Whole-exome sequencing explored mechanism of selpercatinib resistance in RET-rearranged lung adenocarcinoma transformation into small-cell lung cancer: a case report.

Small cell transformation was one mechanism by which EGFR-mutation NSCLC acquired resistance after tyrosine kinase inhibitors (TKIs) treatment. A few reports of small cell transformation occurred in other oncogene-driven lung cancers. We found the first case of transformation of a RET-rearranged lung adenocarcinoma to SCLC after selpercatinib, a novel highly selective RET TKIs. Whole-exome sequencing (WES) was used to explore alteration in gene expression in tumor tissue at initial diagnosis and after transformation into small cell carcinoma. We found that transformed into SCLC tumor tissue had inactivation of RB1 and TP53, with RET fusion was still present. In addition, the APOBEC family of cytidine deaminases appeared amplification. Although RET rearrangement still existed, using another RET TKIs was ineffective, and etoposide plus platinum might be an effective rescue treatment.

Dynamics of Quantum Networks in Noisy Environments.

Noise exists inherently in realistic quantum systems and affects the evolution of quantum systems. We investigate the dynamics of quantum networks in noisy environments by using the fidelity of the quantum evolved states and the classical percolation theory. We propose an analytical framework that allows us to characterize the stability of quantum networks in terms of quantum noises and network topologies. The calculation results of the framework determine the maximal time that quantum networks with different network topologies can maintain the ability to communicate under noise. We demonstrate the results of the framework through examples of specific graphs under amplitude damping and phase damping noises. We further consider the capacity of the quantum network in a noisy environment according to the proposed framework. The analytical framework helps us better understand the evolution time of a quantum network and provides a reference for designing large quantum networks.

Large-scale genomic analysis reveals the genetic cost of chicken domestication.

BACKGROUND: Species domestication is generally characterized by the exploitation of high-impact mutations through processes that involve complex shifting demographics of domesticated species. These include not only inbreeding and artificial selection that may lead to the emergence of evolutionary bottlenecks, but also post-divergence gene flow and introgression. Although domestication potentially affects the occurrence of both desired and undesired mutations, the way wild relatives of domesticated species evolve and how expensive the genetic cost underlying domestication is remain poorly understood. Here, we investigated the demographic history and genetic load of chicken domestication. RESULTS: We analyzed a dataset comprising over 800 whole genomes from both indigenous chickens and wild jungle fowls. We show that despite having a higher genetic diversity than their wild counterparts (average π, 0.00326 vs. 0.00316), the red jungle fowls, the present-day domestic chickens experienced a dramatic population size decline during their early domestication. Our analyses suggest that the concomitant bottleneck induced 2.95% more deleterious mutations across chicken genomes compared with red jungle fowls, supporting the "cost of domestication" hypothesis. Particularly, we find that 62.4% of deleterious SNPs in domestic chickens are maintained in heterozygous states and masked as recessive alleles, challenging the power of modern breeding programs to effectively eliminate these genetic loads. Finally, we suggest that positive selection decreases the incidence but increases the frequency of deleterious SNPs in domestic chicken genomes. CONCLUSION: This study reveals a new landscape of demographic history and genomic changes associated with chicken domestication and provides insight into the evolutionary genomic profiles of domesticated animals managed under modern human selection.

High-speed identification system for fresh tea leaves based on phenotypic characteristics utilizing an improved genetic algorithm.

BACKGROUND: High-quality tea requires leaves of similar size and tenderness. The grade of the fresh leaves determines the quality of the tea. The automated classification of fresh tea leaves improves resource utilization and reduces manual picking costs. The present study proposes a method based on an improved genetic algorithm for identifying fresh tea leaves in high-speed parabolic motion using the phenotypic characteristics of the leaves. During parabolic flight, light is transmitted through the tea leaves, and six types of fresh tea leaves can be quickly identified by a camera. RESULTS: The influence of combinations of morphology, color, and custom corner-point morphological features on the classification results were investigated, and the necessary dimensionality of the model was tested. After feature selection and combination, the classification performance of the Naive Bayes, k-nearest neighbor, and support vector machine algorithms were compared. The recognition time of Naive Bayes was the shortest, whereas the accuracy of support vector machine had the best classification accuracy at approximately 97%. The support vector machine algorithm with only three feature dimensions (equivalent diameter, circularity, and skeleton endpoints) can meet production requirements with an accuracy rate reaching 92.5%. The proposed algorithm was tested by using the Swedish leaf and Flavia data sets, on which it achieved accuracies of 99.57% and 99.44%, respectively, demonstrating the flexibility and efficiency of the recognition scheme detailed in the present study. CONCLUSION: This research provides an efficient tea leaves recognition system that can be applied to production lines to reduce manual picking costs. © 2022 Society of Chemical Industry.

Construction of a Family of Maximally Entangled Bases in ℂd⊗ℂd'.

In this paper, we present a new method for the construction of maximally entangled states in Cd⊗Cd' when d'≥2d. A systematic way of constructing a set of maximally entangled bases (MEBs) in Cd⊗Cd' was established. Both cases when d' is divisible by d and not divisible by d are discussed. We give two examples of maximally entangled bases in C2⊗C4, which are mutually unbiased bases. Finally, we found a new example of an unextendible maximally entangled basis (UMEB) in C2⊗C5.

CypB promotes cell proliferation and metastasis in endometrial carcinoma.

BACKGROUND: The molecular pathogenesis of endometrial cancer is not completely understood. CypB upregulated in many cancers, however, its role in endometrial carcinoma has not been studied. Here, we determine the effect of CypB on the growth of endometrial cancer. METHODS: In this study, we examined the expression of CypB in endometrial cancer tissues using immunohistochemistry. CypB silenced in HEC-1-B cell line by shRNA. CCK-8, colony formation assays, wound healing assays, and transwell analysis were performed to assess its effect on tumor cell proliferation and metastasis. Furthermore, microarray analysis was carried out to compare the global mRNA expression profile between the HEC-1-B and CypB-silenced HEC-1-B cells. Gene ontology and KEGG pathway enrichment analysis were performed to determine the potential function of differentially expressed genes related to CypB. RESULTS: We found that CypB was upregulated in endometrial cancer, inhibit CypB expression could significantly suppress cell proliferation, metastasis, and migration. We identified 1536 differentially expressed genes related to CypB (onefold change, p < 0.05), among which 652 genes were upregulated and 884 genes were downregulated. The genes with significant difference in top were mainly enriched in the cell cycle, glycosphingolipid biosynthesis, adherens junctions, and metabolism pathways. CONCLUSION: The results of our study suggest that CypB may serve as a novel regulator of endometrial cell proliferation and metastasis, thus representing a novel target for gene-targeted endometrial therapy. TRIAL REGISTRATION: YLYLLS [2018] 008. Registered 27 November 2017.

Rapid detection of quality index of postharvest fresh tea leaves using hyperspectral imaging.

BACKGROUND: The quality of fresh tea leaves after harvest determines, to some extent, the quality and price of commercial tea. A fast and accurate method to evaluate the quality of fresh tea leaves is required. RESULTS: In this study, the potential of hyperspectral imaging in the range of 328-1115 nm for the rapid prediction of moisture, total nitrogen, crude fiber contents, and quality index value was investigated. Ninety samples of eight tea-leaf varieties and two picking standards were tested. Quantitative partial least squares regression (PLSR) models were established using a full spectrum, whereas multiple linear regression (MLR) models were developed using characteristic wavelengths selected by a successive projections algorithm (SPA) and competitive adaptive reweighted sampling. The results showed that the optimal SPA-MLR models for moisture, total nitrogen, crude fiber contents, and quality index value yielded optimal performance with coefficients of determination for prediction (R2 p) of 0.9357, 0.8543, 0.8188, 0.9168; root mean square error of 0.3437, 0.1097, 0.3795, 1.0358; and residual prediction deviation of 4.00, 2.56, 2.31, and 3.51, respectively. CONCLUSION: The results suggested that the hyperspectral imaging technique coupled with chemometrics was a promising tool for the rapid and nondestructive measurement of tea-leaf quality, and had the potential to develop multispectral imaging systems for future online detection of tea-leaf quality. © 2020 Society of Chemical Industry.

Qualitative and quantitative diagnosis of nitrogen nutrition of tea plants under field condition using hyperspectral imaging coupled with chemometrics.

BACKGROUND: Rapid and accurate diagnosis of nitrogen (N) status in field crops is of great significance for site-specific N fertilizer management. This study aimed to evaluate the potential of hyperspectral imaging coupled with chemometrics for the qualitative and quantitative diagnosis of N status in tea plants under field conditions. RESULTS: Hyperspectral data from mature leaves of tea plants with different N application rates were preprocessed by standard normal variate (SNV). Partial least squares discriminative analysis (PLS-DA) and least squares-support vector machines (LS-SVM) were used for the classification of different N status. Furthermore, partial least squares regression (PLSR) was used for the prediction of N content. The results showed that the LS-SVM model yielded better performance with correct classification rates of 82% and 92% in prediction sets for the diagnosis of different N application rates and N status, respectively. The PLSR model for leaf N content (LNC) showed excellent performance, with correlation coefficients of 0.924, root mean square error of 0.209, and residual predictive deviation of 2.686 in the prediction set. In addition, the important wavebands of the PLSR model were interpreted based on regression coefficients. CONCLUSION: Overall, our results suggest that the hyperspectral imaging technique can be an effective and accurate tool for qualitative and quantitative diagnosis of N status in tea plants. © 2019 Society of Chemical Industry.

An improved method for quantitative recovery of conductivity using tomographically measured thermoacoustic data.

Noninvasive extraction of tissue conductivity distribution is important in brain imaging and cancer detection. Here we present an improved method that can accurately image tissue conductivity using tomographically measured microwave-induced thermoacoustic data. Our reconstruction algorithm is first tested using simulations, and then validated using tissue phantom experiments where saline-containing tubes are used as target(s) with various target sizes, positions and conductivities. The average error of reconstruction for the simulations is reduced from 4.87% to 1.38% compared with the previous algorithm. The experimental results obtained suggest that accurate quantitative thermoacoustic imaging would provide a potential tool for precision medicine.

[Joint effects of nano-selenium and nano-cerium on the male reproductive function of mice exposed to microwave radiation].

OBJECTIVE: To study effect of nano-selenium and nano-cerium(nano cerium oxide) on the spermatogenic ability of mice irradiated by 1800 MHz microwave radiation(MR). METHODS: Forty-two ICR mice were randomly divided into groups: blank control group, solvent control group, microwave radiation model group, low, medium and high dose groups of nano-selenium+nano-cerium. In joint effects groups of nano-selenium and nano-cerium, the nano-selenium solution(60, 120 and 240 µg/kg) and the nano-cerium oxide solution(15, 30, 60 µg/kg) were administered to the stomach at 7:30 in the morning and 18:30 in the evening, respectively. The blank control group was orally administered with an equal volume of distilled water, and the solvent control group and the MR group were orally administered with an equal volume of carboxymethylcellulose sodium solution. During the second week of gastric administration, the mice were exposed to microwave radiation(1800 MHz) for 2 h every day(specific absorption ratio: 0. 2986 W/kg). After MR treatment, the daily sperm production of testis, sperm motility and sperm deformity rate in epididymis were measured, and the testicular marker enzymes [G6 PDH(6-phosphatedehydrogenase), ACP(acid phosphatase), LDH(lactate dehydrogenase)], antioxidant indexes [CAT(catalase), MDA(malondialdehyde) and T-AOC(total antioxidant capacity)] in testicular tissue were analyzed. RESULTS: Compared with the solvent control group, MR led to the decrease of sperm motility and the increase of sperm deformity rate, decreased the enzymes activities of G6 PDH, ACP and CAT, increased LDH activity and MDA content, and decreased the T-AOC level in testicular tissue, and the differences were statistically significant(P<0. 05). Compared with the MR group, the joint action of nano-selenium and nano-cerium with medium dose increased the daily sperm production of testis((18. 98±1. 27) ×10~6/g) vs. (15. 53±1. 24) ×10~6/g), decreased the sperm deformity rate(11. 74%±0. 91% vs. 16. 84%±2. 05%), and the joint action of nano-selenium and nano-cerium with medium and high dose increased the sperm motility in epididymis(61. 98%±6. 33%, 54. 17±4. 38 vs. 45. 16%±5. 01%), and the differences were statistically significant(P<0. 05). Compared with the MR group, the joint action of nano-selenium and nano-cerium with low and medium dose increased the activity of ACP(11. 07±0. 98, 14. 85±1. 39 vs. 8. 72±0. 91 nmol/(min·mg prot), P<0. 05). The joint action of nano-selenium and nano-cerium with medium and high dose increased the activity of G6 PDH(24. 12±2. 06, 21. 36±3. 65 vs. 15. 11±1. 73 nmol/(min·mg prot), P<0. 05) and decreased the activity of LDH(15. 52±1. 17, 13. 51±1. 68 vs. 22. 46±2. 01 nmol/(min·mg prot), P<0. 05). The joint action of nano-selenium and nano-cerium with medium dose increased the activity of CAT(17. 92±2. 03 vs. 11. 69±0. 87 nmol/(min·mg prot), P<0. 05) and decreased the content of MDA(5. 17 ±0. 62 vs. 9. 03 ±0. 63 nmol/mg prot, P<0. 05). The joint action of nano-selenium and nano-cerium with low, medium and high dose increased the level of T-AOC(22. 06±1. 54, 29. 36±2. 39, 21. 01±2. 47 vs. 12. 88±1. 82 U/mg prot, P<0. 05). CONCLUSION: The joint addition of nano-selenium and nano-cerium can improve the reproductive function of male mice exposed to MR, and can effectively alleviate the changes of mouse testicular marker enzyme activity and the decline of antioxidant capacity caused by MR.