Comparison of Two Suspension Arrays for Simultaneous Detection of Five Biothreat Bacterial in Powder Samples

We have developed novel Bio-Plex assays for simultaneous detection of Bacillus anthracis, Yersinia pestis, Brucella spp., Francisella tularensis, and Burkholderia pseudomallei. Universal primers were used to amplify highly conserved region located within the 16S rRNA amplicon, followed by hybridized to pathogen-specific probes for identification of these five organisms. The other assay is based on multiplex PCR to simultaneously amplify five species-specific pathogen identification-targeted regions unique to individual pathogen. Both of the two arrays are validated to be flexible and sensitive for simultaneous detection of bioterrorism bacteria. However, universal primer PCR-based array could not identify Bacillus anthracis, Yersinia pestis, and Brucella spp. at the species level because of the high conservation of 16S rDNA of the same genus. The two suspension arrays can be utilized to detect Bacillus anthracis sterne spore and Yersinia pestis EV76 from mimic “write powder” samples, they also proved that the suspension array system will be valuable tools for diagnosis of bacterial biothreat agents in environmental samples

Insight into Conformational Change for 14-3-3σ Protein by Molecular Dynamics Simulation

14-3-3σ is a member of a highly conserved family of 14-3-3 proteins that has a double-edged sword role in human cancers. Former reports have indicated that the 14-3-3 protein may be in an open or closed state. In this work, we found that the apo-14-3-3σ is in an open state compared with the phosphopeptide bound 14-3-3σ complex which is in a more closed state based on our 80 ns molecular dynamics (MD) simulations. The interaction between the two monomers of 14-3-3σ in the open state is the same as that in the closed state. In both open and closed states, helices A to D, which are involved in dimerization, are stable. However, large differences are found in helices E and F. The hydrophobic contacts and hydrogen bonds between helices E and G in apo-14-3-3σ are different from those in the bound 14-3-3σ complex. The restrained and the mutated (Arg56 or Arg129 to alanine) MD simulations indicate that the conformation of four residues (Lys49, Arg56, Arg129 and Tyr130) may play an important role to keep the 14-3-3σ protein in an open or closed state. These results would be useful to evaluate the 14-3-3σ protein structure-function relationship

Does Continual Learning Equally Forget All Parameters?

Distribution shift (e.g., task or domain shift) in continual learning (CL) usually results in catastrophic forgetting of neural networks. Although it can be alleviated by repeatedly replaying buffered data, the every-step replay is time-consuming. In this paper, we study which modules in neural networks are more prone to forgetting by investigating their training dynamics during CL. Our proposed metrics show that only a few modules are more task-specific and sensitively alter between tasks, while others can be shared across tasks as common knowledge. Hence, we attribute forgetting mainly to the former and find that finetuning them only on a small buffer at the end of any CL method can bring non-trivial improvement. Due to the small number of finetuned parameters, such ``Forgetting Prioritized Finetuning (FPF)'' is efficient in computation. We further propose a more efficient and simpler method that entirely removes the every-step replay and replaces them by only $k$-times of FPF periodically triggered during CL. Surprisingly, this ``$k$-FPF'' performs comparably to FPF and outperforms the SOTA CL methods but significantly reduces their computational overhead and cost. In experiments on several benchmarks of class- and domain-incremental CL, FPF consistently improves existing CL methods by a large margin, and $k$-FPF further excels in efficiency without degrading the accuracy. We also empirically studied the impact of buffer size, epochs per task, and finetuning modules on the cost and accuracy of our methods

Do lncRNAs and circRNAs expression profiles influence discoid lupus erythematosus progression?—a comprehensive analysis.

Background: Long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs)are involved in the progression of discoid lupus erythematosus (DLE), but an understanding of their underlying mechanisms remains elusive. To explore the expression profiles of lncRNAs and circRNAs in DLE, we surveyed the lncRNA/circRNA and mRNA expression profiles in the epithelia of oral DLE and adjacent normal tissues. Methods: The lesional and non-lesional lower lips of three DLE patients were analysed by RNAsequencing (RNA-seq). The principal functions of the significantly deregulated genes were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. And the correlated expression networks (coding-noncoding co-expression and lncRNAstranscription factor-mRNA) were evaluated as well. Results: Hundreds of significantly changed lncRNAs and mRNAs and dozens of significantly changed circRNAs were identified. lncRNA lnc-MIPOL1-6 and IncRNA IncDDX47-3 expressions were correlated with immune response-related genes, including IL19, CXCL1, CXCL11, and TNFSF15. Up-regulated IncRNA-TF network consists of 8 TFs and 74 related lncRNAs. The lncRNA-TF-gene trans-regulation consisting of 204 lncRNAs,39 TFs, and correlated 3 genes. Conclusions: These results demonstrate that lncRNAs and circRNAs can influence the progression of DLE. Certain mRNAs/lncRNAs/circRNAs may have substantial value in DLE diagnosis and therapy

Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depth

Conventional self-supervised monocular depth prediction methods are based on a static environment assumption, which leads to accuracy degradation in dynamic scenes due to the mismatch and occlusion problems introduced by object motions. Existing dynamic-object-focused methods only partially solved the mismatch problem at the training loss level. In this paper, we accordingly propose a novel multi-frame monocular depth prediction method to solve these problems at both the prediction and supervision loss levels. Our method, called DynamicDepth, is a new framework trained via a self-supervised cycle consistent learning scheme. A Dynamic Object Motion Disentanglement (DOMD) module is proposed to disentangle object motions to solve the mismatch problem. Moreover, novel occlusion-aware Cost Volume and Re-projection Loss are designed to alleviate the occlusion effects of object motions. Extensive analyses and experiments on the Cityscapes and KITTI datasets show that our method significantly outperforms the state-of-the-art monocular depth prediction methods, especially in the areas of dynamic objects. Our code will be made publicly available

Cancer Treatment With the Ketogenic Diet: A Systematic Review and Meta-analysis of Animal Studies

Background: The ketogenic diet (KD) has been reported to play an important role in the development of cancer by an abundance of pre-clinical experiments; however, their conclusions have been controversial. We therefore aimed to perform a systematic review and meta-analysis of animal studies evaluating the effects of KD on cancer.Methods: Relevant studies were collected by searching PubMed, Embase, and Web of Science. Outcome measures comprised tumor weight, tumor volume, and survival time. Meta-analysis was performed using the random-effect model according to heterogeneity.Results: The search resulted in 1,254 references, of which 38 were included in the review and 17 included in the meta-analysis. Pooled results indicated that KD supplementation significantly prolonged survival time [standardized mean difference (SMD) = 1.76, 95% CI (0.58, 2.94), p = 0.003], and reduced tumor weight [SMD = −2.459, 95% CI (−4.188, −0.730), p = 0.027] and tumor volume [SMD = −0.759, 95% CI (−1.349, −0.168), p = 0.012]. Meta-regression and subgroup analysis results suggested that KD supplementation at a ratio of 4:1 was associated with remarkable prolongation of survival time in animals with limited tumor types.Conclusion: In summary, the pre-clinical evidence pointed toward an overall anti-tumor effect of the KD in animals studies currently available with limited tumor types