The relationship of low-density lipoprotein cholesterol and all-cause or cardiovascular mortality in patients with type 2 diabetes: a retrospective study
Background The optimal levels of low-density lipoprotein cholesterol (LDL-C) in patients with type 2 diabetes (T2D) are not currently clear. In this study, we determined the relationship between various mean LDL-C and all-cause or cardiovascular mortality risks in patients with T2D, stratifying by albumin level, age, sex, and antilipid medication use. We also evaluated the association of LDL-C standard deviation (LDL-C-SD) and all-cause and cardiovascular mortality by type of antilipid medication use. Methods A total of 46,675 T2D patients with a prescription for antidiabetic agents >6 months from outpatient visits (2003–2018) were linked to Taiwan’s National Death Registry to identify all-cause and cardiovascular mortality. The Poisson assumption was used to estimate mortality rates, and the Cox proportional hazard regression model was used to assess the relative hazards of respective mortality in relation to mean LDL-C in patient cohorts by albumin level, age, sex, and antilipid use adjusting for medications, comorbidities, and laboratory results. We also determined the overall, and anti-lipid-specific mortality rates and relative hazards of all-cause and cardiovascular mortality associated with LDL-C-SD using the Poisson assumption and Cox proportional hazard regression model, respectively. Results All-cause and cardiovascular mortality rates were the lowest in T2D patients with a mean LDL-C > 90-103.59 mg/dL in the normal albumin group (≥ 3.5 g/dL). Compared to T2D patients with a mean LDL-C > 90–103.59 mg/dL, those with a mean LDL-C ≤ 77 mg/dL had an elevated risk of all-cause mortality in both the normal and lower albumin groups. T2D patients with a mean LDL-C ≤ 90 and > 103.59–119 mg/dL had relatively higher risk of cardiovascular mortality in the normal albumin group, but in the lower albumin group (<3.5 g/dL), any level of mean LDL-C ≤ 119 mg/dL was not significantly associated with cardiovascular mortality. Increased risks of all-cause and cardiovascular mortality were observed in patients with a mean LDL-C ≤ 77 mg/dL in both sexes and in all age groups except in those aged <50 years, a lower mean LDL-C was not associated with cardiovascular mortality. Similarly, patients with an LDL-C-SD <10th and > 90th percentiles were associated with significant risks of all-cause and cardiovascular mortality. In statin users, but not fibrate users, lower and higher levels of mean LDL-C and LDL-C-SD were both associated with elevated risks of all-cause and cardiovascular mortality. Conclusions The optimal level of LDL-C was found to be >90–103.59 mg/dL in T2D patients. Lower and higher levels of mean LDL-C and LDL-C-SD were associated with all-cause and cardiovascular mortality, revealing U-shaped associations. Further studies are necessary to validate the relationship between optimal LDL-C levels and all-cause and cardiovascular mortality in patients with diabetes.
Chang et al. (2023) The relationship of low-density lipoprotein cholesterol and all-cause or cardiovascular mortality in patients with type 2 diabetes: a retrospective study. PeerJ 11:e14609 https://doi.org/10.7717/peerj.14609
Be positive: customized reference databases and new, local barcodes balance false taxonomic assignments in metabarcoding studies
Background In metabarcoding analyses, the taxonomic assignment is crucial to place sequencing data in biological and ecological contexts. This fundamental step depends on a reference database, which should have a good taxonomic coverage to avoid unassigned sequences. However, this goal is rarely achieved in many geographic regions and for several taxonomic groups. On the other hand, more is not necessarily better, as sequences in reference databases belonging to taxonomic groups out of the studied region/environment context might lead to false assignments. Methods We investigated the effect of using several subsets of a cytochrome c oxidase subunit I (COI) reference database on taxonomic assignment. Published metabarcoding sequences from the Mediterranean Sea were assigned to taxa using COInr, which is a comprehensive, non-redundant and recent database of COI sequences obtained both from BOLD and NCBI, and two of its subsets: (i) all sequences except insects (COInr-WO-Insecta), which represent the overwhelming majority of COInr database, but are irrelevant for marine samples, and (ii) all sequences from taxonomic families present in the Mediterranean Sea (COInr-Med). Four different algorithms for taxonomic assignment were employed in parallel to evaluate differences in their output and data consistency. Results The reduction of the database to more specific custom subsets increased the number of unassigned sequences. Nevertheless, since most of them were incorrectly assigned by the less specific databases, this is a positive outcome. Moreover, the taxonomic resolution (the lowest taxonomic level to which a sequence is attributed) of several sequences tended to increase when using customized databases. These findings clearly indicated the need for customized databases adapted to each study. However, the very high proportion of unassigned sequences points to the need to enrich the local database with new barcodes specifically obtained from the studied region and/or taxonomic group. Including novel local barcodes to the COI database proved to be very profitable: by adding only 116 new barcodes sequenced in our laboratory, thus increasing the reference database by only 0.04%, we were able to improve the resolution for ca. 0.6–1% of the Amplicon Sequence Variants (ASVs).
Mugnai et al. (2023) Be positive: customized reference databases and new, local barcodes balance false taxonomic assignments in metabarcoding studies. PeerJ 11:e14616 https://doi.org/10.7717/peerj.14616
Different types of plantar vibration affect gait characteristics differently while walking on different inclines
Background Plantar vibration has been widely used to strengthen the sensation of the somatosensory system, further enhancing balance during walking on a level surface in patients with stroke. However, previous studies with plantar vibration only involved the level surface, which neglected the importance of inclined/declined walking in daily life. Thus, combining the plantar vibration and inclined/declined walking might answer a critical research question: whether different types of plantar vibration had different effects on gait characteristics during walking on different inclines. Methods Eighteen healthy young adults were recruited. Fifteen walking conditions were assigned randomly to these healthy adults (no, sub-, and supra-threshold plantar vibration × five different inclines: +15%, +8%, 0%, −8%, −15% grade). A motion capture system with eight cameras captured 12 retro-reflective markers and measured the stride time, stride length, step width, and respective variabilities. Results A significant interaction between vibration and inclination was observed in the stride time (p < 0.0001) and step width (p = 0.015). Post hoc comparisons found that supra-threshold vibration significantly decreased the stride time (−8%: p < 0.001; −15%: p < 0.001) while the sub-threshold vibration significantly increased the step width (−8%: p = 0.036) in comparison with no plantar vibration. Conclusions When walking downhill, any perceivable (supra-threshold) vibration on the plantar area decreased the stride time. Also, the increase in step width was observed by non-perceivable (sub-threshold) plantar vibration while walking uphill. These observations were crucial as follows: (1) applying sub-threshold plantar vibrations during uphill walking could increase the base of support, and (2) for those who may need challenges in locomotor training, applying supra-threshold vibration during downhill walking could reach this specific training goal.
Xie et al. (2023) Different types of plantar vibration affect gait characteristics differently while walking on different inclines. PeerJ 11:e14619 https://doi.org/10.7717/peerj.14619
Dominance of Bacillus species in the wheat (Triticum aestivum L.) rhizosphere and their plant growth promoting potential under salt stress conditions
Wheat (Triticum aestivum L.) is a major source of calorific intake in its various forms and is considered one of the most important staple foods. Improved wheat productivity can contribute substantially to addressing food security in the coming decades. Soil salinity is the most serious limiting factor in crop production and fertilizer use efficiency. In this study, 11 bacteria were isolated from wheat rhizosphere and examined for salt tolerance ability. WGT1, WGT2, WGT3, WGT6, WGT8, and WGT11 were able to tolerate NaCl salinity up to 4%. Bacterial isolates were characterized in vitro for plant growth-promoting properties including indole-3-acetic acid (IAA) production, phosphate solubilization, nitrogen fixation, zinc solubilization, biofilm formation, and cellulase-pectinase production. Six isolates, WGT1, WGT3, WGT4, WGT6, WGT8, and WGT9 showed IAA production ability ranging from 0.7–6 µg m/L. WGT8 displayed the highest IAA production. Five isolates, WGT1, WGT2, WGT5, WGT10, and WGT11, demonstrated phosphate solubilization ranging from 1.4–12.3 µg m/L. WGT2 showed the highest phosphate solubilization. Nitrogen fixation was shown by only two isolates, WGT1 and WGT8. Zinc solubilization was shown by WGT1 and WGT11 on minimal media. All isolates showed biofilm formation ability, where WGT4 exhibited maximum potential. Cellulase production ability was noticed in WGT1, WGT2, WGT4, and WGT5, while pectinase production was observed in WGT2 and WGT3. Phylogenetic identification of potential bacteria isolates confirmed their close relationship with various species of the genus Bacillus. WGT1, WGT2, and WGT3 showed the highest similarity with B. cereus, WGT6 with B. tianshenii, WGT8 with B. subtilis, and WGT11 with B. thuringiensis. Biofertilizer characteristics of salt-tolerant potential rhizospheric bacteria were evaluated by inoculating wheat plants under controlled conditions and field experiments. B. cereus WGT1 and B. thuringiensis WGT11 displayed the maximum potential to increase plant growth parameters and enhance grain yield by 37% and 31%, respectively. Potential bacteria of this study can tolerate salt stress, have the ability to produce plant growth promoting substances under salt stress and contribute significantly to enhance wheat grain yield. These bacterial isolates have the potential to be used as biofertilizers for improved wheat production under salinity conditions and contribute to the sustainable agriculture.
Zahra et al. (2023) Dominance of Bacillus species in the wheat (Triticum aestivum L.) rhizosphere and their plant growth promoting potential under salt stress conditions. PeerJ 11:e14621 https://doi.org/10.7717/peerj.14621
Construction of an anthropometric discriminant model for identification of elite swimmers: an adaptive lasso approach
Background Anthropometric characteristics are important factors that affect swimming performance. The aim of this study is to build a discriminant model using anthropometric factors to identify elite short-to-medium-distance freestyle swimmers through an adaptive Lasso approach. Methods The study recruited 254 swimmers (145 males and 109 females) who were divided them into elite (aged 17.9 ± 2.2 years, FINA points 793.8 ± 73.8) and non-elite (aged 17.1 ± 1.3 years, FINA points 560.6 ± 78.7) groups. Data for 73 variables were obtained, including basic information, anthropometric and derivative indicators. After filtering out highly correlated variables, 24 candidate variables were retained to be used in adaptive Lasso to select variables for prediction of elite swimmers. Deviance and area under the curve (AUC) were applied to assess the goodness of fit and prediction accuracy of the model, respectively. Results The adaptive Lasso selected 12 variables using the whole sample, with an AUC being 0.926 (95% CI [0.895–0.956]; P = 2.42 × 10−29). In stratified analysis by gender, nine variables were selected for male swimmers with an AUC of 0.921 (95% CI [0.880–0.963]; P = 8.82 × 10−17), and eight variables were for female swimmers with an AUC of 0.941 (95% CI [0.898–0.984]; P = 7.67 × 10−15). Conclusion The adaptive Lasso showed satisfactory performance in selecting anthropometric characteristics to identify elite swimmers. Additional studies with longitudinal data or data from other ethnicities are needed to validate our findings.
Pan et al. (2023) Construction of an anthropometric discriminant model for identification of elite swimmers: an adaptive lasso approach. PeerJ 11:e14635 https://doi.org/10.7717/peerj.14635
Integrated omics analysis reveals the immunologic characteristics of cystic Peyer’s patches in the cecum of Bactrian camels
Bactrian camels have specific mucosa-associated lymphoid tissue (MALT) throughout the large intestine, with species-unique cystic Peyer’s patches (PPS) as the main type of tissue. However, detailed information about the molecular characteristics of PPS remains unclear. This study applied a transcriptomic analysis, untargeted metabolomics, and 16S rDNA sequencing to compare the significant differences between PPS and the adjacent normal intestine tissues (NPPS) during the healthy stage of three young Bactrian camels. The results showed that samples from PPS could be easily differentiated from the NPPS samples based on gene expression profile, metabolites, and microbial composition, separately indicated using dimension reduction methods. A total of 7,568 up-regulated and 1,266 down-regulated differentially expressed genes (DEGs) were detected, and an enrichment analysis found 994 DEGs that participated in immune-related functions, and a co-occurance network analysis identified nine hub genes (BTK, P2RX7, Pax5, DSG1, PTPN2, DOCK11, TBX21, IL10, and HLA-DOB) during multiple immunologic processes. Further, PPS and NPPS both had a similar pattern of most compounds among all profiles of metabolites, and only 113 differentially expressed metabolites (DEMs) were identified, with 101 of these being down-regulated. Deoxycholic acid (DCA; VIP = 37.96, log2FC = −2.97, P = 0), cholic acid (CA; VIP = 13.10, log2FC = −2.10, P = 0.01), and lithocholic acid (LCA; VIP = 12.94, log2FC = −1.63, P = 0.01) were the highest contributors to the significant dissimilarities between groups. PPS had significantly lower species richness (Chao1), while Firmicutes (35.92% ± 19.39%), Bacteroidetes (31.73% ± 6.24%), and Proteobacteria (13.96% ± 16.21%) were the main phyla across all samples. The LEfSe analysis showed that Lysinibacillus, Rikenellaceae_RC9_gut_group, Candidatus_Stoquefichus, Mailhella, Alistipes, and Ruminococcaceae_UCG_005 were biomarkers of the NPPS group, while Escherichia_Shigella, Synergistes, Pyramidobacter, Odoribacter, Methanobrevibacter, Cloacibacillus, Fusobacterium, and Parabacteroides were significantly higher in the PPS group. In the Procrustes analysis, the transcriptome changes between groups showed no significant correlations with metabolites or microbial communities, whereas the alteration of metabolites significantly correlated with the alteration of the microbial community. In the co-occurrence network, seven DEMs (M403T65-neg, M329T119-neg, M309T38-neg, M277T42-2-neg, M473T27-neg, M747T38-1-pos, and M482t187-pos) and 14 genera (e.g., Akkermansia, Candidatus-Stoquefichus, Caproiciproducens, and Erysipelatoclostridium) clustered much more tightly, suggesting dense interactions. The results of this study provide new insights into the understanding of the immune microenvironment of the cystic PPS in the cecum of Bactrian camels.
Wang et al. (2023) Integrated omics analysis reveals the immunologic characteristics of cystic Peyer’s patches in the cecum of Bactrian camels. PeerJ 11:e14647 https://doi.org/10.7717/peerj.14647
A more reliable species richness estimator based on the Gamma–Poisson model
Background Accurately estimating the true richness of a target community is still a statistical challenge, particularly in highly diverse communities. Due to sampling limitations or limited resources, undetected species are present in many surveys and observed richness is an underestimate of true richness. In the literature, methods for estimating the undetected richness of a sample are generally divided into two categories: parametric and nonparametric estimators. Imposing no assumptions on species detection rates, nonparametric methods demonstrate robust statistical performance and are widely used in ecological studies. However, nonparametric estimators may seriously underestimate richness when species composition has a high degree of heterogeneity. Parametric approaches, which reduce the number of parameters by assuming that species-specific detection probabilities follow a given statistical distribution, use traditional statistical inference to calculate species richness estimates. When species detection rates meet the model assumption, the parametric approach could supply a nearly unbiased estimator. However, the infeasibility and inefficiency of solving maximum likelihood functions limit the application of parametric methods in ecological studies when the model assumption is violated, or the collected data is sparse. Method To overcome these estimating challenges associated with parametric methods, an estimator employing the moment estimation method instead of the maximum likelihood estimation method is proposed to estimate parameters based on a Gamma-Poisson mixture model. Drawing on the concept of the Good-Turing frequency formula, the proposed estimator only uses the number of singletons, doubletons, and tripletons in a sample for undetected richness estimation. Results The statistical behavior of the new estimator was evaluated by using real and simulated data sets from various species abundance models. Simulation results indicated that the new estimator reduces the bias presented in traditional nonparametric estimators, presents more robust statistical behavior compared to other parametric estimators, and provides confidence intervals with better coverage among the discussed estimators, especially in assemblages with high species composition heterogeneity.
Chiu (2023) A more reliable species richness estimator based on the Gamma–Poisson model. PeerJ 11:e14540 https://doi.org/10.7717/peerj.14540
The biomarkers discovery of hyperuricemia and gout: proteomics and metabolomics
Background Hyperuricemia and gout are a group of disorders of purine metabolism. In recent years, the incidence of hyperuricemia and gout has been increasing, which is a severe threat to people’s health. Several studies on hyperuricemia and gout in proteomics and metabolomics have been conducted recently. Some literature has identified biomarkers that distinguish asymptomatic hyperuricemia from acute gout or remission of gout. We summarize the physiological processes in which these biomarkers may be involved and their role in disease progression. Methodology We used professional databases including PubMed, Web of Science to conduct the literature review. This review addresses the current landscape of hyperuricemia and gout biomarkers with a focus on proteomics and metabolomics. Results Proteomic methods are used to identify differentially expressed proteins to find specific biomarkers. These findings may be suggestive for the diagnosis and treatment of hyperuricemia and gout to explore the disease pathogenesis. The identified biomarkers may be mediators of the link between hyperuricemia, gout and kidney disease, metabolic syndrome, diabetes and hypertriglyceridemia. Metabolomics reveals the main influential pathways through small molecule metabolites, such as amino acid metabolism, lipid metabolism, or other characteristic metabolic pathways. These studies have contributed to the discovery of Chinese medicine. Some traditional Chinese medicine compounds can improve the metabolic disorders of the disease. Conclusions We suggest some possible relationships of potential biomarkers with inflammatory episodes, complement activation, and metabolic pathways. These biomarkers are able to distinguish between different stages of disease development. However, there are relatively few proteomic as well as metabolomic studies on hyperuricemia and gout, and some experiments are only primary screening tests, which need further in-depth study.
Wu et al. (2023) The biomarkers discovery of hyperuricemia and gout: proteomics and metabolomics. PeerJ 11:e14554 https://doi.org/10.7717/peerj.14554
On the origin of mitochondria: a multilayer network approach
Backgound The endosymbiotic theory is widely accepted to explain the origin of mitochondria from a bacterial ancestor. While ample evidence supports the intimate connection of Alphaproteobacteria to the mitochondrial ancestor, pinpointing its closest relative within sampled Alphaproteobacteria is still an open evolutionary debate. Many different phylogenetic methods and approaches have been used to answer this challenging question, further compounded by the heterogeneity of sampled taxa, varying evolutionary rates of mitochondrial proteins, and the inherent biases in each method, all factors that can produce phylogenetic artifacts. By harnessing the simplicity and interpretability of protein similarity networks, herein we re-evaluated the origin of mitochondria within an enhanced multilayer framework, which is an extension and improvement of a previously developed method. Methods We used a dataset of eight proteins found in mitochondria (N = 6 organisms) and bacteria (N = 80 organisms). The sequences were aligned and resulting identity matrices were combined to generate an eight-layer multiplex network. Each layer corresponded to a protein network, where nodes represented organisms and edges were placed following mutual sequence identity. The Multi-Newman-Girvan algorithm was applied to evaluate community structure, and bifurcation events linked to network partition allowed to trace patterns of divergence between studied taxa. Results In our network-based analysis, we first examined the topology of the 8-layer multiplex when mitochondrial sequences disconnected from the main alphaproteobacterial cluster. The resulting topology lent firm support toward an Alphaproteobacteria-sister placement for mitochondria, reinforcing the hypothesis that mitochondria diverged from the common ancestor of all Alphaproteobacteria. Additionally, we observed that the divergence of Rickettsiales was an early event in the evolutionary history of alphaproteobacterial clades. Conclusion By leveraging complex networks methods to the challenging question of circumscribing mitochondrial origin, we suggest that the entire Alphaproteobacteria clade is the closest relative to mitochondria (Alphaproteobacterial-sister hypothesis), echoing recent findings based on different datasets and methodologies.
Borges et al. (2023) On the origin of mitochondria: a multilayer network approach. PeerJ 11:e14571 https://doi.org/10.7717/peerj.14571
Stem transcriptome screen for selection in wild and cultivated pitahaya (Selenicereus undatus): an epiphytic cactus with edible fruit
Dragon fruit, pitahaya or pitaya are common names for the species in the Hylocereus group of Selenicereus that produce edible fruit. These Neotropical epiphytic cacti are considered promising underutilized crops and are currently cultivated around the world. The most important species, S. undatus, has been managed in the Maya domain for centuries and is the focus of this article. Transcriptome profiles from stems of wild and cultivated plants of this species were compared. We hypothesized that differences in transcriptomic signatures could be associated with genes related to drought stress. De novo transcriptome assembly and the analysis of differentially expressed genes (DEGs) allowed us to identify a total of 9,203 DEGs in the Hunucmá cultivar relative of wild Mozomboa plants. Of these, 4,883 represent up-regulated genes and 4,320, down-regulated genes. Additionally, 6,568 DEGs were identified from a comparison between the Umán cultivar and wild plants, revealing 3,286 up-regulated and 3,282 down-regulated genes. Approximately half of the DEGs are shared by the two cultivated plants. Differences between the two cultivars that were collected in the same region could be the result of differences in management. Metabolism was the most representative functional category in both cultivars. The up-regulated genes of both cultivars formed a network related to the hormone-mediated signaling pathway that includes cellular responses to auxin stimulus and to hormone stimulus. These cellular reactions have been documented in several cultivated plants in which drought-tolerant cultivars modify auxin transport and ethylene signaling, resulting in a better redistribution of assimilates.
Oltehua-López et al. (2023) Stem transcriptome screen for selection in wild and cultivated pitahaya (Selenicereus undatus): an epiphytic cactus with edible fruit. PeerJ 11:e14581 https://doi.org/10.7717/peerj.14581