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Abstract Observational and genetic studies have reported the relationship between dyslexia and Alzheimer’s disease (AD). Until now, the causal effect of dyslexia on AD risk has remained unclear. We conducted a two-sample univariable Mendelian randomization (MR) analysis to determine the causal association between dyslexia and the risk of AD, vascular dementia (VD), Lewy body dementia (LBD), and frontotemporal dementia (FTD) and its four subtypes. First, we selected 42 dyslexia genetic variants from a large-scale genome-wide association studies (GWAS) dataset and extracted their corresponding GWAS summary statistics from AD, VD, LBD, and FTD. Second, we selected four MR methods, including inverse-variance weighted (IVW), weighted median, MR-Egger, and MR-PRESSO. Heterogeneity, horizontal pleiotropy, and leave-one-out sensitivity analysis were then used to evaluate the reliability of all causal estimates. We also conducted multivariable MR (MVMR) and mediation analysis to assess the potential mediating role of cognitive performance (CP) or educational achievement (EA) on the causal association between dyslexia and AD. Two MVMR methods, including MV IVW and MV-Egger, and two-step MR were used to perform the analysis. Using IVW, we found a significant causal association between increased dyslexia and increased risk of AD (OR = 1.15, 95% CI: 1.04–1.28, P = 0.006), but not VD, LBD, FTD, or its four subtypes. MR-PRESSO further supported the statistically significant association between dyslexia and AD (OR = 1.15, 95% CI: 1.05–1.27, P = 0.006). All sensitivity analyses confirmed the reliability of causal estimates. Using MV IVW and mediation analysis, we found no causal relationship between dyslexia and AD after adjusting for CP but not EA, CP mediated the total effect of dyslexia on AD with a proportion of 46.32%. We provide genetic evidence to support a causal effect of increased dyslexia on increased risk of AD, which was largely mediated by CP. Reading activity may be a potential intervention strategy for AD by improving cognitive function.

Abstract Background There is an association between migraine and dementia, however, their causal relationship remains unclear. This study employed bidirectional two-sample Mendelian randomization (MR) to investigate the potential causal relationship between migraine and dementia and its subtypes: Alzheimer’s disease (AD), vascular dementia (VaD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB). Methods Summary-level statistics data were obtained from publicly available genome-wide association studies (GWAS) for both migraine and five types of dementia. Single nucleotide polymorphisms (SNPs) associated with migraine and each dementia subtype were selected. MR analysis was conducted using inverse variance weighting (IVW) and weighted median (WM) methods. Sensitivity analyses included Cochran’s Q test, MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, the intercept of MR-Egger, and leave-one-out analysis. Results Migraine showed a significant causal relationship with AD and VaD, whereas no causal relationship was observed with all-cause dementia, FTD, or DLB. Migraine may be a potential risk factor for AD (odds ratio [OR]: 1.09; 95% confidence interval [CI]: 0.02–0.14; P = 0.007), while VaD may be a potential risk factor for migraine (OR: 1.04; 95% CI: 0.02–0.06; P = 7.760E-5). Sensitivity analyses demonstrated the robustness of our findings. Conclusion Our study suggest that migraine may have potential causal relationships with AD and VaD. Migraine may be a risk factor for AD, and VaD may be a risk factor for migraine. Our study contributes to unraveling the comprehensive genetic associations between migraine and various types of dementia, and our findings will enhance the academic understanding of the comorbidity between migraine and dementia.

Stroke remains the leading cause of death and disability in some countries, predominantly attributed to acute ischemic stroke (AIS). While intravenous thrombolysis and endovascular thrombectomy are widely acknowledged as effective treatments for AIS, boasting a high recanalization rate, there is a significant discrepancy between the success of revascularization and the mediocre clinical outcomes observed among patients with AIS. It is now increasingly understood that the implementation of effective cerebral protection strategies, serving as adjunctive treatments to reperfusion, can potentially improve the outcomes of AIS patients following recanalization therapy. Herein, we reviewed several promising cerebral protective methods that have the potential to slow down infarct growth and protect ischemic penumbra. We dissect the underlying reasons for the mismatch between high recanalization rates and moderate prognosis and introduce a novel concept of “multi-target and multi-phase adjunctive cerebral protection” to guide our search for neuroprotective agents that can be administered alongside recanalization therapy.

Equisetin was isolated from endophytic fungus Fusarium sp. JDJR1 via bioassay-guided isolation, and it was evaluated as an anti-microbial and herbicidal agent. Bioactivity assessments revealed that equisetin exhibited a broad spectrum of fungicidal and anti-bacterial activity against various plant pathogens. The EC50 values against Botrytis cinerea, Fusarium graminearum, Sclerotinia sclerotiorum, and Rhizoctonia solani ranged from 10.7 to 21.0 μg/mL. Notably, equisetin demonstrated activity against Xanthomonas oryzae pv. oryzicola, Xanthomonas oryzae pv. oryzae and Pseudomonas solanacearum with an MIC range of 4–16 μg/mL, surpassing the efficacy of the positive control: streptomycin sulfate. Equisetin, at a concentration of 100 μg/mL, could completely inhibit the spore germination of F. graminearum. In in vivo protection experiments, the protective efficacy of equisetin against B. cinerea on tomato fruits at 200 μg/mL reached 72.9%. Furthermore, in herbicidal activity tests that use the Petri dish bioassay method, equisetin had a good inhibitory effect on the root growth of weeds. At a concentration of 100 μg/mL, the inhibition rates for Echinochloa crusgalli and Eclipta prostrata root were 98.8 and 94.4%, respectively.

Abstract Background Until now, Mendelian randomization (MR) studies have investigated the causal association of risk factors with Alzheimer’s disease (AD) using large-scale AD genome-wide association studies (GWAS), GWAS by proxy (GWAX), and meta-analyses of GWAS and GWAX (GWAS+GWAX) datasets. However, it currently remains unclear about the consistency of MR estimates across these GWAS, GWAX, and GWAS+GWAX datasets. Methods Here, we first selected 162 independent educational attainment genetic variants as the potential instrumental variables (N = 405,072). We then selected one AD GWAS dataset (N = 63,926), two AD GWAX datasets (N = 314,278 and 408,942), and three GWAS+GWAX datasets (N = 388,324, 455,258, and 472,868). Finally, we conducted a MR analysis to evaluate the impact of educational attainment on AD risk across these datasets. Meanwhile, we tested the genetic heterogeneity of educational attainment genetic variants across these datasets. Results In AD GWAS dataset, MR analysis showed that each SD increase in years of schooling (about 3.6 years) was significantly associated with 29% reduced AD risk (OR=0.71, 95% CI: 0.60–0.84, and P=1.02E−04). In AD GWAX dataset, MR analysis highlighted that each SD increase in years of schooling significantly increased 84% AD risk (OR=1.84, 95% CI: 1.59–2.13, and P=4.66E−16). Meanwhile, MR analysis suggested the ambiguous findings in AD GWAS+GWAX datasets. Heterogeneity test indicated evidence of genetic heterogeneity in AD GWAS and GWAX datasets. Conclusions We highlighted significant difference and genetic heterogeneity in clinically diagnosed AD GWAS and self-report proxy phenotype GWAX. Our MR findings are consistent with recent findings in AD genetic variants. Hence, the GWAX and GWAS+GWAX findings and MR findings from GWAX and GWAS+GWAX should be carefully interpreted and warrant further investigation using the AD GWAS dataset.

BackgroundThe causality between plasma branched-chain amino acids (BCAAs) levels and stroke remains uncertain and the stratified research on the association between BCAAs levels and subtypes of stroke is not well studied. Therefore, the association of genetically proxied circulating BCAA levels with the risks of stroke and its subtypes was explored by Mendelian randomization (MR) in this study.MethodsSummary-level data derived from the published genome-wide association studies (GWAS) were employed for analyses. Data for plasma BCAA levels (n = 16,596) were obtained from a meta-analysis of GWAS. The MEGASTROKE consortium provided data for ischemic stroke (n = 440,328) and its subtypes and data for hemorrhagic stroke were available from 2 meta-analyses of GWAS of European-ancestry groups (intracerebral hemorrhage, n = 3,026; subarachnoid hemorrhage, n = 77,074). The inverse variance weighted (IVW) method was selected as the primary MR analysis. Supplementary analysis used included the weighted median, MR-Egger regression, Cochran’s Q statistic, MR Pleiotropy Residual Sum and Outlier global test, and leave-one-out analysis method.ResultsAccording to IVW analysis, 1-SD increment in genetically determined circulating isoleucine was associated with increased risks of cardioembolic stroke (CES) (OR: 1.56, 95% CI: 1.21–2.20, P = 0.0007), but not with risks of other stroke subtypes. We could not discover any proof that leucine and valine levels could increase risk of any stroke subtype. All heterogeneity tests produced stable findings, and there was no concrete evidence to indicate the perturbation of horizontal multiplicity.ConclusionIncreasing plasma isoleucine level had a causal effect on the risk of CES but not on the risk of other stroke subtypes. Further research is needed to identify the mechanisms of the causal associations between BCAAs and stroke subtypes.

Nucleus basalis of Meynert (NbM), one of the earliest targets of Alzheimer's disease (AD), may act as a seed for pathological spreading to its connected regions. However, the underlying basis of regional vulnerability to NbM dysconnectivity remains unclear. NbM functional dysconnectivity was assessed using resting-state fMRI data of health controls and mild cognitive impairment (MCI) patients from the Alzheimer's disease Neuroimaging Initiative (ADNI2/GO phase). Transcriptional correlates of NbM dysconnectivity was explored by leveraging public intrinsic and differential post-mortem brain-wide gene expression datasets from Allen Human Brain Atlas (AHBA) and Mount Sinai Brain Bank (MSBB). By constructing an individual-level tissue-specific gene set risk score (TGRS), we evaluated the contribution of NbM dysconnectivity-correlated gene sets to change rate of cerebral spinal fluid (CSF) biomarkers during preclinical stage of AD, as well as to MCI onset age. An independent cohort of health controls and MCI patients from ADNI3 was used to validate our main findings. Between-group comparison revealed significant connectivity reduction between the right NbM and right middle temporal gyrus in MCI. This regional vulnerability to NbM dysconnectivity correlated with intrinsic expression of genes enriched in protein and immune functions, as well as with differential expression of genes enriched in cholinergic receptors, immune, vascular and energy metabolism functions. TGRS of these NbM dysconnectivity-correlated gene sets are associated with longitudinal amyloid-beta change at preclinical stages of AD, and contributed to MCI onset age independent of traditional AD risks. Our findings revealed the transcriptional vulnerability to NbM dysconnectivity and their crucial role in explaining preclinical amyloid-beta change and MCI onset age, which offer new insights into the early AD pathology and encourage more investigation and clinical trials targeting NbM.

Abstract Background Until now, epidemiological evidence regarding the association between vitamin C intake (both diet and supplements) and Parkinson’s disease (PD) remains inconsistent. Hence, it is necessary to establish the causal link between vitamin C levels and PD, and further develop effective therapies or prevention. Methods We selected 11 newly identified plasma vitamin C genetic variants from a large-scale plasma vitamin C GWAS dataset (n = 52,018) as the effective instrumental variables, and extracted their corresponding GWAS summary statistics from PD (33,674 PD cases and 449,056 controls) and PD age at onset (AAO) (n = 28,568). We then performed a Mendelian randomization (MR) study to evaluate the causal association of plasma vitamin C levels with PD and PD AAO using inverse-variance weighted (IVW), the weighted median, MR-Egger, and MR-PRESSO test. Results We did not observe any significant association between genetically increased vitamin C levels and PD. Interestingly, we found a reduced trend of PD AAO (1.134 years) with 1 SD genetically increased vitamin C levels using IVW (beta = − 1.134, 95% CI: [− 2.515, 0.248], P = 0.108). Importantly, this trend was further successfully verified using both weighted median and MR-Egger. Each 1 SD genetically increased vitamin C levels could reduce PD AAO 1.75 and 2.592 years using weighted median (beta = − 1.750, 95% CI: [− 3.396, − 0.105], P = 0.037) and MR-Egger (beta = − 2.592, 95% CI: [− 4.623, − 0.560], P = 0.012). Conclusions We demonstrated the causal association between genetically increased plasma vitamin C levels and reduced PD AAO in people of European descent. Randomized controlled trials are required to clarify whether diet intake or supplement, or both could reduce the AAO of PD.

Diaporthe species produce versatile secondary metabolites (SMs), including terpenoids, fatty acids, polyketides, steroids, and alkaloids. These structurally diverse SMs exhibit a wide range of biological activities, including cytotoxic, antifungal, antibacterial, antiviral, antioxidant, anti-inflammatory, and phytotoxic activities, which could be exploited in the medical, agricultural, and other modern industries. This review comprehensively covers the production and biological potencies of isolated natural products from the genus Diaporthe associated with terrestrial and marine origins. A total of 275 SMs have been summarized from terrestrial (153; 55%) and marine (110; 41%) origins during the last twelve years, and 12 (4%) compounds are common to both environments. All secondary metabolites are categorized predominantly on the basis of their bioactivities (cytotoxic, antibacterial, antifungal, and miscellaneous activity). Overall, 134 bioactive compounds were isolated from terrestrial (92; 55%) and marine (42; 34%) origins, but about half the compounds did not report any kind of activity. The antiSMASH results suggested that Diaporthe strains are capable of encoding a wide range of SMs and have tremendous biosynthetic potential for new SMs. This study will be useful for future research on drug discovery from terrestrial and marine natural products.

Abstract Background It has been well established that the TMEM106B gene rs1990622 variant was a frontotemporal dementia (FTD) risk factor. Until recently, growing evidence highlights the role of TMEM106B in Alzheimer’s disease (AD). However, it remains largely unclear about the role of rs1990622 variant in AD. Methods Here, we conducted comprehensive analyses including genetic association study, gene expression analysis, eQTLs analysis, and colocalization analysis. In stage 1, we conducted a genetic association analysis of rs1990622 using large-scale genome-wide association study (GWAS) datasets from International Genomics of Alzheimer’s Project (21,982 AD and 41,944 cognitively normal controls) and UK Biobank (314,278 participants). In stage 2, we performed a gene expression analysis of TMEM106B in 49 different human tissues using the gene expression data in GTEx. In stage 3, we performed an expression quantitative trait loci (eQTLs) analysis using multiple datasets from UKBEC, GTEx, and Mayo RNAseq Study. In stage 4, we performed a colocalization analysis to provide evidence of the AD GWAS and eQTLs pair influencing both AD and the TMEM106B expression at a particular region. Results We found (1) rs1990622 variant T allele contributed to AD risk. A sex-specific analysis in UK Biobank further indicated that rs1990622 T allele only contributed to increased AD risk in females, but not in males; (2) TMEM106B showed different expression in different human brain tissues especially high expression in cerebellum; (3) rs1990622 variant could regulate the expression of TMEM106B in human brain tissues, which vary considerably in different disease statuses, the mean ages at death, the percents of females, and the different descents of the selected donors; (4) colocalization analysis provided suggestive evidence that the same variant contributed to AD risk and TMEM106B expression in cerebellum. Conclusion Our comprehensive analyses highlighted the role of FTD rs1990622 variant in AD risk. This cross-disease approach may delineate disease-specific and common features, which will be important for both diagnostic and therapeutic development purposes. Meanwhile, these findings highlight the importance to better understand TMEM106B function and dysfunction in the context of normal aging and neurodegenerative diseases.

A endo-1,4-β-mannanase (CcMan5C) gene was cloned from Coprinopsis cinerea and heterologously expressed in Pichia pastoris, and the recombinant enzyme was purified by Ni-affinity chromatography and identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/TOF-MS). CcMan5C hydrolyzed only locust bean gum galactomannan (LBG) but not α-mannan from S. cerevisiae or Avicel cellulose, oat spelt xylan, or laminarin from Laminaria digitata. CcMan5C exhibited distinctive catalytic features that were different from previously reported β-mannanases. (1) CcMan5C is the first reported fungal β-mannase with an optimal alkalic pH of 8.0–9.0 for hydrolytic activity under assay conditions. (2) CcMan5C is the first reported alkalic fungal β-mannase with an optimal temperature of 70 °C for hydrolytic activity under assay conditions. (3) The organic solvents methanol, ethanol, isopropanol, and acetone at concentrations of 10% or 20% did not inhibit CcMan5C activity, while 10% or 20% isopropanol and acetone even enhanced CcMan5C activity by 9.20–34.98%. Furthermore, CcMan5C tolerated detergents such as Tween 20 and Triton X-100, and its activity was even enhanced to 26.2–45.6% by 1% or 10% Tween 20 and Triton X-100. (4) CcMan5C solution or lyophilized CcMan5C exhibited unchanged activity and even increasing activity after being stored at −20 °C or −80 °C for 12 months and retained above 50% activity after being stored at 4 °C for 12 months. These features make CcMan5C a suitable candidate for the detergent industry and paper and pulp industry.

Chemical investigation of the plant-derived endophytic fungus Diaporthe unshiuensis YSP3 led to the isolation of four new compounds (1–4), including two new xanthones (phomopthane A and B, 1 and 2), one new alternariol methyl ether derivative (3) and one α-pyrone derivative (phomopyrone B, 4), together with eight known compounds (5–12). The structures of new compounds were interpreted on the basis of spectroscopic data and single-crystal X-ray diffraction analysis. All new compounds were assessed for their antimicrobial and cytotoxic potential. Compound 1 showed cytotoxic activity against HeLa and MCF-7 cells with IC50 values of 5.92 µM and 7.50 µM, respectively, while compound 3 has an antibacterial effect on Bacillus subtilis (MIC value 16 μg/mL).

Abstract Epigenome‐wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next‐generation, and third‐generation sequencing technologies have prepared a high‐quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

Anthracycline dutomycin is a tetracyclic quinone glycoside produced by Streptomyces minoensis NRRL B-5482. SW91 is a C-12 demethylated dutomycin derivative, which was identified in our previous research. In vitro cytotoxicity and apoptosis assays of these two compounds were conducted to demonstrate their antiproliferation activities. The results showed that both dutomycin and SW91 block cells at the S phase, whereas dutomycin shows more significant inhibition of cell growth. Their interactions with calf thymus DNA (CT-DNA) were investigated, with dutomycin exhibiting higher binding affinity. The molecular docking demonstrated that the 12-methyl group makes dutomycin attach to the groove of DNA. These findings suggest that dutomycin has binding higher affinity to DNA and impairs DNA replication resulting in more significant antitumor activity.

Abstract Background The development of single-cell RNA sequencing has enabled profound discoveries in biology, ranging from the dissection of the composition of complex tissues to the identification of novel cell types and dynamics in some specialized cellular environments. However, the large-scale generation of single-cell RNA-seq (scRNA-seq) data collected at multiple time points remains a challenge to effective measurement gene expression patterns in transcriptome analysis. Results We present an algorithm based on the Dynamic Time Warping score (DTWscore) combined with time-series data, that enables the detection of gene expression changes across scRNA-seq samples and recovery of potential cell types from complex mixtures of multiple cell types. Conclusions The DTWscore successfully classify cells of different types with the most highly variable genes from time-series scRNA-seq data. The study was confined to methods that are implemented and available within the R framework. Sample datasets and R packages are available at https://github.com/xiaoxiaoxier/DTWscore .

The molecular mechanism that maintains the pluripotency of embryonic stem cells (ESCs) is not well understood but may be reflected in complex biological networks. However, there have been few studies on the effects of transcriptional and post-transcriptional regulation during the development of ESCs from the perspective of computational systems biology. In this study, we analyzed the topological properties of the "core" pluripotency transcription factors (TFs) OCT4, SOX2 and NANOG in protein-protein interaction networks (PPINs). Further, we identified synergistic interactions between these TFs and microRNAs (miRNAs) in PPINs during ESC development. Results show that there were significant differences in centrality characters between TF-targets and non-TF-targets in PPINs. We also found that there was consistent regulation of multiple "core" pluripotency TFs. Based on the analysis of shortest path length, we found that the module properties were not only within the targets regulated by common or multiple "core" pluripotency TFs but also between the groups of targets regulated by different TFs. Finally, we identified synergistic regulation of these TFs and miRNAs. In summary, the synergistic effects of "core" pluripotency TFs and miRNAs were analyzed using computational methods in both human and mouse PPINs.

Traditional permutation (TradPerm) tests are usually considered the gold standard for multiple testing corrections. However, they can be difficult to complete for the meta-analyses of genetic association studies based on multiple single nucleotide polymorphism loci as they depend on individual-level genotype and phenotype data to perform random shuffles, which are not easy to obtain. Most meta-analyses have therefore been performed using summary statistics from previously published studies. To carry out a permutation using only genotype counts without changing the size of the TradPerm P-value, we developed a Monte Carlo permutation (MCPerm) method. First, for each study included in the meta-analysis, we used a two-step hypergeometric distribution to generate a random number of genotypes in cases and controls. We then carried out a meta-analysis using these random genotype data. Finally, we obtained the corrected permutation P-value of the meta-analysis by repeating the entire process N times. We used five real datasets and five simulation datasets to evaluate the MCPerm method and our results showed the following: (1) MCPerm requires only the summary statistics of the genotype, without the need for individual-level data; (2) Genotype counts generated by our two-step hypergeometric distributions had the same distributions as genotype counts generated by shuffling; (3) MCPerm had almost exactly the same permutation P-values as TradPerm (r = 0.999; P

Demographic events such as migration, and evolutionary events like mutation and recombination, have contributed to the genetic variations that are found in the human genome. During the evolution and differentiation of human populations, different functional genes and pathways (a group of genes that act together to perform specific biological tasks) would have displayed different degrees of genetic diversity or evolutionary conservatism. To query the genetic differences of functional genes or pathways in populations, we have developed the human gene population genetic difference (HGPGD) database. Currently, 11 common population genetic features, 18,158 single human genes, 220 KEGG (Kyoto Encyclopedia of Genes and Genomes) human pathways and 4,639 Gene Ontology (GO) categories (3,269 in biological process; 862 in molecular function; and 508 in cellular component) are available in the HGPGD database. The 11 population genetic features are related mainly to three aspects: allele frequency, linkage disequilibrium pattern, and transferability of tagSNPs. By entering a list of Gene IDs, KEGG pathway IDs or GO category IDs and selecting a population genetic feature, users can search the genetic differences between pairwise HapMap populations. We hope that, when the researchers carry out gene-based, KEGG pathway-based or GO category-based research, they can take full account of the genetic differences between populations. The HGPGD database (V1.0) is available at http://www.bioapp.org/hgpgd.

Growing evidence from epidemiological studies indicates the association between rheumatoid arthritis (RA) and measles. However, the exact mechanism for this association is still unclear now. We consider that the strong association between both diseases may be caused by shared genetic pathways. We performed a pathway analysis of large-scale RA genome-wide association studies (GWAS) dataset with 5,539 cases and 20,169 controls of European descent. Meanwhile, we evaluated our findings using previously identified RA loci, protein-protein interaction network and previous results from pathway analysis of RA and other autoimmune diseases GWAS. We confirmed four pathways including Cytokine-cytokine receptor interaction, Jak-STAT signaling, T cell receptor signaling and Cell adhesion molecules. Meanwhile, we highlighted for the first time the involvement of Measles and Intestinal immune network for IgA production pathways in RA. Our results may explain the strong association between RA and measles, which may be caused by the shared genetic pathway. We believe that our results will be helpful for future genetic studies in RA pathogenesis and may significantly assist in the development of therapeutic strategies.

Antimicrobial peptides (AMPs) represent a class of natural peptides that form a part of the innate immune system, and this kind of 'nature's antibiotics' is quite promising for solving the problem of increasing antibiotic resistance. In view of this, it is highly desired to develop an effective computational method for accurately predicting novel AMPs because it can provide us with more candidates and useful insights for drug design. In this study, a new method for predicting AMPs was implemented by integrating the sequence alignment method and the feature selection method. It was observed that, the overall jackknife success rate by the new predictor on a newly constructed benchmark dataset was over 80.23%, and the Mathews correlation coefficient is 0.73, indicating a good prediction. Moreover, it is indicated by an in-depth feature analysis that the results are quite consistent with the previously known knowledge that some amino acids are preferential in AMPs and that these amino acids do play an important role for the antimicrobial activity. For the convenience of most experimental scientists who want to use the prediction method without the interest to follow the mathematical details, a user-friendly web-server is provided at http://amp.biosino.org/.