Phenology and predictors of spring emergence for the Timber Rattlesnake (Crotalus horridus)
Many temperate reptiles survive winter by using subterranean refugia until external conditions become suitable for activity. Determining when to emerge from refugia relies on the ability to interpret when above-ground environmental conditions are survivable. If temperate reptiles rely on specific environmental cues such as temperature to initiate emergence, we should expect emergence phenologies to be predictable using local climatic data. However, specific predictors of emergence for many temperate reptiles, including the Timber Rattlesnake (Crotalus horridus), remain unclear, limiting our understanding of their overwintering phenology and restricting effective conservation and management. Our objectives were to identify environmental cues of spring emergence for C. horridus in Illinois to determine the species’ emergence phenology, and to examine the applicability of identified cues in predicting emergence phenology across the species’ range. We used wildlife cameras and weather station-derived environmental data to observe and predict the daily surface presence of C. horridus throughout the late winter and early spring at communal refugia in west-central and northern Illinois. The most parsimonious model for predicting surface presence included the additive effects of maximum daily temperature, accumulated degree days, and latitude. With a notable exception in the southeastern U.S., the model accurately predicted the average emergence day for eight other populations range wide, emphasizing the importance of temperature in influencing the phenological plasticity observed across the species’ range. The apparent broad applicability of the model to other populations suggests it can be a valuable tool in predicting spring emergence phenology. Our results provide a foundation for further ecological enquiries and improved management and conservation strategies.
Jesper et al. (2023) Phenology and predictors of spring emergence for the Timber Rattlesnake (Crotalus horridus). PeerJ 11:e16044 https://doi.org/10.7717/peerj.16044
Comparative analysis of codon usage patterns and phylogenetic implications of five mitochondrial genomes of the genus Japanagallia Ishihara, 1955 (Hemiptera, Cicadellidae, Megophthalminae)
Japanagallia is a genus of Cicadomorpha in the family of leafhoppers that are plant piercing-sucking insects, and it is difficult to distinguish by morphological characteristics. So far, only one complete mitochondrial genome data has been reported for the genus Japanagallia. Therefore, in order to better understand this group, we assembled and annotated the complete mitochondrial genomes of five Japanagallia species, and analyzed their codon usage patterns. Nucleotide composition analysis showed that AT content was higher than GC content, and the protein-coding sequences preferred to end with A/T at the third codon position. Relative synonymous codon usage analysis revealed most over-represented codon ends with A or T. Parity plot analysis revealed the codon usage bias of mitochondrial genes was influenced by both natural selection and mutation pressure. In the neutrality plot, the slopes of regression lines were < 0.5, suggesting that natural selection was playing a major role while mutation pressure was of minor importance. The effective number of codons showed that the codon usage bias between genes and genomes was low. Correspondence analysis revealed that the codon usage pattern differed among 13 protein-coding genes. Phylogenetic analyses based on three datasets using two methods (maximum likelihood and Bayesian inference), restored the Megophthalminae monophyly with high support values (bootstrap support values (BS) = 100, Bayesian posterior probability (PP) = 1). In the obtained topology, the seven Japanagallia species were clustered into a monophyletic group and formed a sister group with Durgade. In conclusion, our study can provide a reference for the future research on organism evolution, identification and phylogeny relationships of Japanagallia species.
Li et al. (2023) Comparative analysis of codon usage patterns and phylogenetic implications of five mitochondrial genomes of the genus Japanagallia Ishihara, 1955 (Hemiptera, Cicadellidae, Megophthalminae). PeerJ 11:e16058 https://doi.org/10.7717/peerj.16058
Berberine protects hepatocyte from hypoxia/reoxygenation-induced injury through inhibiting circDNTTIP2
Background During hepatic ischemia-reperfusion injury, the excessive release of inflammatory cytokines can activate the intracellular signal transduction cascade to induce hepatocyte injury. Apoptosis is an important way of cell death after I/R injury. Berberine, a common quaternary ammonium alkaloid, has anti-inflammatory, anti-oxidative stress, and anti-apoptotic effects. An increasing number of studies have revealed the importance of non-coding RNAs, including microRNA, long non-coding RNAs and circular RNAs (circRNAs), as regulators of the effects of berberine. Purpose In this study, we investigated the mechanism of berberine against liver ischemia-reperfusion injury in vitro. Study Design and Methods In this study, hypoxia-reoxygenation (H/R)-treated L02 cells were pretreated with berberine to study the role and mechanism of berberine in resisting hepatic ischemia-reperfusion injury. Results The results show that berberine pre-treatment increased the cell viability of H/R-challenged cells, reduced H/R-induced apoptosis and ROS production, reversed H/R-increased on IL-6, IL-1β, TNF-α, and H/R-decreased IL-10 expression. Mechanically, berberine protect hepatocyte from H/R injury, at least partially, through circDNTTIP2. In addition, circDNTTIP2 can bind to the TATA box of caspase3 promoter, thereby promoting caspase 3-related cell apoptosis and the release of inflammatory cytokines. Conclusion This study found that berberine has a protective effect on H/R-induced hepatocyte damage by inhibiting a novel circRNA, circDNTTIP2. This study provides potential treatment strategies and treatment targets for liver ischemia-reperfusion injury.
Zhu et al. (2023) Berberine protects hepatocyte from hypoxia/reoxygenation-induced injury through inhibiting circDNTTIP2. PeerJ 11:e16080 https://doi.org/10.7717/peerj.16080
Habitat suitability of four threatened Himalayan species: Asiatic black bear, common leopard, musk deer, and snow leopard
Background Biodiversity conservation is becoming challenging day by day. For this, it is essential to understand the distribution, habitat, and impact of anthropogenic activities on animals at risk. We assessed the suitable habitats and anthropogenic impacts on Asiatic black bears, common leopards, musk deer, and snow leopards in and outside the protected areas of Gandaki Province, Nepal. Methods We collected the presence locations of Asiatic black bears, common leopards, musk deer, and snow leopards based on scats and other signs. We employed the Maximum Entropy (MaxEnt) tool to identify suitable habitats of our studied species and their anthropogenic impacts on them. Results The total suitable habitat of the common leopard was found to be 6,052 km2, followed by the Asiatic black bear (5,819 km2), snow leopard (4,447 km2), and musk deer (1,690 km2) in Gandaki Province. Most of the areas of suitable habitat for common leopards and Asiatic black bears were outside the protected areas, and for musk deer and snow leopards were inside the protected areas. Elevation was the most important variable determining habitat suitability of Asiatic black bear, common leopard, and musk deer, whereas the distance to water was the most important variable determining habitat suitability of snow leopard. Asiatic black bears, common leopards, and musk deer face significant anthropogenic impacts, but snow leopards face some anthropogenic impacts. Conclusion Managing these animals’ habitats inside and outside protected areas is essential. Hence, biodiversity conservation and livelihood opportunities should be balanced in the Himalayas on a win-win basis.
Malla et al. (2023) Habitat suitability of four threatened Himalayan species: Asiatic black bear, common leopard, musk deer, and snow leopard. PeerJ 11:e16085 https://doi.org/10.7717/peerj.16085
Exploring the relationship between nutritional intake and menstrual cycle in elite female athletes
This study aimed to examine potential variations in nutritional intake among female athletes, including top-level, throughout the menstrual cycle. A total 122 female athletes participated in the study, documenting their food consumption over a 3-day period. The menstrual status of female athletes was also assessed, and using the survey results, the phase of the menstrual cycle (the follicular, early luteal, or late luteal) during which each meal was recorded was determined. Consequently, the meal records were categorized into the respective three phases. The findings of this study indicated that there were no notable disparities in nutritional intake, encompassing energy, protein, fat, carbohydrate, calcium, iron, and fiber, across the three phases of the menstrual cycle. The results imply that female athletes may experience comparatively smaller variations in nutrient intake related to the menstrual cycle. This could be attributed to the higher energy requirements of female athletes because of their rigorous training. This study underscores the significance of accounting for the population when examining nutrient intake changes associated with the menstrual cycle.
Miyamoto et al. (2023) Exploring the relationship between nutritional intake and menstrual cycle in elite female athletes. PeerJ 11:e16108 https://doi.org/10.7717/peerj.16108
DeepMethylation: a deep learning based framework with GloVe and Transformer encoder for DNA methylation prediction
DNA methylation is a crucial topic in bioinformatics research. Traditional wet experiments are usually time-consuming and expensive. In contrast, machine learning offers an efficient and novel approach. In this study, we propose DeepMethylation, a novel methylation predictor with deep learning. Specifically, the DNA sequence is encoded with word embedding and GloVe in the first step. After that, dilated convolution and Transformer encoder are utilized to extract the features. Finally, full connection and softmax operators are applied to predict the methylation sites. The proposed model achieves an accuracy of 97.8% on the 5mC dataset, which outperforms state-of-the-art methods. Furthermore, our predictor exhibits good generalization ability as it achieves an accuracy of 95.8% on the m1A dataset. To ease access for other researchers, our code is publicly available at https://github.com/sb111169/tf-5mc.
Wang et al. (2023) DeepMethylation: a deep learning based framework with GloVe and Transformer encoder for DNA methylation prediction. PeerJ 11:e16125 https://doi.org/10.7717/peerj.16125
Seroprevalence of SARS-CoV-2 anti-spike IgG antibody among COVID-19 vaccinated individuals residing in Surabaya, East Java, Indonesia
Background To limit the SARS-CoV-2 transmission, the Indonesian government launched a COVID-19 vaccination program in January 2021. Studies on the clinical treatment and implementation of COVID-19 vaccination have shown promising results; however, it is necessary to estimate the effectiveness of the vaccines. With the ongoing COVID-19 pandemic, studies have highlighted the impact of COVID-19 vaccines, especially CoronaVac, on Indonesian healthcare workers. To get a better picture of how the vaccines work in Indonesia, it is necessary to estimate the prevalence of SARS-CoV-2 anti-S IgG antibody induced by the COVID-19 vaccine in individuals who have already received two-to-three doses of vaccines. Materials and Methods Four-hundred and ninety-six whole-blood samples were collected from participants residing in Surabaya, East Java, Indonesia, who received a minimum of a two-dose COVID-19 vaccine. Serums were then isolated from the blood and subjected to detect SARS-CoV-2 anti-S IgG antibodies using a lateral flow immunochromatographic assay. Results The prevalence of positive anti-S-IgG antibodies was 91.7% (455/496) in all participants receiving a minimum of a two-dose COVID-19 vaccine. As many as 209 (85.3%) and 141 (96.6%) participants were seropositive for receiving CoronaVac and AstraZeneca, respectively. Meanwhile, all participants receiving two-dose CoronaVac with one booster dose of Moderna (105/100%) were seropositive (p < 0.05). Age, comorbidity, and time after the last vaccine were significantly correlated with seropositivity (p < 0.05). Conclusion Different vaccines might produce different antibody responses. Adopting a stronger policy regarding the administration of booster doses might be beneficial to elicit positive anti-S-IgG antibodies, especially among older individuals, those with comorbid diseases, and those with a longer time after the second vaccination dose.
Megasari et al. (2023) Seroprevalence of SARS-CoV-2 anti-spike IgG antibody among COVID-19 vaccinated individuals residing in Surabaya, East Java, Indonesia. PeerJ 11:e16142 https://doi.org/10.7717/peerj.16142
Classification and prediction of Klebsiella pneumoniae strains with different MLST allelic profiles via SERS spectral analysis
The Gram-negative non-motile Klebsiella pneuomoniae is currently a major cause of hospital-acquired (HA) and community-acquired (CA) infections, leading to great public health concern globally, while rapid identification and accurate tracing of the pathogenic bacterium is essential in facilitating monitoring and controlling of K. pneumoniae outbreak and dissemination. Multi-locus sequence typing (MLST) is a commonly used typing approach with low cost that is able to distinguish bacterial isolates based on the allelic profiles of several housekeeping genes, despite low resolution and labor intensity of the method. Core-genome MLST scheme (cgMLST) is recently proposed to sub-type and monitor outbreaks of bacterial strains with high resolution and reliability, which uses hundreds or thousands of genes conserved in all or most members of the species. However, the method is complex and requires whole genome sequencing of bacterial strains with high costs. Therefore, it is urgently needed to develop novel methods with high resolution and low cost for bacterial typing. Surface enhanced Raman spectroscopy (SERS) is a rapid, sensitive and cheap method for bacterial identification. Previous studies confirmed that classification and prediction of bacterial strains via SERS spectral analysis correlated well with MLST typing results. However, there is currently no similar comparative analysis in K. pneumoniae strains. In this pilot study, 16 K. pneumoniae strains with different sequencing typings (STs) were selected and a phylogenetic tree was constructed based on core genome analysis. SERS spectra (N = 45/each strain) were generated for all the K. pneumoniae strains, which were then comparatively classified and predicted via six representative machine learning (ML) algorithms. According to the results, SERS technique coupled with the ML algorithm support vector machine (SVM) could achieve the highest accuracy (5-Fold Cross Validation = 100%) in terms of differentiating and predicting all the K. pneumoniae strains that were consistent to corresponding MLSTs. In sum, we show in this pilot study that the SERS-SVM based method is able to accurately predict K. pneumoniae MLST types, which has the application potential in clinical settings for tracing dissemination and controlling outbreak of K. pneumoniae in hospitals and communities with low costs and high rapidity.
Zhang et al. (2023) Classification and prediction of Klebsiella pneumoniae strains with different MLST allelic profiles via SERS spectral analysis. PeerJ 11:e16161 https://doi.org/10.7717/peerj.16161
Systematic and meta-based evaluation of the relationship between the built environment and physical activity behaviors among older adults
Objectives Existing assertions about the relationship between various factors of the built environment and physical activity behaviors are inconsistent and warrant further exploration and analysis. Methods This study systematically searched PubMed, Embase, Web of Science, Scopus, the Cochrane Library and Google Scholar for the effect of the built environment on the physical activity behaviors of older adults. R software was used to calculate the meta-estimated odds ratio with a 95% confidence interval. Simultaneously, the quality of included studies was evaluated using an observational study quality evaluation standard recommended by American health care quality and research institutions. Results A total of 16 original researches were included in this meta-analysis and eight factors of the built environment were evaluated. These factors which ranked from high to low according to their impact were traffic safety (OR = 1.58, 95% CI [1.14–2.20]), destination accessibility (OR = 1.24, 95% CI [1.06–1.44]), aesthetics of sports venues (OR = 1.21, 95% CI [1.07–1.37]), virescence of sports venues (OR = 1.14, 95% CI [1.06–1.23]), building density (OR = 1.07, 95% CI [1.02–1.13]). Additionally, it seemed that there was no potential association between mixed land use (OR = 1.01, 95% CI [0.92–1.10]), the quality of pedestrian facilities (OR = 1.00, 95% CI [0.92–1.08]) or commercial facilities (OR = 0.94, 95% CI [0.88–1.00]) and physical activity behaviors of older adults. Conclusions The built environment has been found to exhibit a significant relationship with the physical activity behaviors of older adults. It is proposed that factors such as traffic safety, destination accessibility, aesthetics of sports venues, virescence of sports venues, and building density be given more consideration when aiming to promote physical activity levels among older adults.
You et al. (2023) Systematic and meta-based evaluation of the relationship between the built environment and physical activity behaviors among older adults. PeerJ 11:e16173 https://doi.org/10.7717/peerj.16173
Comprehensive analyses of genetic diversities and population structure of the Guizhou Dong group based on 44 Y-markers
Background The non-recombining region of the human Y chromosome (NRY) is a strictly paternally inherited genetic marker and the best material to trace the paternal lineages of populations. Y chromosomal short tandem repeat (Y-STR) is characterized by high polymorphism and paternal inheritance pattern, so it has been widely used in forensic medicine and population genetic research. This study aims to understand the genetic distribution of Y-STRs in the Guizhou Dong population, provide reference data for forensic application, and explore the phylogenetic relationships between the Guizhou Dong population and other comparison populations. Methods Based on the allele profile of 44 Y-markers in the Guizhou Dong group, we estimate their allele frequencies and haplotype frequencies. In addition, we also compare the forensic application efficiency of different Y-STR sets in the Guizhou Dong group. Finally, genetic relationships among Guizhou Dong and other reference populations are dissected by the multi-dimensional scaling and the phylogenetic tree. Results A total of 393 alleles are observed in 312 Guizhou Dong individuals for these Y-markers, with allele frequencies ranging from 0.0032 to 0.9679. The haplotype diversity and discriminatory capacity for these Y-markers in the Guizhou Dong population are 0.99984 and 0.97440, respectively. The population genetic analyses of the Guizhou Dong group and other reference populations show that the Guizhou Dong group has the closest genetic relationship with the Hunan Dong population, and followed by the Guizhou Tujia population. Conclusions In conclusion, these 44 Y-markers can be used as an effective tool for male differentiation in the Guizhou Dong group. The haplotype data in this study not only enrich the Y-STR data of different ethnic groups in China, but also have important significance for population genetics and forensic research.
Zhang et al. (2023) Comprehensive analyses of genetic diversities and population structure of the Guizhou Dong group based on 44 Y-markers. PeerJ 11:e16183 https://doi.org/10.7717/peerj.16183