A remarkable enhancement of Raman scattering is achieved by submicrometer‐sized spherical ZnO superstructures. The secondary superstructures of ZnO particles with a uniform diameter in the range of 220–490 nm was formed by aggregating ca. 13 nm primary single crystallites. By engineering the superstructure size to induce Mie resonances, leading to an electromagnetic contribution to the SERS enhancement. Meanwhile, a highly efficient charge‐transfer (CT) contribution derived from the primary structure of the ZnO nanocrystallites was able to enhance the SERS signals as well. The highest Raman enhancement factor of 105 was achieved for a non‐resonant molecule by the synergistic effect of CT and Mie resonances. The Mie resonances scattered near‐field effect investigated in the present study provides not only an important guide for designing novel SERS‐active semiconductor substrates, but also a coherent framework for modelling the electromagnetic mechanism of SERS on semiconductors.

This study found that could play a role in microbiota dysbiosis via the secreted antagonistic substances against probiotics. Moreover, the ratio of to the important probiotics and was identified as a valuable biomarker for screening early CRC.

This study aims to present a noninvasive prostate cancer screening methods using serum surface-enhanced Raman scattering (SERS) and support vector machine (SVM) techniques through peripheral blood sample. SERS measurements are performed using serum samples from 93 prostate cancer patients and 68 healthy volunteers by silver nanoparticles. Three types of kernel functions including linear, polynomial, and Gaussian radial basis function (RBF) are employed to build SVM diagnostic models for classifying measured SERS spectra. For comparably evaluating the performance of SVM classification models, the standard multivariate statistic analysis method of principal component analysis (PCA) is also applied to classify the same datasets. The study results show that for the RBF kernel SVM diagnostic model, the diagnostic accuracy of 98.1% is acquired, which is superior to the results of 91.3% obtained from PCA methods. The receiver operating characteristic curve of diagnostic models further confirm above research results. This study demonstrates that label-free serum SERS analysis technique combined with SVM diagnostic algorithm has great potential for noninvasive prostate cancer screening.

Fusobacterium nucleatum (F. nucleatum, Fn) is associated with the colorectal cancer (CRC). Fn-infection could induce significant levels of serum Fn-specific antibodies in human and mice. The objective of this study was to identify Fn-infection that elicit a humoral response in patients with CRC and evaluate the diagnostic performance of serum anti-Fn antibodies. In this work, we showed the mean absorbance value of anti-Fn-IgA and -IgG in the CRC group were significantly higher than those in the benign colon disease group and healthy control group (P < 0.001). The sensitivity and specificity of ELISA for the detection of anti-Fn-IgA were 36.43% and 92.71% based on the optimal cut-off. The combination of anti-Fn-IgA and carcino-embryonic antigen (CEA) was better for diagnosing CRC (Sen: 53.10%, Spe: 96.41%; AUC = 0.848). Furthermore, combining anti-Fn-IgA with CEA and carbohydrate antigen 19-9 (CA19-9) (Sen: 40.00%, Spe: 94.22%; AUC = 0.743) had the better ability to classify CRC patients with stages I-II. These results suggested that Fn-infection elicited high level of serum anti-Fn antibodies in CRC patients, and serum anti-Fn-IgA level may be a potential diagnosing biomarker for CRC. Serum anti-Fn-IgA in combination with CEA and CA19-9 increases the sensitivity of detecting early CRC.

Mesothelin (MSLN) is an attractive antigen for chimeric antigen receptor (CAR) T therapy and the epitope selection within MSLN is essential. In this study, we constructed two types of CARs targeting either region I of MSLN (meso1 CAR, also known as a membrane-distal region) or region III of MSLN (meso3 CAR, also known as a membrane-proximal region) using a modified piggyBac transposon system. We reported that, compared with meso1 CAR T cells, meso3 CAR T cells express higher levels of CD107α upon activation and produce increased levels of interleukin-2, TNF-α, and IFN-γ against multiple MSLN-expressing cancer cells in vitro. In a real-time cell analyzer system and a three-dimensional spheroid cancer cell model, we also demonstrated that meso3 CAR T cells display an enhanced killing effect compared with that of meso1 CAR T cells. More importantly, in a gastric cancer NSG mice model, meso3 CAR T cells mediated stronger antitumor responses than meso1 CAR T cells did. We further identified that meso3 CAR T cells can effectively inhibit the growth of large ovarian tumors in vivo. Collectively, our study provides evidences that meso3 CAR T-cell therapy performs as a better immunotherapy than meso1 CAR T-cell therapy in treating MSLN-positive solid tumors.

Low-temperature germination (LTG) is an important agronomic trait for direct seeding of rice in temperate regions of East Asia. To dissect the genetic control of LTG, we constructed a recombinant inbred line (RIL) population derived from a cross of japonica variety USSR5 and indica variety N22. Three putative QTL involved in LTG were detected and named qLTG-7, qLTG-9 and qLTG-12. They explained 9.5, 12.12 and 7.08 % of the phenotypic variation, respectively, and the alleles from USSR5 enhanced LTG. A set of advanced backcross lines selected for the presence of qLTG-9 (with the biggest contribution of the three QTL), by both linked markers and phenotype, was used to validate qLTG-9 in different generations, years and locations. A near-isogenic line in USSR5 background with a qLTG-9 insertion from N22 had retarded germination under low-temperature conditions. Finally, qLTG-9 was fine mapped between markers L9-25D and ID-1, to a 72.3-kb region in chromosome 9, which in the Nipponbare genome contains five predicted genes. This result provides a springboard for map-based cloning of qLTG-9 and is helpful in understanding the mechanism of seed germination under low-temperature conditions.

This study aims to characterize and classify serum surface-enhanced Raman spectroscopy (SERS) spectra between bladder cancer patients and normal volunteers by genetic algorithms (GAs) combined with linear discriminate analysis (LDA). Two group serum SERS spectra excited with nanoparticles are collected from healthy volunteers (n = 36) and bladder cancer patients (n = 55). Six diagnostic Raman bands in the regions of 481–486, 682–687, 1018–1034, 1313–1323, 1450–1459 and 1582–1587 cm−1 related to proteins, nucleic acids and lipids are picked out with the GAs and LDA. By the diagnostic models built with the identified six Raman bands, the improved diagnostic sensitivity of 90.9% and specificity of 100% were acquired for classifying bladder cancer patients from normal serum SERS spectra. The results are superior to the sensitivity of 74.6% and specificity of 97.2% obtained with principal component analysis by the same serum SERS spectra dataset. Receiver operating characteristic (ROC) curves further confirmed the efficiency of diagnostic algorithm based on GA-LDA technique. This exploratory work demonstrates that the serum SERS associated with GA-LDA technique has enormous potential to characterize and non-invasively detect bladder cancer through peripheral blood.

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