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Urolithiasis is a common disease that affects 5% to 8.8% of the world population with high recurring frequency. Therefore, there is an urgent need for the rapid and efficient diagnostics of urolithiasis. In this study, we developed a quantum dots (QDs)-based sensor for detecting urolithiasis oxalate. Urolithiasis oxalate was quantified by reducing Cu2+ to Cu+, which can be selectively recognized by CdTe QDs. The homogeneous sensing system shows high sensitivity for oxalate detection in the range of 0.1 μM to 10 mM within 6 min; moreover, the visual detection of 10 μM oxalate could be achieved by the naked eye. Our method was tested on 53 clinical samples; it showed 100% specificity and sensitivity for calcium oxalate urolithiasis compared with clinical diagnosis, even for hematuria samples. Furthermore, this method can be expanded to other wide range of biochemistry applications for medical diagnosis and point-of-care testing.

Retinal segmentation is a prerequisite for quantifying retinal structural features and diagnosing related ophthalmic diseases. Canny operator is recognized as the best boundary detection operator so far, and is often used to obtain the initial boundary of the retina in retinal segmentation. However, the traditional Canny operator is susceptible to vascular shadows, vitreous artifacts, or noise interference in retinal segmentation, causing serious misdetection or missed detection. This paper proposed an improved Canny operator for automatic segmentation of retinal boundaries. The improved algorithm solves the problems of the traditional Canny operator by adding a multi-point boundary search step on the basis of the original method, and adjusts the convolution kernel. The algorithm was used to segment the retinal images of healthy subjects and age-related macular degeneration (AMD) patients; eleven retinal boundaries were identified and compared with the results of manual segmentation by the ophthalmologists. The average difference between the automatic and manual methods is: 2-6 microns (1~2 pixels) for healthy subjects and 3-10 microns (1~3 pixels) for AMD patients. Qualitative method is also used to verify the accuracy and stability of the algorithm. The percentage of “perfect segmentation” and “good segmentation” is 98% in healthy subjects and 94% in AMD patients. This algorithm can be used alone or in combination with other methods as an initial boundary detection algorithm. It is easy to understand and improve, and may become a useful tool for analyzing and diagnosing eye diseases.

The size and shape of the foveal avascular zone (FAZ) have a strong positive correlation with several vision-threatening retinovascular diseases. The identification, segmentation and analysis of FAZ are of great significance to clinical diagnosis and treatment. We presented an adaptive watershed algorithm to automatically extract FAZ from retinal optical coherence tomography angiography (OCTA) images. For the traditional watershed algorithm, “over-segmentation” is the most common problem. FAZ is often incorrectly divided into multiple regions by redundant “dams”. This paper analyzed the relationship between the “dams” length and the maximum inscribed circle radius of FAZ, and proposed an adaptive watershed algorithm to solve the problem of “over-segmentation”. Here, 132 healthy retinal images and 50 diabetic retinopathy (DR) images were used to verify the accuracy and stability of the algorithm. Three ophthalmologists were invited to make quantitative and qualitative evaluations on the segmentation results of this algorithm. The quantitative evaluation results show that the correlation coefficients between the automatic and manual segmentation results are 0.945 (in healthy subjects) and 0.927 (in DR patients), respectively. For qualitative evaluation, the percentages of “perfect segmentation” (score of 3) and “good segmentation” (score of 2) are 99.4% (in healthy subjects) and 98.7% (in DR patients), respectively. This work promotes the application of watershed algorithm in FAZ segmentation, making it a useful tool for analyzing and diagnosing eye diseases.

Human immunodeficiency virus (HIV) infection inflicts significant economic and social burdens on many countries worldwide. Given the substantial morbidity and mortality from HIV infection, there is an urgent need for accurate and early detection of the virus. In this study, immunofluorescence and visual techniques are described that detect the HIV-1 p24 antigen, which relied on selective recognition of Ag+/Ag nanoparticles (Ag NPs) and Cu2+/Cu+ using cadmium telluride quantum dots (CdTe QDs). After the sandwich immunoreactions were accomplished, the alkaline phosphatase (ALP) hydrolyzed L-ascorbic acid 2-phosphate (AAP) to form ascorbic acid (AA) that further reduces Ag+ and Cu2+ to Ag NPs and Cu+, respectively. This method was highly sensitive and selective and could detect as low as 1 pg/mL of p24 antigen by naked eyes and had a good linearity in the concentration range 1–100 pg/mL. When using Ag+ and Cu2+ as media, the limit of detection (LOD) of the new method was 0.3 pg/mL and 0.2 pg/mL, respectively. Compared with clinical electrochemiluminescence immunoassay (ECLIA) results and clinical data, this method demonstrated good consistency for the quantification of HIV-1 p24 antigen in 34 clinical serum samples. In addition, this method could accurately distinguish HIV from other viruses and infections such as hepatitis B virus, systemic lupus erythematosus, hepatitis C virus, Epstein-Barr virus, cytomegalovirus, lipemia, and hemolysis. Therefore, our dual-mode analysis method may provide additional solutions to identify clinical HIV infection. An immunofluorescence and visualization dual-mode strategy for the detection of p24 antigen was constructed based on immune recognition reaction and a phenomenon that cadmium telluride quantum dots (CdTe QDs) can selectively recognize Ag+/Ag nanoparticles (Ag NPs) and Cu2+/Cu+.

Hairpin structures play an essential role in DNA replication, transcription, and recombination. Single-molecule studies enable the real-time measurement and observation of the energetics and dynamics of hairpin structures, including folding and DNA-protein interactions. Nanopore sensing is emerging as a powerful tool for DNA sensing and sequencing, and previous research into hairpins using an α-hemolysin (α-HL) nanopore suggested that hairpin DNA enters from its stem side. In this work, the translocation and interaction of hairpin and dumbbell DNA samples with varying stems, loops, and toeholds were investigated systematically using a Mycobacterium smegmatis porin A (MspA) nanopore. It was found that these DNA constructs could translocate through the pore under a bias voltage above +80 mV, and blockage events with two conductance states could be observed. The events of the lower blockage were correlated with the loop size of the hairpin or dumbbell DNA (7 nt to 25 nt), which could be attributed to non-specific collisions with the pore, whereas the dwell time of events with the higher blockage were correlated with the stem length, thus indicating effective translocation. Furthermore, dumbbell DNA with and without a stem opening generated different dwell times when driven through the MspA nanopore. Finally, a new strategy based on the dwell time difference was developed to detect single nucleotide polymorphisms (SNPs). These results demonstrated that the unzipping behaviors and DNA-protein interactions of hairpin and dumbbell DNA could be revealed using nanopore technology, and this could be further developed to create sensors for the secondary structures of nucleic acids.

Ascorbic acid (AA) and alkaline phosphatase (ALP) serve as an important coenzyme and enzyme in multiple biological metabolism reactions, respectively, and abnormal levels of these substrates have been associated with several diseases. Herein, a new and simple fluorescence strategy has been developed for AA and ALP sensing by exploiting CdTe quantum dots (QDs) as an effective signal indicator. This method is mainly based on the selective fluorescence-quenching reaction between Ag+ and CdTe QDs, as opposed to silver nanoparticles (Ag NPs); Ag+ can be reduced to Ag NPs by AA. Furthermore, by taking advantage of AA as a mediator, this strategy is further exploited for ALP assay given that ALP can cause the hydrolysis of l-ascorbic acid-2-phosphate (AAP), which yields AA. Under optimal conditions, controlled generation of Ag NPs and the selective recognition-based sensing system exhibit high sensitivity toward AA and ALP with limits of detection (LODs) of 3 μM and 0.25 U L-1 and linear ranges of detection from 0 to 800 μM and 1 to 1000 U L-1, respectively. Moreover, the sensor was successfully used for assaying AA in fruit juice and ALP in human serum. The results demonstrate that the proposed fluorescence strategy has significant advantages, such as its simplicity, cost-effectiveness, and rapid runtime, and the operational convenience of this label-free method further demonstrates its potential for constructing effective sensors with biochemical and clinical applications.

This paper summarizes the technological progress of the Chinese petroleum geophysical industry in recent years and analyzes in detail the trend of development in the petroleum industry as well as the main challenges to geophysical techniques on the mainland. Proposals to improve the situation have also been put forward.