Earthworms neutralize the influence of components of particulate pollutants on soil extracellular enzymatic functions in subtropical forests
Human activities are increasing the input of atmospheric particulate pollutants to forests. The components of particulate pollutants include inorganic anions, base cations and hydrocarbons. Continuous input of particulate pollutants may affect soil functioning in forests, but their effects may be modified by soil fauna. However, studies investigating how soil fauna affects the effects of particulate pollutants on soil functioning are lacking. Here, we investigated how earthworms and the particulate components interact in affecting soil enzymatic functions in a deciduous (Quercus variabilis) and a coniferous (Pinus massoniana) forest in southeast China. We manipulated the addition of nitrogen (N, ammonium nitrate), sodium (Na, sodium chloride) and polycyclic aromatic hydrocarbons (PAHs, five mixed PAHs) in field mesocosms with and without Eisenia fetida, an earthworm species colonizing forests in eastern China. After one year, N and Na addition increased, whereas PAHs decreased soil enzymatic functions, based on average Z scores of extracellular enzyme activities. Earthworms generally stabilized soil enzymatic functions via neutralizing the effects of N, Na and PAHs addition in the deciduous but not in the coniferous forest. Specifically, earthworms neutralized the effects of N and Na addition on soil pH and the effects of the addition of PAHs on soil microbial biomass. Further, both particulate components and earthworms changed the correlations among soil enzymatic and other ecosystem functions in the deciduous forest, but the effects depended on the type of particulate components. Generally, the effects of particulate components and earthworms on soil enzymatic functions were weaker in the coniferous than the deciduous forest. Overall, the results indicate that earthworms stabilize soil enzymatic functions in the deciduous but not the coniferous forest irrespective of the type of particulate components. This suggests that earthworms may neutralize the influence of atmospheric particulate pollutants on ecosystem functions, but the neutralization may be restricted to deciduous forests.
Yang et al. (2023) Earthworms neutralize the influence of components of particulate pollutants on soil extracellular enzymatic functions in subtropical forests. PeerJ 11:e15720 https://doi.org/10.7717/peerj.15720
Prevalence of bone loss surrounding dental implants as detected in cone beam computed tomography: a cross-sectional study
Objectives The objective of this study was to assess the prevalence of crestal, and apical bone loss (CBL & ABL) associated with dental implants in CBCT scans. The second objective was to assess the radiographic stage of implant disease and the visible predisposing factors. Materials and Methods The CBCT scans that were taken from January 2015 to January 2022 in King Saud Medical City were screened to examine the marginal and periapical condition of dental implants. Information related to demographic variables, stage of bone loss, and radiographically evident predisposing factors were collected. The results were analyzed using descriptive statistics, chi-square test, and logistic regression analysis. Results In total, 772 implant scans were analyzed. The prevalence of crestal bone loss and apical bone loss around the implants were 6.9% and 0.4% respectively. The amount of bone loss was moderate in 52.8% of cases of CBL and 100% mild in cases of ABL. The risk factors for CBL were patient age (p < 0.001), implant location (p < 0.001), bone loss in proximal teeth (p < 0.001), and adjacent edentulous sites (p < 0.001). The risk factors for ABL were adjacent periapical infection (p < 0.001) and endodontic therapy (p = 0.024). Conclusion The prevalence of CBL and ABL was low. The CBCT can be used as a diagnostic tool for studying the prevalence of bone loss associated with peri-implant disease and relevant risk factors. The implantation of CBCT to evaluate the success and the prognosis of dental implants or the treatment of peri-implant diseases can be further considered in future research.
Algahtani et al. (2023) Prevalence of bone loss surrounding dental implants as detected in cone beam computed tomography: a cross-sectional study. PeerJ 11:e15770 https://doi.org/10.7717/peerj.15770
Effects of harvest stages and lactic acid bacteria additives on the nutritional quality of silage derived from triticale, rye, and oat on the Qinghai-Tibet Plateau
Background Triticale (×Triticosecale Wittmack L.), rye (Secale cereale L.), and oat (Avena sativa L.) are the main forage crops on the Qinghai–Tibet Plateau, but there has been relatively little research on the silage produced from these three species. Methods Plants were harvested at the heading, flowering, grouting, milky, and dough stages and then used to produce silage with and without additives (Sila-Max and Sila-Mix). The nutritional quality of the resulting silages was analyzed. Results Triticale was revealed to be more suitable than oat or rye for producing silage on the Qinghai–Tibet Plateau. On the basis of the dry matter yield (DMY), triticale and rye should be harvested at the milky stage to optimize silage quality, whereas oat should be harvested at the dough stage. The lactic acid bacteria additives Sila-Max and Sila-Mix had no significant effect on the nutritional quality of the three silages regardless of when the samples were harvested. Overall, triticale produced higher quality silage than oat or rye. More specifically, triticale variety ‘Gannong No.2’ harvested at the milky stage is ideal for silage production.
Ma et al. (2023) Effects of harvest stages and lactic acid bacteria additives on the nutritional quality of silage derived from triticale, rye, and oat on the Qinghai-Tibet Plateau. PeerJ 11:e15772 https://doi.org/10.7717/peerj.15772
Risk factors for high CAD-RADS scoring in CAD patients revealed by machine learning methods: a retrospective study
Objective This study aimed to investigate a variety of machine learning (ML) methods to predict the association between cardiovascular risk factors and coronary artery disease-reporting and data system (CAD-RADS) scores. Methods This is a retrospective cohort study. Demographical, cardiovascular risk factors and coronary CT angiography (CCTA) characteristics of the patients were obtained. Coronary artery disease (CAD) was evaluated using CAD-RADS score. The stenosis severity component of the CAD-RADS was stratified into two groups: CAD-RADS score 0-2 group and CAD-RADS score 3–5 group. CAD-RADS scores were predicted with random forest (RF), k-nearest neighbors (KNN), support vector machines (SVM), neural network (NN), decision tree classification (DTC) and linear discriminant analysis (LDA). Prediction sensitivity, specificity, accuracy and area under the curve (AUC) were calculated. Feature importance analysis was utilized to find the most important predictors. Results A total of 442 CAD patients with CCTA examinations were included in this study. 234 (52.9%) subjects were CAD-RADS score 0–2 group and 208 (47.1%) were CAD-RADS score 3–5 group. CAD-RADS score 3-5 group had a high prevalence of hypertension (66.8%), hyperlipidemia (50%) and diabetes mellitus (DM) (35.1%). Age, systolic blood pressure (SBP), mean arterial pressure, pulse pressure, pulse pressure index, plasma fibrinogen, uric acid and blood urea nitrogen were significantly higher (p < 0.001), and high-density lipoprotein (HDL-C) lower (p < 0.001) in CAD-RADS score 3–5 group compared to the CAD-RADS score 0–2 group. Nineteen features were chosen to train the models. RF (AUC = 0.832) and LDA (AUC = 0.81) outperformed SVM (AUC = 0.772), NN (AUC = 0.773), DTC (AUC = 0.682), KNN (AUC = 0.707). Feature importance analysis indicated that plasma fibrinogen, age and DM contributed most to CAD-RADS scores. Conclusion ML algorithms are capable of predicting the correlation between cardiovascular risk factors and CAD-RADS scores with high accuracy.
Dai et al. (2023) Risk factors for high CAD-RADS scoring in CAD patients revealed by machine learning methods: a retrospective study. PeerJ 11:e15797 https://doi.org/10.7717/peerj.15797
Uncovering the Grinnellian niche space of the cryptic species complex Gammarus roeselii
Background The discovery of cryptic species complexes within morphologically established species comes with challenges in the classification and handling of these species. We hardly know to what extent species within a species complex differ ecologically. Such knowledge is essential to assess the vulnerability of individual genetic lineages in the face of global change. The abiotic conditions, i.e., the Grinnellian niche that a genetic lineage colonizes, provides insights into how diverse the ecological requirements of each evolutionary lineage are within a species complex. Material and Methods We sampled the cryptic species complex of the amphipod Gammarus roeselii from Central Germany to Greece and identified genetic lineages based on cytochrome c oxidase subunit I (COI) barcoding. At the same time, we recorded various abiotic parameters and local pollution parameters using a series of in vitro assays to then characterize the Grinnellian niches of the morphospecies (i.e., Gammarus roeselii sensu lato) as well as each genetic lineage. Local pollution can be a significant factor explaining current and future distributions in times of increasing production and release of chemicals into surface waters. Results We identified five spatially structured genetic lineages in our dataset that differed to varying degrees in their Grinnellian niche. In some cases, the niches were very similar despite the geographical separation of lineages, supporting the hypothesis of niche conservatism while being allopatrically separated. In other cases, we found a small niche that was clearly different from those of other genetic lineages. Conclusion The variable niches and overlaps of different dimensions make the G. roeselii species complex a promising model system to further study ecological, phenotypic and functional differentiation within this species complex. In general, our results show that the Grinnellian niches of genetically distinct molecular operational taxonomic units (MOTUs) within a cryptic species complex can differ significantly between each other, calling for closer inspection of cryptic species in a conservational and biodiversity context.
Kabus et al. (2023) Uncovering the Grinnellian niche space of the cryptic species complex Gammarus roeselii. PeerJ 11:e15800 https://doi.org/10.7717/peerj.15800
The effect of three different pre-match warm-up structures on male professional soccer players’ physical fitness
Background Optimizing the soccer players’ match preparation is one of the most relevant concerns of coaches for strength and conditioning training. Thus, the aim of this study was to analyze the effects of three pre-match warm-up structures on the physical condition of male professional soccer players. Materials & Methods Seventeen male professional soccer players (age: 20.9 ± 2.4 years) of one Tunisian Professional Soccer League team participated in this study. Players performed three times a typical pre-match warm-up (WU) [aerobic phase (AE); neuromuscular phase (NM); velocity phase (VL); and ball-specific phase (BS) variating the order of the included phases/exercises: WU1 (AE + BS + NM + VL); WU2 (AE + NM + VL + BS); and WU3 (AE + VL + BS + NM). After each warm-up phase, players completed the following physical fitness tests: linear sprint test, countermovement jump test, 15-m ball dribbling agility test and ball shooting test. Additionally, the rate of perceived exertion (RPE) was registered after each warm-up. Results The results indicated significant differences between WU1 and WU3, with better results in the ball shooting test and RPE in WU3. In addition, there were no significant differences in the other variables and between other warm-up structures. These findings could be of great interest for coaches to the strength and conditioning coaches for professional soccer teams in order to improve the players physical performance and perceived exertion.
Ben Brahim et al. (2023) The effect of three different pre-match warm-up structures on male professional soccer players’ physical fitness. PeerJ 11:e15803 https://doi.org/10.7717/peerj.15803
Analysis of technical characteristics of typical lower limb balance movements in Tai Chi: a cross-sectional study based on AnyBody bone muscle modeling
Background Tai Chi is an excellent traditional Chinese physical fitness exercise, and its unique balancing movements are very important for improving human balance. In this study, the two most representative Tai Chi balance movements, “knee lift balance” and “leg stirrup balance”, were selected to establish the lower limb bone muscle model of Tai Chi balance movements by using computer simulation modeling technology, aiming to analyze the characteristics of the lower limb movement mechanisms of typical balance movements, to provide a quantitative theoretical basis for improving the scientific level of Tai Chi. Method A total of 16 subjects were recruited for this study. the BTS three-dimensional motion capture system and three-dimensional force platform were used for motion data acquisition, the physiological electromyographic signals were collected using BTS surface electromyography, and the lower limb bone muscle model of Tai Chi balance movements was established by AnyBody human simulation. Result In the knee lift balancing movement, the balance leg hip abduction/adduction angle, hip flexion/extension moment, and the strength of the rectus femoris muscle, biceps femoris short capitis, and iliacus muscle of the amateur group was significantly smaller than that of the professional group (P < 0.01). In the leg stirrup balance movement, the knee flexion/extension angle of the balancing leg in the amateur group was significantly greater than that in the professional group (P < 0.01), and the hip flexion/extension angle, hip inversion/abduction angle, knee flexion/extension moment, hip flexion/extension moment, the strength iliacus, gluteus maximus, and obturator internus were significantly smaller than those in the professional group (P < 0.01). The integral EMG of the biceps femoris of the support leg in the amateur group was significantly smaller than that of the professional group (P < 0.01). The integral EMG of the lateral femoral muscle of the balance leg was significantly smaller than that of the professional group (P < 0.01). Conclusion In this study, we found that the balancing leg of the balancing movement has a larger hip joint angle, the stirrup balancing knee joint angle is smaller, and the hip and knee joint moments are larger. This is related to joint activity and muscle activation, and amateurs should pay attention to increasing the range of motion of the hip joint and decreasing the range of motion of the knee joint when practicing to better stimulate exercise of the lower limb joints. In addition, the practice of balancing movements should strengthen the iliacus muscle, which plays an important role in maintaining the stable balance of the lower limbs, and strengthen the knee flexor and extensor muscles and hip adductor/abductor muscles of the balancing leg, thus promoting the stability of the balancing leg movements.
Li et al. (2023) Analysis of technical characteristics of typical lower limb balance movements in Tai Chi: a cross-sectional study based on AnyBody bone muscle modeling. PeerJ 11:e15817 https://doi.org/10.7717/peerj.15817
Development of a novel prediction model based on protein structure for identifying RPE65-associated inherited retinal disease (IRDs) of missense variants
Purpose This study aimed to develop a prediction model to classify RPE65-mediated inherited retinal disease (IRDs) based on protein secondary structure and to analyze phenotype-protein structure correlations of RPE65 missense variants in a Chinese cohort. Methods Pathogenic or likely pathogenic missense variants of RPE65 were obtained from UniProt, ClinVar, and HGMD databases. The three-dimensional structure of RPE65 was retrieved from the Protein Data Bank (PDB) and modified with Pymol software. A novel prediction model was developed using LASSO regression and multivariate logistic regression to identify RPE65-associated IRDs. A total of 21 Chinese probands with RPE65 variants were collected to analyze phenotype-protein structure correlations of RPE65 missense variants. Results The study found that both pathogenic and population missense variants were associated with structural features of RPE65. Pathogenic variants were linked to sheet, β-sheet, strands, β-hairpins, Fe2+ (iron center), and active site cavity, while population variants were related to helix, loop, helices, and helix–helix interactions. The novel prediction model showed accuracy and confidence in predicting the disease type of RPE65 variants (AUC = 0.7531). The study identified 25 missense variants in Chinese patients, accounting for 72.4% of total mutations. A significant correlation was observed between clinical characteristics of RPE65-associated IRDs and changes in amino acid type, specifically for missense variants of F8 (H68Y, P419S). Conclusion The study developed a novel prediction model based on the protein structure of RPE65 and investigated phenotype-protein structure correlations of RPE65 missense variants in a Chinese cohort. The findings provide insights into the precise diagnosis of RPE65-mutated IRDs.
Wu et al. (2023) Development of a novel prediction model based on protein structure for identifying RPE65-associated inherited retinal disease (IRDs) of missense variants. PeerJ 11:e15702 https://doi.org/10.7717/peerj.15702
Estimating plant biomass in agroecosystems using a drop-plate meter
Reason for doing the work Plant biomass is a commonly used metric to assess agricultural health and productivity. Removing plant material is the most accurate method to estimate plant biomass, but this approach is time consuming, labor intensive, and destructive. Previous attempts to use indirect methods to estimate plant biomass have been limited in breadth and/or have added complexity in data collection and/or modeling. A cost-effective, quick, accurate, and easy to use and understand approach is desirable for use by scientists and growers. Objectives An indirect method for estimating plant biomass using a drop-plate meter was explored for use in broad array of crop systems. Methods Drop-plate data collected by more than 20 individuals from 16 crop types on 312 farms across 15 states were used to generate models to estimate plant biomass among and within crop types. Results A linear model using data from all crop types explained approximately 67% of the variation in plant biomass overall. This model performed differently among crop types and stand heights, which was owed to differences among sample sizes and farming between annual and perennial systems. Comparatively, the model using the combined dataset explained more variance in biomass than models generated with commodity specific data, with the exception of wheat. Conclusions The drop-plate approach described here was inexpensive, quick, simple, and easy to interpret, and the model generated was robust to error and accurate across multiple crop types. The methods met all expectations for a broad-use approach to estimating plant biomass and are recommended for use across all agroecosystems included in this study. While it may be useful in crops beyond those included, validation is suggested before application.
Robertson et al. (2023) Estimating plant biomass in agroecosystems using a drop-plate meter. PeerJ 11:e15740 https://doi.org/10.7717/peerj.15740
Transcriptomic characterization revealed that METTL7A inhibits melanoma progression via the p53 signaling pathway and immunomodulatory pathway
METTL7A is a protein-coding gene expected to be associated with methylation, and its expression disorder is associated with a range of diseases. However, few research have been carried out to explore the relationship between METTL7A and tumor malignant phenotype as well as the involvement potential mechanism. We conducted our research via a combination of silico analysis and molecular biology techniques to investigate the biological function of METTL7A in the progression of cancer. Gene expression and clinical information were extracted from the TCGA database to explore expression variation and prognostic value of METTL7A. In vitro, CCK8, transwell, wound healing and colony formation assays were conducted to explore the biological functions of METT7A in cancer cell. GSEA was performed to explore the signaling pathway involved in METTL7A and validated via western blotting. In conclusion, METTL7A was downregulated in most cancer tissues and its low expression was associated with shorter overall survival. In melanoma, METTL7A downregulation was associated with poorer clinical staging, lower levels of TIL infiltration, higher IC50 levels of chemotherapeutic agents, and poorer immunotherapy outcomes. QPCR results confirm that METTL7A is down-regulated in melanoma cells. Cell function assays showed that METTL7A knockdown promoted proliferation, invasion, migration and clone formation of melanoma cells. Mechanistic studies showed that METTL7A inhibits tumorigenicity through the p53 signaling pathway. Meanwhile, METTL7A is also a potential immune regulatory factor.
Zhang et al. (2023) Transcriptomic characterization revealed that METTL7A inhibits melanoma progression via the p53 signaling pathway and immunomodulatory pathway. PeerJ 11:e15799 https://doi.org/10.7717/peerj.15799