Previous studies have already shown that Raman spectroscopy can be used in the encoding of suspension array technology. However, almost all existing convolutional neural network-based decoding approaches rely on supervision with ground truth, and may not be well generalized to unseen datasets, which were collected under different experimental conditions, applying with the same coded material. In this study, we propose an improved model based on CyCADA, named as Detail constraint Cycle Domain Adaptive Model (DCDA). DCDA implements the classification of unseen datasets through domain adaptation, adapts representations at the encode level with decoder-share, and enforces coding features while leveraging a feat loss. To improve detailed structural constraints, DCDA takes downsample connection and skips connection. Our model improves the poor generalization of existing models and saves the cost of the labeling process for unseen target datasets. Compared with other models, extensive experiments and ablation studies show the superiority of DCDA in terms of classification stability and generalization. The model proposed by the research achieves a classification with an accuracy of 100% when applied in datasets, in which the spectrum in the source domain is far less than the target domain.

We propose a novel retinal layer segmentation method to accurately segment 10 retinal layers in optical coherence tomography (OCT) images with intraretinal fluid. The method used a fan filter to enhance the linear information pertaining to retinal boundaries in an OCT image by reducing the effect of vessel shadows and fluid regions. A random forest classifier was employed to predict the location of the boundaries. Two novel methods of boundary redirection (SR) and similarity correction (SC) were combined to carry out boundary tracking and thereby accurately locate retinal layer boundaries. Experiments were performed on healthy controls and subjects with diabetic macular edema (DME). The proposed method required an average of 415 s for healthy controls and of 482 s for subjects with DME and achieved high accuracy for both groups of subjects. The proposed method requires a shorter running time than previous methods and also provides high accuracy. Thus, the proposed method may be a better choice for small training datasets.

近年来, 许多研究人员不断努力为药物、除草剂、食品添加剂等小分子物质高特异性、高灵敏的检测和分析开发新的方法和技术。然而, 目前通用的分子检测方法的实施需要较长的前处理时间、昂贵的大型仪器设备及专业操作人员, 无法实现有选择的识别及快速的现场检测。所以, 在本研究中我们将量子点表面分子印迹聚合物(QDs@MIPs)与光纤相结合, 构建了一种新的光纤探头, 并将该光纤探头应用于光纤传感器, 检测小分子物质莱克多巴胺(RAC)。试验中, 我们对QDs@MIPs的表征、光纤探头的性能、光纤探头对RAC的浓度响应、光纤传感器的特异性及光强分布进行了探究。研究结果表明, 该光纤探头应用于光纤传感器能够提高光纤传感器的灵敏度, 使分子印迹光纤传感器具有更高的特异性识别能力和较强的抗干扰能力, 同时检测过程简便快捷, 适用于快速的现场检测。

Soluble microneedles (MNs) have recently become an efficient and minimally invasive tool in transdermal drug delivery because of their excellent biocompatibility and rapid dissolution. However, direct monitoring of structural and functional changes of MNs in vivo to estimate the efficiency of insulin delivery is difficult. We monitored the dissolution of MNs to obtain structural imaging of MNs' changes by using optical coherence tomography (OCT). We also observed the effect of MNs on microvascular conditions with laser speckle contrast imaging (LSCI) and measured the blood perfusion of skin to obtain functional imaging of MNs. We determined the performance of two soluble MN arrays made from polyvinyl alcohol (PVA) and polyvinyl alcohol/ polyvinylpyrolidone (PVA/PVP) by calculating the cross-sectional areas of the microchannels in mouse skin as a function of time. Moreover, the change in blood glucose before and after using MNs loaded with insulin was evaluated as an auxiliary means to demonstrate the ability of the soluble MNs to deliver insulin. Results showed that the structural imaging of these MNs could be observed in vivo via OCT in real time and the functional imaging of MNs could be showed using LSCI. OCT and LSCI are potential tools in monitoring MNs structural and functional changes.

近几年来, 由于可溶性微针更优秀的生物相容性和快速的溶解性, 这种给药方式成为了一种更高效, 对生物体伤害较小的给药技术。然而, 直接的在体监测微针的释药过程仍然比较困难。所以, 在这里提出用光学相干层析成像(OCT)的方法来实时监测可溶性微针的在体溶解过程并由此评估药物的释放; 以聚乙烯醇(PVA)和聚乙烯醇/聚乙烯吡咯烷酮混合物(PVA/PVP)为基质, 制作了两种不同的可溶性微针, 并通过计算微针作用于鼠耳后微通道横截面面积随时间的变化来比较两种微针的溶解性能。结果表明, 可以通过OCT技术实时地监测微针的在体溶解过程并进行数量上的评估。并且, OCT图像也可以评估和比较不同材料的可溶性微针的性能。因此, OCT在实时监测可溶性微针在体给药过程方面有很大的潜力。

Contamination by accidental cutaneous contact with the commercial products and the air pollutants raised a considerable health and safety issue. This study aimed to trace the dynamics of the 20 nm gold nanoparticle (GNP) penetration and accumulation in rat skin tissues using a surface-enhanced Raman scattering (SERS) technique. After the topical application of GNPs on rat skin surface, the SERS spectra were recorded for every 15 μm to an overall depth of 75 μm from skin surface for 150 min. The processes of GNP penetration in rat skin were accompanied by aggregation of GNPs, which affected SERS spectra. The results revealed that 20 nm GNPs can penetrate through stratum corneum layer, viable epidermis layer, and then into dermis layer. This study demonstrated for the first time the potential of SERS spectroscopy to monitor the penetration and accumulation of GNPs in rat skin.

We proposed a new saccharides sensor developed by symmetrical optical waveguide (SOW)- based surface plasmon resonance (SPR). This unique MgF₂/Au/MgF₂/Analyte film structure results in longer surface plasmon wave (SPW) propagation lengths and depths, leading to an increment of resolution. In this paper, we managed to decorate the dielectric interface (MgF₂ layer) by depositing a thin polydopamine film as surface-adherent that provides a platform for secondary reactions with the probe molecule. 3-Aminophenylboronic acid (3-PBA) is chosen to be the saccharides sense probe molecule in the present work. The aqueous humor of Diabetes and Cataract patient whose blood glucose level is normal are analyzed and the results demonstrated that this sensor shows great potential in monitoring the blood sugar and can be adapted in the field of biological monitoring in the future.