COVID-19 mortality is associated with pre-existing impaired innate immunity in health conditions
COVID-19 can be life-threatening to individuals with chronic diseases. To prevent severe outcomes, it is critical that we comprehend pre-existing molecular abnormalities found in common health conditions that predispose patients to poor prognoses. In this study, we focused on 14 pre-existing health conditions for which increased hazard ratios of COVID-19 mortality have been documented. We hypothesized that dysregulated gene expression in these pre-existing health conditions were risk factors of COVID-19 related death, and the magnitude of dysregulation (measured by fold change) were correlated with the severity of COVID-19 outcome (measured by hazard ratio). To test this hypothesis, we analyzed transcriptomics data sets archived before the pandemic in which no sample had COVID-19. For a given pre-existing health condition, we identified differentially expressed genes by comparing individuals affected by this health condition with those unaffected. Among genes differentially expressed in multiple health conditions, the fold changes of 70 upregulated genes and 181 downregulated genes were correlated with hazard ratios of COVID-19 mortality. These pre-existing dysregulations were molecular risk factors of severe COVID-19 outcomes. These genes were enriched with endoplasmic reticulum and mitochondria function, proinflammatory reaction, interferon production, and programmed cell death that participate in viral replication and innate immune responses to viral infections. Our results suggest that impaired innate immunity in pre-existing health conditions is associated with increased hazard of COVID-19 mortality. The discovered molecular risk factors are potential prognostic biomarkers and targets for therapeutic intervention.
Lee et al. (2022) COVID-19 mortality is associated with pre-existing impaired innate immunity in health conditions. PeerJ 10:e13227 https://doi.org/10.7717/peerj.13227
Bacterial profile of bovine mastitis in Ethiopia: a systematic review and meta-analysis
Background Bovine mastitis is the commonest episode of infection in the dairy industry, which often occurs after damage of epithelial cells lining the teat duct. It is ranked as the second most important cause of milk production loss directly and a devastating disease with a higher incidence leading to the culling of dairy cows. Thus, this systematic review and meta-analysis is aimed to quantitatively estimate the current status of mastitis in general and bacterial mastitis particular in Ethiopia. Methods A literature search was carried from major databases and indexing services including PubMed, Google Scholar, Science Direct. Also, local institution repositories were searched to retrieve unpublished MSc and PhD theses. All studies were included addressing the prevalence of mastitis and bacterial isolates conducted in Ethiopia. Microsoft Excel was used to extract data and was imported to R Studio for the analyses. The random-effects model at a 95% confidence level was used for pooled estimates of outcomes. The degree of heterogeneity was computed by Higgins’s I2 statistics. Publication bias was checked by using the funnel plots of standard error augmented by Begg’s and Egger’s tests. Results A total of 46 studies with 15,780 cows were included in this study. All studies have collected 18,478 suspected samples for bacterial isolation. While pooled prevalence estimate of mastitis was 47.6%, the bacterial isolates pooled prevalence was 33.1%. The bacterial mastitis was 6.5% in cows infected by clinical patients and was 28.3% subclinical patients. The common isolates were Staph aureus, Strep species, Staph epidermis, Escherchia coli, Corynebacterium bovis, Coagulase Negative Staphylococcus and Klebsiella species. A univariate meta-regression analysis evidenced that the type of mastitis and management system was a possible source of heterogeneity (P-value = 0.001). Conclusion The pooled prevalence of bacterial mastitis in Ethiopian dairy cattle was high. The analysis showed bacterial pathogens like Staphylococcus aureus, Staph epidermis, Strep species and Coagulase Negative Staphylococcus are majorly accounted for bovine mastitis in Ethiopia. Therefore, the highly prevalent and commonly isolated pathogens cause contagious mastitis which require immediate attention by dairy producers to put under control by devising robust mastitis prevention and control interventions.
Tora et al. (2022) Bacterial profile of bovine mastitis in Ethiopia: a systematic review and meta-analysis. PeerJ 10:e13253 https://doi.org/10.7717/peerj.13253
Development of nitrogen efficiency screening system in alfalfa (Medicago sativa L.) and analysis of alfalfa nitrogen efficiency types
Screening high nitrogen (N) efficiency crops is crucial to utilize resources rationally and reduce N losses. In this research, the biomass, morphological and N-related parameters of 28 alfalfa (Medicago sativa L.) cultivars were assessed at seedling stage. Then, we selected representative materials to compare the changes in stem-leaf dry weight (SDW), total root length (RL) and plant N accumulation (PNA) during whole period. Lastly, we analyzed the expressions of NRT2 and AMT1 genes of alfalfa cultivars. The correlation coefficients between SDW, PDW, RL, RV, SNA, RNA, and PNA were all in the range of 0.522∼0.996. The coefficient of variations of SDW, PDW, RL, RV, SNA and PNA were all more than 20% under low and medium N levels. Though the comprehensive evaluation and cluster analysis, the comprehensive value of LW6010, Gannong NO.5, Longmu 806, Giant 2, Giant 601, Zhaodong, Crown were greater than 0.5 under low and medium N levels; the comprehensive value of Gannong NO.3, Gannong NO.4, Xinjiangdaye, Xinmu NO.1 were less than 0.5 under low N level, but were greater than 0.5 under medium N level. The comprehensive value of Gannong NO.7 Gannong NO.9, Longmu 801, Gongnong NO.3, Elite, Sadie 10, Giant 551 were greater than 0.5 under low N level, but were lesser than 0.5 under medium N level; and those of Longdong, Gannong NO.8, Gongnong NO.1, Reindee, Goldqueen, Weston, Tourists, Giant 6, Algonquin, Sadie 7 were lesser than 0.5 under low and medium N levels. Four N efficiency types of alfalfa cultivars were classified: (1) Very efficient; (2) Efficient; (3) Anti-efficient; and (4) Inefficient.The SDW, RL and PNA of LW6010 were higher than Longdong in each growth period. The expressions of NRT2 and AMT1 genes were highest for LW6010, and lowest for Longdong. So, N efficiency parameters assessed at seedling stage include: SDW, PDW, RL, RV, SNA and PNA. We developed new classification system of N efficiency types of alfalfa cultivars. It proved its effectiveness on 28 alfalfa in China.
Liu et al. (2022) Development of nitrogen efficiency screening system in alfalfa (Medicago sativa L.) and analysis of alfalfa nitrogen efficiency types. PeerJ 10:e13343 https://doi.org/10.7717/peerj.13343
Excessive alcohol consumption and binge drinking in college students
Background Binge drinking (BD) refers to a pattern of alcohol consumption characterized by the consumption of large amounts of alcohol in a short period of time followed by periods of abstinence. This drinking pattern is prevalent worldwide, mainly among young people. Excessive alcohol consumption is the spectrum of consumption patterns that may have or have had health consequences, and includes the concepts of risky alcohol use, harmful alcohol use and alcohol dependence according to Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV), the latter two are currently grouped into alcohol use disorder (AUD) according to the fifth edition of the DSM (DSM-5). Due to the high prevalence of BD among young people, especially university students, as well as the important consequences of its practice, a study was conducted to evaluate excessive alcohol consumption and its relationship with the practice of BD in university students. Methods A cross-sectional study was conducted among students (aged 18–30 years) enrolled in the academic year 2018–2019 at the Faculty of Nursing at a university in northern Spain. Data collection included sociodemographic information, and alcohol use information, collected using a semi-structured questionnaire. To measure the excessive alcohol consumption, this study used the Alcohol Use Disorders Identification Test (AUDIT). Results A total of 142 participants were included, of which 88.03% were women. Up to 38.03% were classified as BD. Up to 14.77% of non-BD participants and 66.67% of BD participants were classified as risky drinkers (AUDIT Total geq 8 in men or geq 6 in women) (p < 0.001). Up to 3.41% of the non-BD and 24.07% of the BD were drinkers with harmful alcohol use and probable alcohol dependence (AUDIT Total geq 13) (p < 0.001). A total of 5.68% of non-BD and 42.59% of BD were AUD drinkers (AUDIT Total geq 9 in males or geq 8 in females) (p < 0.001). In addition, statistically significant differences were found between the BD and non-BD groups in the responses to each of the AUDIT items, as well as in the total score and also in the scores of the three domains of the questionnaire. Conclusions Excessive alcohol consumption is frequent among university students, especially among those who practice BD.
Herrero-Montes et al. (2022) Excessive alcohol consumption and binge drinking in college students. PeerJ 10:e13368 https://doi.org/10.7717/peerj.13368
Temperature responsiveness of soil carbon fractions, microbes, extracellular enzymes and CO2 emission: mitigating role of texture
The interaction of warming and soil texture on responsiveness of the key soil processes i.e. organic carbon (C) fractions, soil microbes, extracellular enzymes and CO2 emissions remains largely unknown. Global warming raises the relevant question of how different soil processes will respond in near future, and what will be the likely regulatory role of texture? To bridge this gap, this work applied the laboratory incubation method to investigate the effects of temperature changes (10–50 °C) on dynamics of labile, recalcitrant and stable C fractions, soil microbes, microbial biomass, activities of extracellular enzymes and CO2 emissions in sandy and clayey textured soils. The role of texture (sandy and clayey) in the mitigation of temperature effect was also investigated. The results revealed that the temperature sensitivity of C fractions and extracellular enzymes was in the order recalcitrant C fractions > stable C fractions > labile C fractions and oxidative enzymes > hydrolytic enzymes. While temperature sensitivity of soil microbes and biomass was in the order bacteria > actinomycetes > fungi ≈ microbial biomass C (MBC) > microbial biomass N (MBN) > microbial biomass N (MBP). Conversely, the temperature effect and sensitivity of all key soil processes including CO2 emissions were significantly (P < 0.05) higher in sandy than clayey textured soil. Results confirmed that under the scenario of global warming and climate change, soils which are sandy in nature are more susceptible to temperature increase and prone to become the CO2-C sources. It was revealed that clayey texture played an important role in mitigating and easing off the undue temperature influence, hence, the sensitivity of key soil processes.
Hassan et al. (2022) Temperature responsiveness of soil carbon fractions, microbes, extracellular enzymes and CO2 emission: mitigating role of texture. PeerJ 10:e13151 https://doi.org/10.7717/peerj.13151
Physical characteristics of elite youth male football players aged 13–15 are based upon biological maturity
Background Older and more mature football players have been reported to gain advantages in the selection process during adolescence. The aim of this study was to investigate the influence of skeletal age (SA) on the physical characteristics of elite male football players aged 13–15 years through a cross-sectional study. Methods and Materials We enrolled 167 elite players aged 13–15 from three academic football schools in China, and measured height, body mass, thigh circumference, skinfold (triceps and calf), 10 m/30-m sprint, T-tests (left and right), 5 × 25-m repeated-sprint ability (5 × 25 RSA), standing long jump, and YoYo intermittent recovery test level 1 (YYIR1). Subjects were divided into early-, average-, and late-maturity levels according to their SA and chronological age (CA) based on the following criteria: SA-CA > +1 year, SA-CA = ±1 year, and SA-CA < −1 year, respectively. The differences in parameters among the groups were analyzed using one-way analysis of variance and Bonferroni’s post-hoc test, with statistical significance set at p < 0.05. Results Relative to the late-maturing players, the early- and average-maturing players aged 13–15 years were taller, heavier, had a larger thigh circumference, and scored higher on the standing long jump, 30 m sprint, and 5 × 25-RSA (p < 0.05). The physical (except for body-fat percentage) and athletic characteristics of players aged 13–15 were not only significantly influenced by biological maturity, but also increased significantly with CA. The influence of biological maturity on height, 30-m sprints, and 5 × 25-m RSA diminished with age and exerted no significant effect on body-fat percentage and on YYIR1. Late-maturing players exhibited the greatest increase in physical (except for body-fat percentage) and athletic performance (except for the 10-m sprint) compared to players of early and/or average maturity. Conclusions Although early-maturing players aged 13–15 possessed better anthropometric and physical performance than late- and average-maturing players, the growth and development of physical function of late- and average-maturing players was significantly greater, particularly with respect to height, sprint speed, and muscular power.
Yang et al. (2022) Physical characteristics of elite youth male football players aged 13–15 are based upon biological maturity. PeerJ 10:e13282 https://doi.org/10.7717/peerj.13282
Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa
Background Mucins are part of the glycoprotein family and the main proteinaceous component of mucus. The sea anemone species, Actinia tenebrosa (Phylum Cnidaria) produce large amounts of mucus, which have not been studied in detail. Furthermore, there has only been limited investigation of mucin genes in phylum Cnidaria. Therefore, the aim of current study was to identify and analyse the repertoire mucin genes present in A. tenebrosa and range of other sea anemone species to document their diversity in this group. Methods To achieve this aim, we undertook transcriptome sequencing, assembly, and annotation to identify mucin genes in A. tenebrosa. Results The results from this study demonstrated a diverse repertoire of mucin proteins, including mucin1-like, mucin4-like, and a range of mucin-like genes in the range of sea anemone species examined. The domain structure of the identified mucin genes was found to be consistent with the conserved domains found in the homologous proteins of vertebrate species. The discovery of a diverse range of mucin genes in sea anemone species provided a basic reference for future mucin studies in cnidarians and could lead to research into their application in the pharmacological, clinical, and cosmetic industries.
Haridi (2022) Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa. PeerJ 10:e13292 https://doi.org/10.7717/peerj.13292
Text mining for identification of biological entities related to antibiotic resistant organisms
Antimicrobial resistance is a significant public health problem worldwide. In recent years, the scientific community has been intensifying efforts to combat this problem; many experiments have been developed, and many articles are published in this area. However, the growing volume of biological literature increases the difficulty of the biocuration process due to the cost and time required. Modern text mining tools with the adoption of artificial intelligence technology are helpful to assist in the evolution of research. In this article, we propose a text mining model capable of identifying and ranking prioritizing scientific articles in the context of antimicrobial resistance. We retrieved scientific articles from the PubMed database, adopted machine learning techniques to generate the vector representation of the retrieved scientific articles, and identified their similarity with the context. As a result of this process, we obtained a dataset labeled “Relevant” and “Irrelevant” and used this dataset to implement one supervised learning algorithm to classify new records. The model’s overall performance reached 90% accuracy and the f-measure (harmonic mean between the metrics) reached 82% accuracy for positive class and 93% for negative class, showing quality in the identification of scientific articles relevant to the context. The dataset, scripts and models are available at https://github.com/engbiopct/TextMiningAMR.
Fortunato Costa et al. (2022) Text mining for identification of biological entities related to antibiotic resistant organisms. PeerJ 10:e13351 https://doi.org/10.7717/peerj.13351
How training loads in the preparation and competitive period affect the biochemical indicators of training stress in youth soccer players?
Background Physical fitness optimization and injury risk-reducing require extensive monitoring of training loads and athletes’ fatigue status. This study aimed to investigate the effect of a 6-month training program on the training-related stress indicators (creatine kinase – CK; cortisol – COR; serotonin – SER; brain-derived neurotrophic factor – BDNF) in youth soccer players. Methods Eighteen players (17.8 ± 0.9 years old, body height 181.6 ± 6.9 cm, training experience 9.7 ± 1.7 years) were blood-tested four times: at the start of the preparation period (T0), immediately following the preparation period (T1), mid-competitive period (T2), and at the end of the competitive period (T3). CK activity as well as concentrations of serum COR, SER and BDNF were determined. Training loads were recorded using a session rating of perceived exertion (sRPE). Results Statistical analyzes revealed significant effects for all biochemical parameters in relation to their time measurements (T0, T1, T2, T3). The statistical analyzes of sRPE and differences of biochemical parameters in their subsequent measurements (T0–T1, T1–T2, T2–T3) also demonstrated significant effects observed for all variables: sRPE (HKW = 13.189 (df = 2); p = 0.00), COR (HKW = 9.261 (df = 2); p = 0.01), CK (HKW = 12.492 (df = 2); p = 0.00), SER (HKW = 7.781 (df = 2); p = 0.02) and BDNF (HKW = 15.160 (df = 2); p < 0.001). Discussion In conclusion, it should be stated that the most demanding training loads applied in the preparation period (highest sRPE values) resulted in a significant increase in all analyzed biochemical training stress indicators. The reduction in the training loads during a competitive period and the addition of recovery training sessions resulted in a systematic decrease in the values of the measured biochemical indicators. The results of the study showed that both subjective and objective markers, including training loads, are useful in monitoring training stress in youth soccer players.
Andrzejewski et al. (2022) How training loads in the preparation and competitive period affect the biochemical indicators of training stress in youth soccer players?. PeerJ 10:e13367 https://doi.org/10.7717/peerj.13367
Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study
Background This study was performed to construct and validate an early risk warning model of urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD). Methods Eligible patients with NLUTD admitted to Shenzhen Longcheng hospital from January 2017 to June 2021 were recruited for model construction, internal validation and external validation. The first time point of data collection was within half a month of patients first diagnosed with NLUTD. The second time point was at the 6-month follow-up. The early warning model was constructed by logistic regression. The model prediction effects were validated using the area under the Receiver Operating Characteristic curve, the Boostrap experiment and the calibration plot of the combined data. The model was externally validated using sensitivity, specificity and accuracy. Results Six predictors were identified in the model, namely patients ≥65 years old (OR = 2.478, 95%CI [1.215– 5.050]), female (OR = 2.552, 95%CI [1.286–5.065]), diabetes (OR = 2.364, 95%CI) [1.182–4.731]), combined with urinary calculi (OR = 2.948, 95%CI [1.387–6.265]), indwelling catheterization (OR = 1.988, 95%CI [1.003 –3.940]) and bladder behavior training intervention time ≥2 weeks (OR = 2.489, 95%CI [1.233–5.022]); and the early warning model formula was Y = 0.907 × age+ 0.937 × sex + 0.860 × diabetes +1.081 × combined with urinary calculi+ 0.687 × indwelling catheterization+ 0.912 × bladder behavior training intervention time-2.570. The results show that the area under the ROC curve is 0.832, which is close to that of 1,000 Bootstrap internal validation (0.828). The calibration plot shows that the early warning model has good discrimination ability and consistency. The external validation shows the sensitivity is 62.5%, the specificity is 100%, and the accuracy is 90%. Conclusion The early warning model for urinary tract infection in patients with NLUTD is suitable for clinical practice, which can provide targeted guidance for the evaluation of urinary tract infection in patients with NLUTD.
Zhou et al. (2022) Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study. PeerJ 10:e13388 https://doi.org/10.7717/peerj.13388