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Background: Ovarian cancer (OC) is among the deadliest malignancies in women and the lack of appropriate markers for early diagnosis leads to poor prognosis in most cases. Previous studies have shown that KAZN is involved in multiple biological processes during development, such as cell proliferation, differentiation, and apoptosis, so defects or aberrant expression of KAZN might cause queer cell behaviors such as malignancy. Here we evaluated the KAZN expression and methylation levels for possible use as an early diagnosis marker for OC.Methods: We used data from Gene Expression Omnibus (GEO) microarrays, The Cancer Genome Atlas (TCGA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) to investigate the correlations between KAZN expression and clinical characteristics of OC by comparing methylation levels of normal and OC samples. The relationships among differentially methylated sites in the KAZN gene, corresponding KAZN mRNA expression levels and prognosis were analyzed.Results: KAZN was up-regulated in ovarian epithelial tumors and the expression of KAZN was correlated with the patients' survival time. KAZN CpG site cg17657618 was positively correlated with the expression of mRNA and the methylation levels were significantly differential between the group of stage "I and II" and the group of stage "III and IV". This study also presents a new method to classify tumor and normal tissue in OC using DNA methylation pattern in the KAZN gene body region.Conclusions: KAZN was involved in ovarian cancer pathogenesis. Our results demonstrate a new direction for ovarian cancer research and provide a potential diagnostic biomarker as well as a novel therapeutic target for clinical application. [ABSTRACT FROM AUTHOR]

The knowledge distillation uses a high-performance teacher network to guide the student network. However, the performance gap between the teacher and student networks can affect the student's training. This paper proposes a novel knowledge distillation algorithm based on dynamic entropy correction, which adjusts the student instead of the teacher to reduce the gap. Firstly, the effect of changing the output entropy (short for output information entropy) on the distillation loss in the student is analyzed in theory. This paper shows that correcting the output entropy can reduce the gap. Then, a knowledge distillation algorithm based on dynamic entropy correction is created, which can correct the output entropy in real-time with an entropy controller updated dynamically by the distillation loss. The proposed algorithm is validated on the CIFAR100, ImageNet, and PASCAL VOC 2007. The comparison with various state-of-the-art distillation algorithms shows impressive results, especially in the experiment on the CIFAR100 regarding teacher–student pair resnet32x4–resnet8x4. The proposed algorithm raises 2.64 points over the traditional distillation algorithm and 0.87 points over the state-of-the-art algorithm CRD in classification accuracy, demonstrating its effectiveness and efficiency. • This paper proposes a novel knowledge distillation algorithm called DynamicKD. • DynamicKD designs an entropy controller to reduce the distillation gap in real time. • DynamicKD uses the dynamic entropy correction to reduce the learning difficulty. • DynamicKD uses a single entropy controller to help students' learning. • Experimental results show the effectiveness and efficiency of DynamicKD. [ABSTRACT FROM AUTHOR]

Knowledge distillation guides student networks' training and enhances their performance through excellent teacher networks. However, along with the performance advantages, knowledge distillation also entails a huge computational burden, sometimes tens or even hundreds of times that of traditional training methods. So, this paper designs a book-based knowledge distillation (BookKD) to minimize the costs of knowledge distillation while improving performance. First, a decoupling-based knowledge distillation framework is designed. By decoupling the traditional knowledge distillation process into two independent sub-processes, book-making and book-learning, knowledge distillation can be completed with little resource consumption. Second, a book-making method based on knowledge ensemble and knowledge regularization is developed, which makes books by organizing and processing the knowledge generated by teachers. These books can replace these teachers to provide sufficient knowledge with little distillation costs. Finally, a book-learning method based on entropy dynamic adjustment and label smoothing is designed. The entropy dynamic adjustment optimizes the training loss and mitigates student networks' difficulty in learning books. Label smoothing alleviates the student network's over-confidence in ground truth labels, which increases its attention to the class similarity knowledge in books. BookKD is tested on three image classification datasets, CIFAR100, ImageNet and ImageNet100, and an object detection dataset PASCAL VOC 2007. The experiment results indicate the advantages of BookKD in reducing distillation costs and improving distillation performance. [ABSTRACT FROM AUTHOR]

Secoisolariciresinol (SECO) is a lignan of potential therapeutic value for diseases such as cancer, but its use has been limited by the lack of ideal production methods, even though its precursors are abundant in plants, such as flaxseeds. Here, we report the characterization of a bacterial strain, S1, isolated from the human intestinal flora, which could produce secoisolariciresinol by biotransformation of precursors in defatted flaxseeds. This bacterium was a Gram-negative and facultatively anaerobic straight rod without capsules. Biochemical assays showed that it was negative for production of oxidase, lysine decarboxylase, ornithine decarboxylase, arginine dihydrolase, and β-glucolase. The G + C content of genomic DNA was 57.37 mol%. Phylogenetic analysis by 16S rRNA and rpoB gene sequences demonstrated S1's close relatedness to Klebsiella. No homologues were found for wzb or wzc (capsular genes), which may explain why Klebsiella sp. strain S1 does not have the capsule and was isolated from a healthy human individual. Based on the percentages of homologous genes with identical nucleotide sequences between the bacteria in comparison, we found that clear-cut genetic boundaries had been formed between S1 and any other Klebsiella strains compared, dividing them into distinct phylogenetic lineages. This work demonstrates that the intestinal Klebsiella, well known as important opportunistic pathogens prevalent in potentially fatal nosocomial infections, may contain lineages that are particularly beneficial to the human health. [ABSTRACT FROM AUTHOR]

Neural architecture search (NAS) has been a great success in the automated design of deep neural networks. However, neural architecture search using evolutionary algorithms is challenging due to the diverse structure of neural networks and the difficulty in performance evaluation. To this end, this paper proposes an evolutionary neural architecture search algorithm (called EF-ENAS) based on evaluation corrections and functional units. First, a mating selection operation based on evaluation correction is developed, which can help EF-ENAS discriminate high-performance network architectures and reduce the harmful effects of low fidelity accuracy evaluation methods. Then, a functional unit-based network architecture crossover operation is designed, which divides the neural network into different functional units for crossover and protects valuable network architectures from destruction. Finally, the idea of species protection is introduced into the traditional environmental selection operation and a species protection-based environmental selection operation is designed, which can improve the diversity of network architectures in a population. The EF-ENAS is tested on ten benchmark datasets with varying complexities. In addition, the proposed algorithm is compared with 44 state-of-the-art algorithms, including DARTS, EvoCNN, CNN-GA, AE-CNN, etc. The experimental results show that the proposed algorithm 1 1 The code of EF-ENAS is available at https://github.com/codesl173/EF-ENAS. can automatically design neural networks and perform better. [ABSTRACT FROM AUTHOR]

Knowledge distillation (KD) has been widely used in model compression. But, in the current multi-teacher KD algorithms, the student can only passively acquire the knowledge of the teacher's middle layer in a single form and all teachers use identical a guiding scheme to the student. To solve these problems, this paper proposes a multi-teacher KD based on joint Guidance of Probe and Adaptive Corrector (GPAC) method. First, GPAC proposes a teacher selection strategy guided by the Linear Classifier Probe (LCP). This strategy allows the student to select better teachers in the middle layer. Teachers are evaluated using the classification accuracy detected by LCP. Then, GPAC designs an adaptive multi-teacher instruction mechanism. The mechanism uses instructional weights to emphasize the student's predicted direction and reduce the student's difficulty learning from teachers. At the same time, every teacher can formulate guiding scheme according to the Kullback–Leibler divergence loss of the student and itself. Finally, GPAC develops a multi-level mechanism for adjusting spatial attention loss. this mechanism uses a piecewise function that varies with the number of epochs to adjust the spatial attention loss. This piecewise function classifies the student' learning about spatial attention into three levels, which can efficiently use spatial attention of teachers. GPAC and the current state-of-the-art distillation methods are tested on CIFAR-10 and CIFAR-100 datasets. The experimental results demonstrate that the proposed method in this paper can obtain higher classification accuracy. [ABSTRACT FROM AUTHOR]

Salmonella enterica subsp. houtenae serovar 16:z4, z32:- str. RKS3027 was isolated from a human in Illinois, USA. S. enterica subsp. houtenae is a facultative aerobic rod-shaped Gram-negative bacterium. Here we describe the features of this organism, together with the draft genome sequence and annotation. The 4,404,136 bp long genome (97 contigs) contains 4,335 protein-coding gene and 28 RNA genes. [ABSTRACT FROM AUTHOR]

Adiabatic and vertical ionization potentials (IPs) and valence electron affinities (EAs) of serinamide in the gas phase have been determined using density functional theory (DFT) B3LYP, B3P86, and B3PW91 methods with the 6‐311++G** and 6‐311G** basis sets, respectively. IPs and EAs of serinamide in solution have been calculated with the B3LYP method using the 6‐311++G** and 6‐311G** basis sets. Eight possible conformers of serinamide and its charged states in the gas phase have been optimized employing the DFT B3LYP method with 6‐311++G** and 6‐311G** basis sets, respectively. All the adiabatic and vertical ionization potentials (AIPs and VIPs) of eight serinamide conformers in our work are positive values, whether in the gas phase or in solutions; the IPs in solutions are smaller than the results in the gas phase and decrease with increased dielectric constants in solutions. This finding indicates that the cationic states in solutions are more stable than those in the gas phase. All EAs of eight serinamide conformers are negative values in the gas phase, indicating that the anionic states are unstable with respect to electron autodetachment, both adiabatically and vertically. In contrast, all other adiabatic electron affinities (AEAs) are negative values in solutions except for 6S in water; 7S in chloroform, acetone, and water; and 8S in acetone and water, and increase with increasing of dielectric constants in solutions. All vertical electron affinities (VEAs) are negative values in solutions; however, no good rule has been found for these values in solutions. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2006 [ABSTRACT FROM AUTHOR]

Background: Salmonella bongori infect mainly cold-blooded hosts, but infections by S. bongori in warm-blooded hosts have been reported. We hypothesized that S. bongori might have diverged into distinct phylogenetic lineages, with some being able to infect warm-blooded hosts. Results: To inspect the divergence status of S. bongori, we first completely sequenced the parakeet isolate RKS3044 and compared it with other sequenced S. bongori strains. We found that RKS3044 contained a novel T6SS encoded in a pathogenicity island-like structure, in addition to a T6SS encoded in SPI-22, which is common to all S. bongori strains so far reported. This novel T6SS resembled the SPI-19 T6SS of the warm-blooded host infecting Salmonella Subgroup I lineages. Genomic sequence comparisons revealed different genomic sequence amelioration events among the S. bongori strains, including a unique CTAG tetranucleotide degeneration pattern in RKS3044, suggesting non-overlapping gene pools between RKS3044 and other S. bongori lineages/strains leading to their independent accumulation of genomic variations. We further proved the existence of a clear-cut genetic boundary between RKS3044 and the other S. bongori lineages/strains analyzed in this study. Conclusions: The warm-blooded host-infecting S. bongori strain RKS3044 has diverged with distinct genomic features from other S. bongori strains, including a novel T6SS encoded in a previously not reported pathogenicity island-like structure and a unique genomic sequence degeneration pattern. These findings alert cautions about the emergence of new pathogens originating from non-pathogenic ancestors by acquiring specific pathogenic traits. [ABSTRACT FROM AUTHOR]

Obesity is a metabolic disorder closely associated with profound alterations in gut microbial composition. However, the dynamics of species composition and functional changes in the gut microbiome in obesity remain to be comprehensively investigated. In this study, we conducted a meta-analysis of metagenomic sequencing data from both obese and non-obese individuals across multiple cohorts, totaling 1351 fecal metagenomes. Our results demonstrate a significant decrease in both the richness and diversity of the gut bacteriome and virome in obese patients. We identified 38 bacterial species including Eubacterium sp. CAG:274, Ruminococcus gnavus, Eubacterium eligens and Akkermansia muciniphila, and 1 archaeal species, Methanobrevibacter smithii, that were significantly altered in obesity. Additionally, we observed altered abundance of five viral families: Mesyanzhinovviridae, Chaseviridae, Salasmaviridae, Drexlerviridae, and Casjensviridae. Functional analysis of the gut microbiome indicated distinct signatures associated to obesity and identified Ruminococcus gnavus as the primary driver for function enrichment in obesity, and Methanobrevibacter smithii, Akkermansia muciniphila, Ruminococcus bicirculans, and Eubacterium siraeum as functional drivers in the healthy control group. Additionally, our results suggest that antibiotic resistance genes and bacterial virulence factors may influence the development of obesity. Finally, we demonstrated that gut vOTUs achieved a diagnostic accuracy with an optimal area under the curve of 0.766 for distinguishing obesity from healthy controls. Our findings offer comprehensive and generalizable insights into the gut bacteriome and virome features associated with obesity, with the potential to guide the development of microbiome-based diagnostics. [ABSTRACT FROM AUTHOR]

Background: Escherichia coli are mostly commensals but also contain pathogenic lineages. It is largely unclear whether the commensal E. coli as the potential origins of pathogenic lineages may consist of monophyletic or polyphyletic populations, elucidation of which is expected to lead to novel insights into the associations of E. coli diversity with human health and diseases. Methods: Using genomic sequencing and pulsed field gel electrophoresis (PFGE) techniques, we analyzed E. coli from the intestinal microbiota of three groups of healthy individuals, including preschool children, university students, and seniors of a longevity village, as well as colorectal cancer (CRC) patients, to probe the commensal E. coli populations for their diversity. Results: We delineated the 2280 fresh E. coli isolates from 185 subjects into distinct genome types (genotypes) by PFGE. The genomic diversity of the sampled E. coli populations was so high that a given subject may have multiple genotypes of E. coli, with the general diversity within a host going up from preschool children through university students to seniors. Compared to the healthy subjects, the CRC patients had the lowest diversity level among their E. coli isolates. Notably, E. coli isolates from CRC patients could suppress the growth of E. coli bacteria isolated from healthy controls under nutrient-limited culture conditions. Conclusions: The coexistence of multiple E. coli lineages in a host may help create and maintain a microbial environment that is beneficial to the host. As such, the low diversity of E. coli bacteria may be associated with unhealthy microenvironment in the intestine and hence facilitate the pathogenesis of diseases such as CRC. [ABSTRACT FROM AUTHOR]

Highly conserved short sequences help identify functional genomic regions and facilitate genomic annotation. We used Salmonella as the model to search the genome for evolutionarily conserved regions and focused on the tetranucleotide sequence CTAG for its potentially important functions. In Salmonella, CTAG is highly conserved across the lineages and large numbers of CTAG-containing short sequences fall in intergenic regions, strongly indicating their biological importance. Computer modeling demonstrated stable stem-loop structures in some of the CTAG-containing intergenic regions, and substitution of a nucleotide of the CTAG sequence would radically rearrange the free energy and disrupt the structure. The postulated degeneration of CTAG takes distinct patterns among Salmonella lineages and provides novel information about genomic divergence and evolution of these bacterial pathogens. Comparison of the vertically and horizontally transmitted genomic segments showed different CTAG distribution landscapes, with the genome amelioration process to remove CTAG taking place inward from both terminals of the horizontally acquired segment. [ABSTRACT FROM AUTHOR]

Background: Organisms have orchestrated coagulation and immune systems. Although a link between inflammation and haemostasis has been reported in asthma, the interaction mechanism has not been completely elucidated. Here, we investigated the direct link between the mammalian immune and coagulation systems. Methods: Mice were administered protease or antigens intranasally to induce airway inflammation with or without thrombin inhibitors treatment. The effects of thrombin and its inhibitors on interleukin (IL)‐33 were investigated both in vivo and in vitro. Peripheral blood mononuclear cells (PBMCs) and plasma from asthma patients are collected to verify the correlation between thrombin and group 2 innate lymphocytes (ILC2s). Results: Low‐molecular‐weight heparin (LMWH, an indirect inhibitor of thrombin) restrained both papain‐ and fungus‐induced type 2 immune responses in mice by inhibiting IL‐33 cleavage. Upon examining the potential thrombin protease consensus sites, we found that IL‐33 was directly cleaved by thrombin at specific amino acids (R48 and R106) to generate a mature form of IL‐33 with potent biological activity. In addition, we found that bivalirudin TFA (a direct inhibitor of thrombin) inhibited a variety of type 2 inflammatory responses, such as those in house dust mite (HDM)‐ and ovalbumin (OVA)‐mediated pulmonary inflammation models. We found that plasma thrombin‐antithrombin complex (TATc) levels in asthma patients were positively associated with the number and function of IL‐33‐responder group 2 innate lymphocytes (ILC2s) among peripheral blood mononuclear cells (PBMCs) from asthma patients. Conclusion: The data suggested that thrombin inhibitors administration could be effective in treating lung inflammation by regulating ILC2s via IL‐33 maturation, indicating that targeting thrombin is a potential way to treat allergic diseases. [ABSTRACT FROM AUTHOR]