Freeze-drying can replace cold-chains for transport and storage of fecal microbiome samples
Background The transport and storage of samples in temperatures of minus 80 °C is commonly considered as the gold standard for microbiome studies. However, studies conducting sample collection at remote sites without a reliable cold-chain would benefit from a sample preservation method that allows transport and storage at ambient temperature. Methods In this study we compare alpha diversity and 16S microbiome composition of 20 fecal sample replicates from Damaraland mole-rats (Fukomys damarensis) preserved in a minus 80 °C freezer and transported on dry ice to freeze-dried samples that were stored and transported in ambient temperature until DNA extraction. Results We found strong correlations between relative abundances of Amplicon Sequence Variants (ASVs) between preservation treatments of the sample, no differences in alpha diversity measures between the two preservation treatments and minor effects of the preservation treatment on beta diversity measures. Our results show that freeze-drying samples can be a useful method for cost-effective transportation and storage of microbiome samples that yields quantitatively almost indistinguishable results in 16S microbiome analyses as those stored in minus 80 °C.
Bensch et al. (2022) Freeze-drying can replace cold-chains for transport and storage of fecal microbiome samples. PeerJ 10:e13095 https://doi.org/10.7717/peerj.13095
Predicting population: development and validation of a new predictive nomogram for evaluating medication nonadherence risk in a type 2 diabetes
Background Diabetes mellitus is a growing global health challenge and affects patients of all ages. Treatment aims to keep blood glucose levels close to normal and to prevent or delay complications. However, adherence to antidiabetic medicines is often unsatisfactory. Purpose Here, we established and internally validated a medication nonadherence risk nomogram for use in Chinese type 2 diabetes mellitus (T2DM) patients. Methods This cross-sectional study was carried out from July–December 2020 on randomly selected T2DM patients visiting a diabetes clinic and included 753 participants. Adherence was analyzed based on an eight-item Morisky Medication Adherence Scale (MMAS-8). Other data, including patient demographics, treatment, complications, and comorbidities, were also collected on questionnaires. Optimization of feature selection to develop the medication nonadherence risk model was achieved using the least absolute shrinkage and selection operator regression model (LASSO). A prediction model comprising features selected from LASSO model was designed by applying multivariable logistic regression analysis. The decision curve analysis, calibration plot, and C-index were utilized to assess the performance of the model in terms of discrimination, calibration, and clinical usefulness. Bootstrapping validation was applied for internal validation. Results The prediction nomogram comprised several factors including sex, marital status, education level, employment, distance, self-monitoringofbloodglucose, disease duration, and dosing frequency of daily hypoglycemics (pills, insulin, or glucagon-like peptide-1). The model exhibited good calibration and good discrimination (C-index = 0.79, 95% CI [0.75–0.83]). In the validation samples, a high C-index (0.75) was achieved. Results of the decision curve analysis revealed that the nonadherence nomogram could be applied in clinical practice in cases where the intervention is decided at a nonadherence possibility threshold of 12%. Conclusion The number of patients who adhere to anti-diabetes therapy was small. Being single male, having no formal education, employed, far from hospital, long disease duration, and taking antidiabetics twice or thrice daily, had significant negative correlation with medication adherence. Thus, strategies for improving adherence are urgently needed.
QiMuge et al. (2022) Predicting population: development and validation of a new predictive nomogram for evaluating medication nonadherence risk in a type 2 diabetes. PeerJ 10:e13102 https://doi.org/10.7717/peerj.13102
Biochemical analysis of collagens from the bone of lizardfish (Saurida tumbil Bloch, 1795) extracted with different acids
Background Lizardfish (Saurida tumbil Bloch, 1795) bone is a fish by-product generated during industrial surimi processing. This by-product is an important source of collagen production since the use of terrestrial animal-based collagens no longer sought due to concern regarding the transfer of infectious diseases and religious issues. Hence, this study was carried out to determine the biochemical analysis of collagens from the bone of lizardfish extracted with different acids. Methods Lizardfish bone collagens were extracted with various acids (i.e., acetic, lactic and citric acids). All extraction processes were conducted in a chiller room (4 °C). The extracted collagens were biochemically characterized, such as hydroxyproline content, Ultraviolet (UV) absorption, X-ray diffraction (XRD), Fourier transform infrared spectroscopy spectra (FTIR), Differential scanning calorimetry (DSC) and solubility in different pH values and NaCl concentrations. Results The yield of extracted collagens ranged between 1.73% and 2.59%, with the highest (p < 0.05) observed in citric acid-extracted collagen (CaEC). Protein patterns confirmed that all-collagen samples had two identical subunits, α1 and α2, representing type I collagen. The highest whiteness value was found in acetic acid-extracted collagen (AaEC), but there was no significant difference (p ≥ 0.05) compared to lactic acid-extracted collagen (LaEC). UV absorption and XRD analysis reflected the characteristics of the collagen, as reported in the literature. For the FTIR, all acid-extracted collagen samples presented a triple helical structure. The thermal transition temperature (Tmax = 77.92–89.04 °C) was in accordance with collagen extracted from other fish species. All extracted collagens were highly soluble in acidic pH and low concentrations of NaCl (0–20 g/L). In conclusion, collagens extracted from lizardfish bone may be used as alternative sources of collagen in industrial settings, and AaEC would be considered superior in terms of the characteristics evaluated in this study.
Jaziri et al. (2022) Biochemical analysis of collagens from the bone of lizardfish (Saurida tumbil Bloch, 1795) extracted with different acids. PeerJ 10:e13103 https://doi.org/10.7717/peerj.13103
Spring diet and energy intake of tundra swan (Cygnus columbianus) at the Yellow River National Wetland in Baotou, China
The Yellow River National Wetland in Baotou, China is an important resting and energy replenishment place for many migratory birds, such as tundra swan (Cygnus columbianus). The energy supply of food available at stopover sites plays an important role in the life cycle of migratory birds. In order to understand diet composition and energy supply of tundra swans for further protection of them, in this study, fecal of tundra swans (C. columbianus) were collected and fecal microhistological analysis was conducted to analyze the feeding habits and the energy supply. Results showed that: (1) tundra swans (C. columbianus) mainly fed on twelve species of plants from five families, including corn (Zea mays), quinoa (Chenopodium album) and rice (Oryza sativa), this is related to local crops and abundant plants. (2) The energy provided by crops to tundra swans (C. columbianus) was significantly higher than other abundant plants in wetlands (P < 0.05), corn and rice were the most consumed food, and other abundant wetland plants play complementary roles. (3) The daily energy intake of tundra swans (C. columbianus) was much higher than their daily energy consumption, the daily net energy intake of tundra swans (C. columbianus) was 855.51 ± 182.88 kJ (mean ± standard deviations). This suggested that the wetland provides energy for continue migrating to the tundra swan (C. columbianus). For further protection of tundra swans (C. columbianus) and other migratory birds, the Baotou Yellow River National Wetland environment and the surrounding farmland habitat should be protected.
Liu et al. (2022) Spring diet and energy intake of tundra swan (Cygnus columbianus) at the Yellow River National Wetland in Baotou, China. PeerJ 10:e13113 https://doi.org/10.7717/peerj.13113
Geomorphically controlled coral distribution in degraded shallow reefs of the Western Caribbean
The development of coral reefs results from the interaction between ecological and geological processes in space and time. Their difference in scale, however, makes it difficult to detect the impact of ecological changes on geological reef development. The decline of coral cover over the last 50 years, for example, has dramatically impaired the function of ecological processes on reefs. Yet given the limited-resolution of their Holocene record, it is uncertain how this will impact accretion and structural integrity over longer timescales. In addition, reports of this ecological decline have focused on intrinsic parameters such as coral cover and colony size at the expense of extrinsic ones such as geomorphic and environmental variables. Despite these problems, several attempts have been made to predict the long-term accretion status of reefs based entirely on the contemporary health status of benthic communities. Here we explore how this ecological decline is represented within the reef geomorphic structure, which represents the long-term expression of reef development. Using a detailed geomorphic zonation scheme, we analyze the distribution and biodiversity of reef-building corals in fringing-reef systems of the Mesoamerican Reef tract. We find a depth-related pattern in community structure which shows that the relative species distribution between geomorphic zones is statistically different. Despite these differences, contemporary coral assemblages in all zones are dominated by the same group of pioneer generalist species. These findings imply that first, coral species distribution is still controlled by extrinsic processes that generate the geomorphic zonation; second, that coral biodiversity still reflects species zonation patterns reported by early studies; and third that dominance of pioneer species implies that modern coral assemblages are in a prolonged post-disturbance adjustment stage. In conclusion, any accurate assessment of the future viability of reefs requires a consideration of the geomorphic context or risks miscalculating the impact of ecological changes on long-term reef development.
Medina-Valmaseda et al. (2022) Geomorphically controlled coral distribution in degraded shallow reefs of the Western Caribbean. PeerJ 10:e12590 https://doi.org/10.7717/peerj.12590
Identification of key microorganisms in facultative stabilization ponds from dairy industries, using metagenomics
Wastewater stabilization ponds are a natural form of wastewater treatment. Their low operation and maintenance costs have made them popular, especially in developing countries. In these systems, effluents are retained for long periods of time, allowing the microbial communities present in the ponds to degrade the organic matter present, using both aerobic and anaerobic processes. Even though these systems are widespread in low income countries, there are no studies about the microorganisms present in them and how they operate. In this study, we analised the microbial communities of two serial full-scale stabilization ponds systems using whole genome shotgun sequencing. First, a taxonomic profiling of the reads was performed, to estimate the microbial diversity. Then, the reads of each system were assembled and binned, allowing the reconstruction of 110 microbial genomes. A functional analysis of the genomes allowed us to find how the main metabolic pathways are carried out, and we propose several organisms that would be key to this kind of environment, since they play an important role in these metabolic pathways. This study represents the first genome-centred approach to understand the metabolic processes in facultative ponds. A better understanding of these microbial communities and how they stabilize the effluents of dairy industries is necessary to improve them and to minimize the environmental impact of dairy industries wastewater.
Irazoqui et al. (2022) Identification of key microorganisms in facultative stabilization ponds from dairy industries, using metagenomics. PeerJ 10:e12772 https://doi.org/10.7717/peerj.12772
PhosVarDeep: deep-learning based prediction of phospho-variants using sequence information
Human DNA sequencing has revealed numerous single nucleotide variants associated with complex diseases. Researchers have shown that these variants have potential effects on protein function, one of which is to disrupt protein phosphorylation. Based on conventional machine learning algorithms, several computational methods for predicting phospho-variants have been developed, but their performance still leaves considerable room for improvement. In recent years, deep learning has been successfully applied in biological sequence analysis with its efficient sequence pattern learning ability, which provides a powerful tool for improving phospho-variant prediction based on protein sequence information. In the study, we present PhosVarDeep, a novel unified deep-learning framework for phospho-variant prediction. PhosVarDeep takes reference and variant sequences as inputs and adopts a Siamese-like CNN architecture containing two identical subnetworks and a prediction module. In each subnetwork, general phosphorylation sequence features are extracted by a pre-trained sequence feature encoding network and then fed into a CNN module for capturing variant-aware phosphorylation sequence features. After that, a prediction module is introduced to integrate the outputs of the two subnetworks and generate the prediction results of phospho-variants. Comprehensive experimental results on phospho-variant data demonstrates that our method significantly improves the prediction performance of phospho-variants and compares favorably with existing conventional machine learning methods.
Liu et al. (2022) PhosVarDeep: deep-learning based prediction of phospho-variants using sequence information. PeerJ 10:e12847 https://doi.org/10.7717/peerj.12847
Textural quality, growth parameters and oxidative responses in Nile tilapia (Oreochromis niloticus) fed faba bean water extract diet
Texture is one of the key quality attributes used in the fresh and processed fish industry to assess product quality and consumer acceptability. To improve the textural quality of tilapia, we formulated the expanded pellet diet (EPD) and pellet diet (PD), both containing faba bean (Vicia faba, FB) water extract, a previously reported potential aquafeed additive to increase flesh texture. The common diet was used as a control. After Nile tilapia (Oreochromis niloticus) were fed three kinds of experimental diet for 120 days, muscle textural quality, growth parameters, oxidative response and immune parameters were analyzed. The results showed that there was no significant difference in the growth parameters between the three groups (P > 0.05). The highest measure of textural quality (hardness and chewiness) was found for the PD group, followed by the EPD and the control (P < 0.05). Less oxidative damage to the hepatopancreas and intestine was found in the EPD compared with the PD group, as demonstrated by the decreased levels of reactive oxygen species and increased levels of nicotinamide adenine dinucleotide and intestinal digestive enzyme activity (amylase and lipase). Taken together, this study highlights the potential usefulness in commercial settings of FB water extract for improving the textural quality of tilapia, and EPD containing faba bean water extract could be more advanced substitute for faba bean in tilapia culture in term of both effectiveness in textural quality improvement and health status enhancement compared with PD.
Li et al. (2022) Textural quality, growth parameters and oxidative responses in Nile tilapia (Oreochromis niloticus) fed faba bean water extract diet. PeerJ 10:e13048 https://doi.org/10.7717/peerj.13048
Full vaccination coverage and associated factors among children aged 12 to 23 months in remote rural area of Demba Gofa District, Southern Ethiopia
Background Full vaccination refers to the administration of vaccines/antigens recommended for children in the first year of life. However, little is known about full vaccination in remote, rural Ethiopia. This study aimed to measure full vaccination coverage and associated factors among children aged 12 to 23 months in Demba Gofa District, Southern Ethiopia. Methods A community-based cross-sectional study was conducted in April and May 2019 using a multistage sampling technique to select 677 mothers with children 12–23 months of age. Data was collected using a pre-tested structured questionnaire, and data were edited, coded, entered, and cleaned using Epi Info v3.1 and analyzed using SPSS v20. Bivariate and multivariable logistic regression was used to understand associations between dependent and independent variables. Results Three-hundred and nine children (47.0%) were fully vaccinated, 274 (41.7%) were partially vaccinated, and 74 (11.3%) were not vaccinated at all. Children were more likely to be vaccinated if decisions were made jointly with husbands (AOR = 1.88, 95% CI [1.06–3.34]), were made by mothers (AOR = 4.03, 95% CI [1.66–9.78]), followed postnatal care (AOR = 5.02, 95% CI [2.28–11.05]), if the child’s age for completing vaccination was known (AOR = 2.54, 95% CI [1.04–6.23]), and if vaccinations did not make the child sick (AOR = 0.32, 95% CI [0.16–0.64]). Conclusion Full vaccination coverage was less than average in the study district and far below the governmental target (90%) necessary for sustained control of vaccine-preventable diseases. Interventions targeted towards maternal healthcare decision-making, postnatal care, knowledge on vaccination timing, and importance should be prioritized to improve full vaccination coverage. A continuous supply of vaccination cards needs to be ensured to improve vaccination conditions.
Darebo et al. (2022) Full vaccination coverage and associated factors among children aged 12 to 23 months in remote rural area of Demba Gofa District, Southern Ethiopia. PeerJ 10:e13081 https://doi.org/10.7717/peerj.13081
3,4-dihydroxyphenylethyl alcohol glycoside reduces acetaminophen-induced acute liver failure in mice by inhibiting hepatocyte ferroptosis and pyroptosis
APAP is one of the most commonly used antipyretic and pain medications, but excessive use can cause liver toxicity and damage. 3,4-dihydroxyphenylethyl alcohol glycoside (DAG) is a component isolated from Sargentodoxa cuneata known to have anti-apoptotic, anti-oxidation and anti-inflammatory effects. However, the effects of DAG on acute liver failure (ALF) are largely unknown. The purpose of this study is to study the protective effects and mechanism of DAG on APAP-induced ALF in mice. We established an ALF model in adult male pathogen-free C57BL/6 mice treated with APAP (300 mg/kg) by intraperitoneal injection and resolved by 24 h. Hematoxylin and eosin (HE) staining was used to evaluate the pathological changes in mouse liver tissue. The infiltration of neutrophils in liver tissue and reactive oxygen species (ROS) in AML12 cells were analyzed by flow cytometry. The levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), glutathione (GSH), malondialdehyde (MDA), catalase (CAT), and superoxide dismutase (SOD) were analyzed using relevant kits. Our results show that DAG reduced APAP-induced serum ALT and AST levels, histopathological changes, liver neutrophil infiltration and proinflammatory cytokines production, also attenuated the accumulation of MDA and the exhaustion of GSH, CAT and SOD. In vitro experiment indicated that DAG dose-dependently inhibited APAP-induced the levels of pro-inflammatory factors (IL-1β and IL18), and reactive oxygen species (ROS) and preventing GSH depletion in mouse AML12 hepatocytes. More interestingly, DAG inhibited the expression of ERK, HO-1, NLRP3, Caspase1 (p20) and Gasdermin-D and upregulated the expression of GPX4 in liver tissues and AML12hepatocytes. Therefore, our results indicate that DAG may act as a potential agent to treat ALF induced by APAP by inhibiting hepatocyte ferroptosis and pyroptosis.
Liu et al. (2022) 3,4-dihydroxyphenylethyl alcohol glycoside reduces acetaminophen-induced acute liver failure in mice by inhibiting hepatocyte ferroptosis and pyroptosis. PeerJ 10:e13082 https://doi.org/10.7717/peerj.13082