Modified detrended fluctuation analysis based on empirical mode decomposition

Detrended fluctuation analysis (DFA) is a simple but very efficient method for investigating the power-law long-term correlations of non-stationary time series, in which a detrending step is necessary to obtain the local fluctuations at different timescales. We propose to determine the local trends through empirical mode decomposition (EMD) and perform the detrending operation by removing the EMD-based local trends, which gives an EMD-based DFA method. Similarly, we also propose a modified multifractal DFA algorithm, called an EMD-based MFDFA. The performance of the EMD-based DFA and MFDFA methods is assessed with extensive numerical experiments based on fractional Brownian motion and multiplicative cascading process. We find that the EMD-based DFA method performs better than the classic DFA method in the determination of the Hurst index when the time series is strongly anticorrelated and the EMD-based MFDFA method outperforms the traditional MFDFA method when the moment order $q$ of the detrended fluctuations is positive. We apply the EMD-based MFDFA to the one-minute data of Shanghai Stock Exchange Composite index, and the presence of multifractality is confirmed.Comment: 6 RevTex pages including 5 eps figure

Direct phasing of one-wavelength anomalous-scattering data of the protein core streptavidin

The direct method [Fan, Hao, Gu, Qian, Zheng & Ke (1990). Acta Cryst. A46, 935-939] was used to break the phase ambiguity intrinsic to one-wavelength anomalous scattering data from a known protein of moderate size, core streptavidin, which was solved originally with three-wavelength anomalous diffraction data [Hendrickson, Pähler, Smith, Satow, Merritt & Phizackerley (1989). Proc. Natl Acad. Sci. USA, 86, 2190-2194]. Unlike that in the previous test with a small protein, the Fourier map calculated with the direct-method phases could not clearly reveal the moderate-sized protein structure. However, the phases can be improved step by step using Wang's solvent-flattening method, non-crystallographic symmetry averaging and the skeletonization method. The final electron-density map clearly shows most Calpha positions and some side chains and it is traceable without prior knowledge of the structure. It is concluded that the direct method is capable of breaking the OAS phase ambiguity of a moderate-sized protein at moderate resolution such as 3 A, while the combination of direct methods with macromolecular techniques may produce phases good enough for unknown protein structure to be traced

Epigenetic Regulation in Cancer

Epigenetic modifications are defined as heritable changes in gene activity that do not involve changes in the underlying DNA sequence. The oncogenic process is driven by the accumulation of alterations that impact genome\u27s structure and function. Genetic mutations, which directly disrupt the DNA sequence, are complemented by epigenetic modifications that modulate gene expression, thereby facilitating the acquisition of malignant characteristics. Principals among these epigenetic changes are shifts in DNA methylation and histone mark patterns, which promote tumor development and metastasis. Notably, the reversible nature of epigenetic alterations, as opposed to the permanence of genetic changes, positions the epigenetic machinery as a prime target in the discovery of novel therapeutics. Our review delves into the complexities of epigenetic regulation, exploring its profound effects on tumor initiation, metastatic behavior, metabolic pathways, and the tumor microenvironment. We place a particular emphasis on the dysregulation at each level of epigenetic modulation, including but not limited to, the aberrations in enzymes responsible for DNA methylation and histone modification, subunit loss or fusions in chromatin remodeling complexes, and the disturbances in higher-order chromatin structure. Finally, we also evaluate therapeutic approaches that leverage the growing understanding of chromatin dysregulation, offering new avenues for cancer treatment

Comprehensive Analysis of Bulk and Single-Cell Transcriptomic Data Reveals a Novel Signature Associated With Endoplasmic Reticulum Stress, Lipid Metabolism, and Liver Metastasis in Pancreatic Cancer

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with high probability of recurrence and distant metastasis. Liver metastasis is the predominant metastatic mode developed in most pancreatic cancer cases, which seriously affects the overall survival rate of patients. Abnormally activated endoplasmic reticulum stress and lipid metabolism reprogramming are closely related to tumor growth and metastasis. This study aims to construct a prognostic model based on endoplasmic reticulum stress and lipid metabolism for pancreatic cancer, and further explore its correlation with tumor immunity and the possibility of immunotherapy. METHODS: Transcriptomic and clinical data are acquired from TCGA, ICGC, and GEO databases. Potential prognostic genes were screened by consistent clustering and WGCNA methods, and the whole cohort was randomly divided into training and testing groups. The prognostic model was constructed by machine learning method in the training cohort and verified in the test, TCGA and ICGC cohorts. The clinical application of this model and its relationship with tumor immunity were analyzed, and the relationship between endoplasmic reticulum stress and intercellular communication was further explored. RESULTS: A total of 92 characteristic genes related to endoplasmic reticulum stress, lipid metabolism and liver metastasis were identified in pancreatic cancer. We established and validated a prognostic model for pancreatic cancer with 7 signatures, including ADH1C, APOE, RAP1GAP, NPC1L1, P4HB, SOD2, and TNFSF10. This model is considered to be an independent prognosticator and is a more accurate predictor of overall survival than age, gender, and stage. TIDE score was increased in high-risk group, while the infiltration levels of CD8 CONCLUSIONS: We constructed and validated a novel prognostic model for pancreatic cancer, which can also be used as an instrumental variable to predict the prognosis and immune microenvironment. In addition, this study revealed the effect of ER stress on cell-cell communication in the tumor microenvironment

17β-Estradiol Enhances Schwann Cell Differentiation via the ERβ-ERK1/2 Signaling Pathway and Promotes Remyelination in Injured Sciatic Nerves

Remyelination is critical for nerve regeneration. However, the molecular mechanism involved in remyelination is poorly understood. To explore the roles of 17β-estradiol (E2) for myelination in the peripheral nervous system, we used a co-culture model of rat dorsal root ganglion (DRG) explants and Schwann cells (SCs) and a regeneration model of the crushed sciatic nerves in ovariectomized (OVX) and non-ovariectomized (non-OVX) rats for in vitro and in vivo analysis. E2 promoted myelination by facilitating the differentiation of SCs in vitro, which could be inhibited by the estrogen receptors (ER) antagonist ICI182780, ERβ antagonist PHTPP, or ERK1/2 antagonist PD98059. This suggests that E2 accelerates SC differentiation via the ERβ-ERK1/2 signaling. Furthermore, E2 promotes remyelination in crushed sciatic nerves of both OVX and non-OVX rats. Interestingly, E2 also significantly increased the expression of the lysosome membrane proteins LAMP1 and myelin protein P0 in the regenerating nerves. Moreover, P0 has higher degree of colocalization with LAMP1 in the regenerating nerves. Taking together, our results suggest that E2 enhances Schwann cell differentiation and further myelination via the ERβ-ERK1/2 signaling and that E2 increases the expression of myelin proteins and lysosomes in SCs to promotes remyelination in regenerating sciatic nerves

Synthesis and characterization of cobalt hydroxide carbonate nanostructures

Battery-type electrodes of three-dimensional (3D) hierarchical cobalt hydroxide carbonate arrays on Ni foam were fabricated using a hydrothermal method for use in supercapacitors. X-ray diffraction analysis, scanning electron microscopy, and transmission electron microscopy were used to characterize their structures and morphologies. The cobalt hydroxide carbonate synthesized with 10 h reaction time showed the highest specific capacitance (1381 F g−1 at a current density of 2 A g−1) and excellent cycling stability (92% capacitance retention after 5000 cycles). Moreover, its capacitance increased by 33% at 2 A g−1 and by 10% at 20 A g−1 after 5000 charge–discharge cycles. This cobalt hydroxide carbonate composite is a promising candidate for electrochemical energy-related applications

Association of body mass index with rapid eye movement sleep behavior disorder in Parkinson’s disease

BackgroundThe association between body mass index (BMI) and rapid eye-movement (REM) sleep-related behavioral disorder (RBD) in Parkinson’s disease (PD) remains unknown. Our study was to investigate the association of BMI with RBD in PD patients.MethodsIn this cross-sectional study, a total of 1,115 PD participants were enrolled from Parkinson’s Progression Markers Initiative (PPMI) database. BMI was calculated as weight divided by height squared. RBD was defined as the RBD questionnaire (RBDSQ) score with the cutoff of 5 or more assessed. Univariable and multivariable logistic regression models were performed to examine the associations between BMI and the prevalence of RBD. Non-linear correlations were explored with use of restricted cubic spline (RCS) analysis. And the inflection point was determined by the two-line piecewise linear models.ResultsWe identified 426 (38.2%) RBD. The proportion of underweight, normal, overweight and obese was 2.61, 36.59, 40.36, and 20.44%, respectively. In the multivariate logistic regression model with full adjustment for confounding variables, obese individuals had an odds ratio of 1.77 (95% confidence interval: 1.21 to 2.59) with RBD compared with those of normal weight. In the RCS models with three knots, BMI showed a non-linear association with RBD. The turning points of BMI estimated from piecewise linear models were of 28.16 kg/m2, 28.10 kg/m2, and 28.23 kg/m2 derived from univariable and multivariable adjusted logistic regression models. The effect modification by depression on the association between BMI and RBD in PD was also found in this study. Furthermore, the sensitivity analyses linked with cognition, education, and ethnic groups indicated the robustness of our results.ConclusionThe current study found a significant dose–response association between BMI and RBD with a depression-based difference in the impact of BMI on RBD in PD patients

Analysis of codon usage and nucleotide composition bias in polioviruses

<p>Abstract</p> <p>Background</p> <p>Poliovirus, the causative agent of poliomyelitis, is a human enterovirus and a member of the family of Picornaviridae and among the most rapidly evolving viruses known. Analysis of codon usage can reveal much about the molecular evolution of the viruses. However, little information about synonymous codon usage pattern of polioviruses genome has been acquired to date.</p> <p>Methods</p> <p>The relative synonymous codon usage (RSCU) values, effective number of codon (ENC) values, nucleotide contents and dinucleotides were investigated and a comparative analysis of codon usage pattern for open reading frames (ORFs) among 48 polioviruses isolates including 31 of genotype 1, 13 of genotype 2 and 4 of genotype 3.</p> <p>Results</p> <p>The result shows that the overall extent of codon usage bias in poliovirus samples is low (mean ENC = 53.754 > 40). The general correlation between base composition and codon usage bias suggests that mutational pressure rather than natural selection is the main factor that determines the codon usage bias in those polioviruses. Depending on the RSCU data, it was found that there was a significant variation in bias of codon usage among three genotypes. Geographic factor also has some effect on the codon usage pattern (exists in the genotype-1 of polioviruses). No significant effect in gene length or vaccine derived polioviruses (DVPVs), wild viruses and live attenuated virus was observed on the variations of synonymous codon usage in the virus genes. The relative abundance of dinucleotide (CpG) in the ORFs of polioviruses are far below expected values especially in DVPVs and attenuated virus of polioviruses genotype 1.</p> <p>Conclusion</p> <p>The information from this study may not only have theoretical value in understanding poliovirus evolution, especially for DVPVs genotype 1, but also have potential value for the development of poliovirus vaccines.</p