Periodic waves travelling along an unsmooth boundary via the fractal variational theory

Abstract The solitary waves of the fractal Korteweg-de Vries (KdV) equation travelling along an unsmooth boundary is studied by Ji-Huan He, et al (Results in Physics, 2021, 104104 [1] ). In this letter, we obtain its periodic waves travelling along an unsmooth boundary via the fractal variational theory, which is expected to open the new perspectives on the study of the fractal travelling wave theory

To analyze the relationship between gut microbiota, metabolites and migraine: a two-sample Mendelian randomization study

BackgroundIt has been suggested in several observational studies that migraines are associated with the gut microbiota. It remains unclear, however, how the gut microbiota and migraines are causally related.MethodsWe performed a bidirectional two-sample mendelian randomization study. Genome-wide association study (GWAS) summary statistics for the gut microbiota were obtained from the MiBioGen consortium (n = 18,340) and the Dutch Microbiota Project (n = 7,738). Pooled GWAS data for plasma metabolites were obtained from four different human metabolomics studies. GWAS summary data for migraine (cases = 48,975; controls = 450,381) were sourced from the International Headache Genetics Consortium. We used inverse-variance weighting as the primary analysis. Multiple sensitivity analyses were performed to ensure the robustness of the estimated results. We also conducted reverse mendelian randomization when a causal relationship between exposure and migraine was found.ResultsLachnospiraceaeUCG001 (OR = 1.12, 95% CI: 1.05–1.20) was a risk factor for migraine. Blautia (OR = 0.93, 95% CI: 0.88–0.99), Eubacterium (nodatum group; OR = 0.94, 95% CI: 0.90–0.98), and Bacteroides fragilis (OR = 0.97, 95% CI: 0.94–1.00) may have a suggestive association with a lower migraine risk. Functional pathways of methionine synthesis (OR = 0.89, 95% CI: 0.83–0.95) associated with microbiota abundance and plasma hydrocinnamate (OR = 0.85, 95% CI: 0.73–1.00), which are downstream metabolites of Blautia and Bacteroides fragilis, respectively, may also be associated with lower migraine risk. No causal association between migraine and the gut microbiota or metabolites was found in reverse mendelian randomization analysis. Both significant horizontal pleiotropy and significant heterogeneity were not clearly identified.ConclusionThis Mendelian randomization analysis showed that LachnospiraceaeUCG001 was associated with an increased risk of migraine, while some bacteria in the gut microbiota may reduce migraine risk. These findings provide a reference for a deeper comprehension of the role of the gut–brain axis in migraine as well as possible targets for treatment interventions

Thick MgB2 film with (101) oriented micro-crystals

Very thick, ~ 40 $\mu$m, clean, and highly textured MgB2 film was effectively grown on an Al2O3 substrate. The fabrication technique is by the hybrid physical-chemical vapor deposition (HPCVD) using B2H6 gas and Mg ingot as the sources. The X-ray diffraction (XRD) analysis shows a highly (101)-oriented MgB2 crystal structure without any impurity detected. There is no signal from the substrate in the XRD spectrum, indicating that the film thickness exceeds the X-ray penetration length. Scanning electron microscopy (SEM) reveals that the film is composed of highly-packed MgB2 micro-crystals with a uniform size distribution of about 2 $\mu$m in diameter and 0.2 $\mu$m in thickness. According to the compositional analysis of energy-dispersive X-ray spectroscopy (EDX), no oxygen, hence no MgO, exists in the textured film, consistent with the XRD result. Also, the transport properties are similar to those of a single crystal, indicating a clean film of good crystallite. The zero field transition temperatures are determined as TC(onset) = 39.2 K and TC(zero) = 38.4 K, giving a sharp transition typical of a clean sample. The residual resistivity ratio (RRR) is determined as 6.4 and the magnetoreisitance (MR) is about 28 % at 40 K under the applied field of 9 T, which are similar to those of a single crystal. The zero temperature upper critical field, HC2(0), is extrapolated as 19 T from the TC(onset) at applied field up to 9 T.Comment: 10 pages, 4 figure

Efficacy and efficacy-influencing factors of stem cell transplantation on patients with Parkinson’s disease: a systematic review and meta-analysis

BackgroundCell transplants as a treatment for Parkinson’s disease have been studied for decades, and stem cells may be the most promising cell sources for this treatment. We aimed to investigate whether stem cell transplantation contributes to the cure for Parkinson’s disease and the factors that may influence the efficacy for this therapy.MethodsPubMed, Embase, Cochrane Library, Web of Science, SinoMed, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), and ChinaInfo were thoroughly searched to find controlled trials or randomized controlled trials performing stem cell transplantation in patients with Parkinson’s disease. The pooled effects were analyzed to evaluate the weighted mean difference (WMD) with 95% confidence intervals.ResultsNine articles were identified including 129 individuals. Stem cell transplantation was an effective treatment for Parkinson’s disease (WMD = −14.86; 95% CI: −16.62 to −13.10; p < 0.00001), with neural stem cells, umbilical cord mesenchymal stem cells (UCMSCs), and bone marrow mesenchymal stem cells (BMMSCs) being effective cell sources for transplantation. Stem cell transplantation can be effective for at least 12 months, but its long-term effectiveness remains unknown due to the limited studies monitoring patients for more than 1 year, not to mention decades.ConclusionData from controlled trials suggest that stem cell transplantation as a therapy for Parkinson’s disease can be effective for at least 12 months. The factors that may influence its curative effect are time after transplantation and stem cell types.Systematic review registration(Registration ID: CRD42022353145)

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities

Genetic Variations in Plasma Circulating DNA of HBV-Related Hepatocellular Carcinoma Patients Predict Recurrence after Liver Transplantation

BACKGROUND: Recurrence prediction of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients undergoing liver transplantation (LT) present a great challenge because of a lack of biomarkers. Genetic variations play an important role in tumor development and metastasis. METHODS: Oligonucleotide microarrays were used to evaluate the genetic characteristics of tumor DNA in 30 HBV-related HCC patients who were underwent LT. Recurrence-related single-nucleotide polymorphism were selected, and their prognostic value was assessed and validated in two independent cohorts of HCC patients (N = 102 and N = 77), using pretransplant plasma circulating DNA. Prognostic significance was assessed by Kaplan-Meier survival estimates and log-rank tests. Multivariate analyses were performed to evaluate prognosis-related factors. RESULTS: rs894151 and rs12438080 were significantly associated with recurrence (P = .003 and P = .004, respectively). Multivariate analyses demonstrated that the co-index of the 2 SNPs was an independent prognostic factor for recurrence (P = .040). Similar results were obtained in the third cohort (N = 77). Furthermore, for HCC patients (all the 3 cohorts) exceeding Milan criteria, the co-index was a prognostic factor for recurrence and survival (P<.001 and P = .002, respectively). CONCLUSIONS: Our study demonstrated first that genetic variations of rs894151 and rs12438080 in pretransplant plasma circulating DNA are promising prognostic markers for tumor recurrence in HCC patients undergoing LT and identify a subgroup of patients who, despite having HCC exceeding Milan criteria, have a low risk of post-transplant recurrence