Assessing cotton maturity from fiber cross-section measurements

textThe previous Fiber Image Analysis System (FIAS-I) is not reliable enough to detect fibers, especially for the immature fibers. It yields a systematic bias in the maturity distribution. Furthermore, the maturity distributions are often assumed to be normal without any normality tests in many previous studies, and those distributions are commonly measured by a sole parameter, e.g., the mean maturity value. In fact, those statistical inferences on cotton maturity may not be valid when cotton maturity does not follow a normal distribution. In light of the complexity of maturity distributions, the sole-parameter approach does not appear to be reliable and rational to rank the maturity among different samples. In this thesis, modified algorithms are made in the previous Fiber Image Analysis System (FIAS-I) to improve the number and accuracy of detected cross-sections and reduce the bias on immature fiber. The normality of cotton maturity distributions are analyzed through multiple parameters and patterns of cotton maturity distributions, and the experimental results on the cross section images selected from seven cotton varieties are displayed. Finally, several normality tests are introduced, and the Box-Cox transformation is applied to the maturity distribution, which makes the comparisons among the mean maturity feasible.Textile and Apparel Technolog

The Longest Common Exemplar Subsequence Problem

In this paper, we propose to find order conserved subsequences of genomes by finding longest common exemplar subsequences of the genomes. The longest common exemplar subsequence problem is given by two genomes, asks to find a common exemplar subsequence of them, such that the exemplar subsequence length is maximized. We focus on genomes whose genes of the same gene family are in at most s spans. We propose a dynamic programming algorithm with time complexity O(s4 s mn) to find a longest common exemplar subsequence of two genomes with one genome admitting s span genes of the same gene family, where m, n stand for the gene numbers of those two given genomes. Our algorithm can be extended to find longest common exemplar subsequences of more than one genomes

Native Proteomics in Discovery Mode Using Size-Exclusion Chromatography–Capillary Zone Electrophoresis–Tandem Mass Spectrometry

Native proteomics aims to characterize complex proteomes under native conditions and ultimately produces a full picture of endogenous protein complexes in cells. It requires novel analytical platforms for high-resolution and liquid-phase separation of protein complexes prior to native mass spectrometry (MS) and MS/MS. In this work, size exclusion chromatography (SEC)-capillary zone electrophoresis (CZE)-MS/MS was developed for native proteomics in discovery mode, resulting in the identification of 144 proteins, 672 proteoforms, and 23 protein complexes from the Escherichia coli proteome. The protein complexes include four protein homodimers, 16 protein-metal complexes, two protein-[2Fe-2S] complexes, and one protein-glutamine complex. Half of them have not been reported in the literature. This work represents the first example of online liquid-phase separation-MS/MS for characterization of a complex proteome under the native condition, offering the proteomics community an efficient and simple platform for native proteomics

The prognostic value of negative lymph node count for patients with cervical cancer after radical surgery

Negative lymph node (NLN) count has been recognized as a prognostic indicator in various cancers. However, the relationship between NLN count and the prognosis of cervical cancer is still unknown. In this study, 10, 500 cervical cancer patients after radical surgery were selected from Epidemiology and End Results Program (SEER) data. Clinicopathological characteristics were collected for analysis, including year of diagnosis, age, race, grade, primary site, FIGO stage and cause specific survival (CSS). Univariate and multivariate Cox proportional hazards model was used to assess risk factors for survival of patients. X-tile plots identified 6 as the optimal cutoff value of NLN count to divide patients into high and low risk subsets in terms of CSS (χ2 = 183.95, P < 0.001). The rate of 5-year CCS of cervical cancer patients was improved with an increase in NLN count from 0 to 23 (all P < 0.001). NLN count was validated as an independently prognostic factor by the multivariate Cox analysis (HR: 1.571, 95% CI: 1.370~1.801, P < 0.001). Subgroup analysis showed that NLN count was a prognosis factor in FIGO stage I (χ2=35.023, P < 0.001), stage II (χ2 = 12.910, P < 0.001), stage III + IV (χ2 = 9.732, P = 0.002) and unknown stage (χ2 = 16.654, P < 0.001). Conclusively, this study demonstrated the NLN count was an independent prognostic factor for cervical cancer patients

A novel deep learning segmentation model for organoid-based drug screening

Organoids are self-organized three-dimensional in vitro cell cultures derived from stem cells. They can recapitulate organ development, tissue regeneration, and disease progression and, hence, have broad applications in drug discovery. However, the lack of effective graphic algorithms for organoid growth analysis has slowed the development of organoid-based drug screening. In this study, we take advantage of a bladder cancer organoid system and develop a deep learning model, the res-double dynamic conv attention U-Net (RDAU-Net) model, to improve the efficiency and accuracy of organoid-based drug screenings. In this RDAU-Net model, the dynamic convolution and attention modules are integrated. The feature-extracting capability of the encoder and the utilization of multi-scale information are substantially enhanced, and the semantic gap caused by skip connections has been filled, which substantially improved its anti-interference ability. A total of 200 images of bladder cancer organoids on culture days 1, 3, 5, and 7, with or without drug treatment, were employed for training and testing. Compared with the other variations of the U-Net model, the segmentation indicators, such as Intersection over Union and dice similarity coefficient, in the RDAU-Net model have been improved. In addition, this algorithm effectively prevented false identification and missing identification, while maintaining a smooth edge contour of segmentation results. In summary, we proposed a novel method based on a deep learning model which could significantly improve the efficiency and accuracy of high-throughput drug screening and evaluation using organoids

Sharp bounds for the general Randić index of graphs with fixed number of vertices and cyclomatic number

The cyclomatic number, denoted by $\gamma$, of a graph $G$ is the minimum number of edges of $G$ whose removal makes $G$ acyclic. Let $\mathscr{G}_{n}^{\gamma}$ be the class of all connected graphs with order $n$ and cyclomatic number $\gamma$. In this paper, we characterized the graphs in $\mathscr{G}_{n}^{\gamma}$ with minimum general Randić index for $\gamma\geq 3$ and $1\leq\alpha\leq \frac{39}{25}$. These extend the main result proved by A. Ali, K. C. Das and S. Akhter in 2022. The elements of $\mathscr{G}_{n}^{\gamma}$ with maximum general Randić index were also completely determined for $\gamma\geq 3$ and $\alpha\geq 1$

Atomic-scale observation of localized phonons at FeSe/SrTiO3 interface

In single unit-cell FeSe grown on SrTiO3, the superconductivity transition temperature features a significant enhancement. Local phonon modes at the interface associated with electron-phonon coupling may play an important role in the interface-induced enhancement. However, such phonon modes have eluded direct experimental observations. Indeed, the complicated atomic structure of the interface brings challenges to obtain the accurate structure-phonon relation knowledge from either experiment or theory, thus hindering our understanding of the enhancement mechanism. Here, we achieve direct characterizations of atomic structure and phonon modes at the FeSe/SrTiO3 interface with atomically resolved imaging and electron energy loss spectroscopy in a scanning transmission electron microscope. We find several phonon modes highly localized (~1.3 nm) at the unique double layer Ti-O termination at the interface, one of which (~ 83 meV) engages in strong interactions with the electrons in FeSe based on ab initio calculations. The electron-phonon coupling strength for such a localized interface phonon with short-range interactions is comparable to that of Fuchs-Kliewer (FK) phonon mode with long-rang interactions. Thus, our atomic-scale study provides new insights into understanding the origin of superconductivity enhancement at the FeSe/SrTiO3 interface

An Effective Screening Method and a Reliable Screening Trait for Salt Tolerance of Brassica napus at the Germination Stage

Salinity is a major and complex abiotic stress that inhibits plant growth and reduces crop yield. Given the global increase in soil salinity, there is a need to develop salt-tolerant species. Brassica napus L. is an important oilseed crop with some level of salt tolerance. However, few studies have evaluated its salt tolerance thoroughly or screened for traits that can be reliably evaluated for salt tolerance. Here, we evaluated salt tolerance in 549 B. napus inbred lines with different genetic backgrounds using the membership function value (MFV) of certain traits, including the germination rate, root and shoot length, root and shoot fresh weight, and total fresh weight. According to the evaluation criteria-mean MFV, 50 highly salt-tolerant, 115 salt-tolerant, 71 moderately salt-tolerant, 202 salt-sensitive, and 111 highly salt-sensitive inbred lines were screened at the germination stage. We also developed a mathematical evaluation model and identified that the salt tolerance index of shoot fresh weight is a single trait that reliably represents the salt tolerance of B. napus germplasm at the germination stage. These results are useful for evaluating and breeding salt-tolerant B. napus germplasm

A Role for a Dioxygenase in Auxin Metabolism and Reproductive Development in Rice

SummaryIndole-3-acetic acid (IAA), the natural auxin in plants, regulates many aspects of plant growth and development. Extensive analyses have elucidated the components of auxin biosynthesis, transport, and signaling, but the physiological roles and molecular mechanisms of auxin degradation remain elusive. Here, we demonstrate that the dioxygenase for auxin oxidation (DAO) gene, encoding a putative 2-oxoglutarate-dependent-Fe (II) dioxygenase, is essential for anther dehiscence, pollen fertility, and seed initiation in rice. Rice mutant lines lacking a functional DAO display increased levels of free IAA in anthers and ovaries. Furthermore, exogenous application of IAA or overexpression of the auxin biosynthesis gene OsYUCCA1 phenocopies the dao mutants. We show that recombinant DAO converts the active IAA into biologically inactive 2-oxoindole-3-acetic acid (OxIAA) in vitro. Collectively, these data support a key role of DAO in auxin catabolism and maintenance of auxin homeostasis central to plant reproductive development