we devised a mask filtering approach to mitigate the impact of SIM reconstruction artifacts on quantitative FRET analysis.Compared to wide-field FRET imaging,SIM-FRET provides nearly twofold spatial resolution enhancement of FRET imaging at sub-second timescales and maintains the advantages of quantitative FRET analysis in vivo.We validate the resolution enhancement and quantitative analysis fidelity of SIM-FRET signals in both simulated FRET models and live-cell FRET-standard construct samples.Our method reveals the intricate structure of FRET signals,which are commonly distorted in conventional wide-field FRET imaging.