Fast Parallel Molecular Algorithms for DNA-Based Computation: Solving the Elliptic Curve Discrete Logarithm Problem over GF(2n)

Elliptic curve cryptographic algorithms convert input data to unrecognizable encryption and the unrecognizable data back again into its original decrypted form. The security of this form of encryption hinges on the enormous difficulty that is required to solve the elliptic curve discrete logarithm problem (ECDLP), especially over GF(2n), n ∈ Z+. This paper describes an effective method to find solutions to the ECDLP by means of a molecular computer. We propose that this research accomplishment would represent a breakthrough for applied biological computation and this paper demonstrates that in principle this is possible. Three DNA-based algorithms: a parallel adder, a parallel multiplier, and a parallel inverse over GF(2n) are described. The biological operation time of all of these algorithms is polynomial with respect to n. Considering this analysis, cryptography using a public key might be less secure. In this respect, a principal contribution of this paper is to provide enhanced evidence of the potential of molecular computing to tackle such ambitious computations

An miR-200 Cluster on Chromosome 23 Regulates Sperm Motility in Zebrafish

Besides its well-documented roles in cell proliferation, apoptosis, and carcinogenesis, the function of the p53-microRNA axis has been recently revealed in the reproductive system. Recent studies indicated that miR-200 family members are dysregulated in nonobstructive azoospermia patients, whereas their functions remain poorly documented. The aim of this study was to investigate the function of the miR-200 family on zebrafish testis development and sperm activity. There was no substantial difference in testis morphology and histology between wild-type (WT) and knockout zebrafish with deletion of miR-200 cluster on chromosome 6 (chr6-miR-200-KO) or on chromosome 23 (chr23-miR-200-KO). Interestingly, compared with WT zebrafish, the chr6-miR-200-KO zebrafish had no difference on sperm motility, whereas chr23-miR-200-KO zebrafish showed significantly improved sperm motility. Consistently, ectopic expression of miR-429a, miR-200a, and miR-200b, which are located in the miR-200 cluster on chromosome 23, significantly reduced motility traits of sperm. Several sperm motility-related genes, such as amh, wt1a, and srd5a2b have been confirmed as direct targets of miR-200s on chr23. 17a-ethynylestradiol (EE2) exposure resulted in upregulated expression of p53 and miR-429a in testis and impairment of sperm motility. Strikingly, in p53 mutant zebrafish testis, the expression levels of miR-200s on chr23 were significantly reduced and accompanied by a stimulation of sperm motility. Moreover, the upregulation of miR-429a associated with EE2 treatment was abolished in testis with p53 mutation. And the impairment of sperm activity by EE2 treatment was also eliminated when p53 was mutated. Together, our results reveal that miR-200 cluster on chromosome 23 controls sperm motility in a p53-dependent manner.</p

Pre-training of Equivariant Graph Matching Networks with Conformation Flexibility for Drug Binding

The latest biological findings observe that the traditional motionless 'lock-and-key' theory is not generally applicable because the receptor and ligand are constantly moving. Nonetheless, remarkable changes in associated atomic sites and binding pose can provide vital information in understanding the process of drug binding. Based on this mechanism, molecular dynamics (MD) simulations were invented as a useful tool for investigating the dynamic properties of a molecular system. However, the computational expenditure limits the growth and application of protein trajectory-related studies, thus hindering the possibility of supervised learning. To tackle this obstacle, we present a novel spatial-temporal pre-training method based on the modified Equivariant Graph Matching Networks (EGMN), dubbed ProtMD, which has two specially designed self-supervised learning tasks: an atom-level prompt-based denoising generative task and a conformation-level snapshot ordering task to seize the flexibility information inside MD trajectories with very fine temporal resolutions. The ProtMD can grant the encoder network the capacity to capture the time-dependent geometric mobility of conformations along MD trajectories. Two downstream tasks are chosen, i.e., the binding affinity prediction and the ligand efficacy prediction, to verify the effectiveness of ProtMD through linear detection and task-specific fine-tuning. We observe a huge improvement from current state-of-the-art methods, with a decrease of 4.3% in RMSE for the binding affinity problem and an average increase of 13.8% in AUROC and AUPRC for the ligand efficacy problem. The results demonstrate valuable insight into a strong correlation between the magnitude of conformation's motion in the 3D space (i.e., flexibility) and the strength with which the ligand binds with its receptor

Anti-inflammatory effect of dental pulp stem cells

Dental pulp stem cells (DPSCs) have received a lot of attention as a regenerative medicine tool with strong immunomodulatory capabilities. The excessive inflammatory response involves a variety of immune cells, cytokines, and has a considerable impact on tissue regeneration. The use of DPSCs for controlling inflammation for the purpose of treating inflammation-related diseases and autoimmune disorders such as supraspinal nerve inflammation, inflammation of the pulmonary airways, systemic lupus erythematosus, and diabetes mellitus is likely to be safer and more regenerative than traditional medicines. The mechanism of the anti-inflammatory and immunomodulatory effects of DPSCs is relatively complex, and it may be that they themselves or some of the substances they secrete regulate a variety of immune cells through inflammatory immune-related signaling pathways. Most of the current studies are still at the laboratory cellular level and animal model level, and it is believed that through the efforts of more researchers, DPSCs/SHED are expected to be transformed into excellent drugs for the clinical treatment of related diseases

A network-based approach to uncover microRNA-mediated disease comorbidities and potential pathobiological implications.

Disease-disease relationships (e.g., disease comorbidities) play crucial roles in pathobiological manifestations of diseases and personalized approaches to managing those conditions. In this study, we develop a network-based methodology, termed meta-path-based Disease Network (mpDisNet) capturing algorithm, to infer disease-disease relationships by assembling four biological networks: disease-miRNA, miRNA-gene, disease-gene, and the human protein-protein interactome. mpDisNet is a meta-path-based random walk to reconstruct the heterogeneous neighbors of a given node. mpDisNet uses a heterogeneous skip-gram model to solve the network representation of the nodes. We find that mpDisNet reveals high performance in inferring clinically reported disease-disease relationships, outperforming that of traditional gene/miRNA-overlap approaches. In addition, mpDisNet identifies network-based comorbidities for pulmonary diseases driven by underlying miRNA-mediated pathobiological pathways (i.e., hsa-let-7a- or hsa-let-7b-mediated airway epithelial apoptosis and pro-inflammatory cytokine pathways) as derived from the human interactome network analysis. The mpDisNet offers a powerful tool for network-based identification of disease-disease relationships with miRNA-mediated pathobiological pathways

Effect of Tanshinone IIA on gut microbiome in diabetes-induced cognitive impairment

Diabetes-induced cognitive impairment (DCI) presents a major public health risk among the aging population. Previous clinical attempts on known therapeutic targets for DCI, such as depleted insulin secretion, insulin resistance, and hyperglycaemia have delivered poor patient outcomes. However, recent evidence has demonstrated that the gut microbiome plays an important role in DCI by modulating cognitive function through the gut–brain crosstalk. The bioactive compound tanshinone IIA (TAN) has shown to improve cognitive and memory function in diabetes mellitus models, though the pharmacological actions are not fully understood. This study aims to investigate the effect and underlying mechanism of TAN in attenuating DCI in relation to regulating the gut microbiome. Metagenomic sequencing analyses were performed on a group of control rats, rats with diabetes induced by a high-fat/high-glucose diet (HFD) and streptozotocin (STZ) (model group) and TAN-treated diabetic rats (TAN group). Cognitive and memory function were assessed by the Morris water maze test, histopathological assessment of brain tissues, and immunoblotting of neurological biomarkers. The fasting blood glucose (FBG) level was monitored throughout the experiments. The levels of serum lipopolysaccharide (LPS) and tumor necrosis factor-α (TNF-α) were measured by enzyme-linked immunoassays to reflect the circulatory inflammation level. The morphology of the colon barrier was observed by histopathological staining. Our study confirmed that TAN reduced the FBG level and improved the cognitive and memory function against HFD- and STZ-induced diabetes. TAN protected the endothelial tight junction in the hippocampus and colon, regulated neuronal biomarkers, and lowered the serum levels of LPS and TNF-α. TAN corrected the reduced abundance of Bacteroidetes in diabetic rats. At the species level, TAN regulated the abundance of B. dorei, Lachnoclostridium sp. YL32 and Clostridiodes difficile. TAN modulated the lipid metabolism and biosynthesis of fatty acids in related pathways as the main functional components. TAN significantly restored the reduced levels of isobutyric acid and butyric acid. Our results supported the use of TAN as a promising therapeutic agent for DCI, in which the underlying mechanism may be associated with gut microbiome regulation

A Mismatch-Tolerant Reverse Transcription Loop-Mediated Isothermal Amplification Method and Its Application on Simultaneous Detection of All Four Serotype of Dengue Viruses

Loop-mediated isothermal amplification (LAMP) has been widely used in the detection of pathogens causing infectious diseases. However, mismatches between primers (especially in the 3′-end) and templates significantly reduced the amplification efficiency of LAMP, and limited its application to genetically diverse viruses. Here, we reported a novel mismatch-tolerant LAMP assay and its application in the detection of dengue viruses (DENV). The novel method features the addition of as little as 0.15 U of high-fidelity DNA polymerase to the standard 25 μl LAMP reaction mixture. This amount was sufficient to remove the mismatched bases at the 3′-end of primers, thereby resulting in excellent tolerance for various mismatches occurring at the 3′-end of the LAMP primers during amplification. This novel LAMP assay has a markedly improved amplification efficiency especially for the mutants forming mismatches with internal primers (FIP/BIP) and loop primers (FLP/BLP). The reaction time of the novel method was about 5.6–22.6 min faster than the conventional LAMP method regardless of the presence or absence of mismatches between primers and templates. Using the novel method, we improved a previously established pan-serotype assay for DENV, and demonstrated greater sensitivity for detection of four DENV serotypes than the previous one. The limit of detection (LOD) of the novel assay was 74, 252, 78, and 35 virus RNA copies per reaction for DENV-1, DENV-2, DENV-3, and DENV-4, respectively. Among 153 clinical samples from patients with suspected DENV infection, the novel assay detected 94.8% samples being DENV positive, higher than that detected by the commercial NS1 antigen assay (92.2%), laboratory-based RT-PCR method (78.4%), and the conventional RT-LAMP assay (86.9%). Furthermore, the novel RT-LAMP assay has been developed into a visual determination method by adding colorimetric dyes. Because of its simplicity, all LAMP-based diagnostic assays may be easily updated to the newly improved version. The novel mismatch-tolerant LAMP method represents a simple, sensitive and promising approach for molecular diagnosis of highly variable viruses, and it is especially suited for application in resource-limited settings

Associations of the Triglyceride and Glucose Index With Hypertension Stages, Phenotypes, and Their Progressions Among Middle-Aged and Older Chinese

Objectives: To assess the associations of the triglyceride and glucose (TyG) index with hypertension stages, phenotypes, and their progressions.Methods: The data originated from the China Health and Retirement Longitudinal Study. Multinomial logistic regression investigated the associations of the TyG index with hypertension stages (stage 1, stage 2), phenotypes (isolated systolic hypertension [ISH], isolated diastolic hypertension [IDH], systolic diastolic hypertension [SDH]), their progressions.Results: Compared with the lowest quartile of TyG index, the highest quartile was associated with increased risks of stage 1 hypertension (OR 1.71, 95% CI 1.38–2.13), stage 2 (1.74, 1.27–2.38), ISH (1.66, 1.31–2.11), IDH (2.52, 1.26–5.05), and SDH (1.65, 1.23–2.23). Similar results were found when TyG index was a continuous variable. From 2011 to 2015, a higher baseline TyG index was associated with normotension to stage 1 (per-unit: 1.39, 1.16–1.65), normotension to ISH (per-unit: 1.28, 1.04–1.56), and normotension to IDH (per-unit: 1.94, 1.27–2.97).Conclusion: The TyG index was associated with different hypertension stages, phenotypes, their progressions, and could be served as a surrogate indicator for early hypertension management

The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family