Using linear measurements to diagnose the ecological habitat of Spinosaurus
Much of the ecological discourse surrounding the polarising theropod Spinosaurus has centred on qualitative discussions. Using a quantitative multivariate data analytical approach on size-adjusted linear measurements of the skull, we examine patterns in skull shape across a range of sauropsid clades and three ecological realms (terrestrial, semi-aquatic, and aquatic). We utilise cluster analyses to identify emergent properties of the data which associate properties of skull shape with ecological realm occupancy. Results revealed terrestrial ecologies to be significantly distinct from both semi- and fully aquatic ecologies, the latter two were not significantly different. Spinosaurids (including Spinosaurus) plotted away from theropods in morphospace and close to both marine taxa and wading birds. The position of nares and the degree of rostral elongation had the greatest effect on categorisation. Comparisons of supervised (k-means) and unsupervised clustering demonstrated categorising taxa into three groups (ecological realms) was inappropriate and suggested instead that cluster division is based on morphological adaptations to feeding on aquatic versus terrestrial food items. The relative position of the nares in longirostrine taxa is associated with which skull bones are elongated. Rostral elongation is observed by either elongating the maxilla and the premaxilla or by elongating the maxilla only. This results in the nares positioned towards the orbits or towards the anterior end of the rostrum respectively, with implications on available feeding methods. Spinosaurids, especially Spinosaurus, show elongation in the maxilla-premaxilla complex, achieving similar functional outcomes to elongation of the premaxilla seen in birds, particularly large-bodied piscivorous taxa. Such a skull construction would bolster “stand-and-wait” predation of aquatic prey to a greater extent than serving other proposed feeding methods.
Smart et al. (2024) Using linear measurements to diagnose the ecological habitat of Spinosaurus. PeerJ 12:e17544 https://doi.org/10.7717/peerj.17544
Integrative systematic revision of the Montseny brook newt (Calotriton arnoldi), with the description of a new subspecies
The Montseny brook newt (Calotriton arnoldi), a glacial relict endemic to a small, isolated massif in northeast Spain, is considered the only Critically Endangered urodele in Europe. Its restricted range is divided by a deep valley that acts as an impassable barrier to dispersal, separating two isolated metapopulations (Western and Eastern) that correspond to independent lineages with different evolutionary trajectories, based on genetic and genomic data. Here, we address the ecological differentiation between lineages and discuss its potential effect on the phenotypic distinctness of each lineage. Based on multiple lines of evidence, we formally describe the Western Montseny brook newt as a new subspecies: Calotriton arnoldi laietanus ssp. nov. Finally, our study underscores the importance of considering taxonomic progress in the conservation policies of endangered species, ensuring appropriate management and protection of the newly described taxa.
Talavera et al. (2024) Integrative systematic revision of the Montseny brook newt (Calotriton arnoldi), with the description of a new subspecies. PeerJ 12:e17550 https://doi.org/10.7717/peerj.17550
When and where? Day-night alterations in wild boar space use captured by a generalized additive mixed model
Wild boar (Sus scrofa), an abundant species across Europe, is often subjected to management in agro-ecosystems in order to control population size, or to scare them away from agricultural fields to safeguard crop yields. Wild boar management can benefit from a better understanding on changes in its space use across the diel cycle (i.e., diel space use) in relation to variable hunting pressures or other factors. Here, we estimate wild boar diel space use in an agro-ecosystem in central Belgium during four consecutive “growing seasons” (i.e., April–September). To achieve this, we fit generalized additive mixed models (GAMMs) to camera trap data of wild boar aggregated over 1-h periods. Our results reveal that wild boar are predominantly nocturnal in all of the hunting management zones in Meerdaal, with activity peaks around sunrise and sunset. Hunting events in our study area tend to take place around sunrise and sunset, while non-lethal human activities occur during sunlight hours. Our GAMM reveals that wild boar use different areas throughout the diel cycle. During the day, wild boar utilized areas in the centre of the forest, possibly to avoid human activities during daytime. During the night, they foraged near (or in) agricultural fields. A post hoc comparison of space use maps of wild boar in Meerdaal revealed that their diurnal and nocturnal space use were uncorrelated. We did not find sufficient evidence to prove that wild boar spatiotemporally avoid hunters. Finally, our work reveals the potential of GAMMs to model variation in space across 24-h periods from camera trap data, an application that will be useful to address a range of ecological questions. However, to test the robustness of this approach we advise that it should be compared against telemetry-based methods to derive diel space use.
Bollen et al. (2024) When and where? Day-night alterations in wild boar space use captured by a generalized additive mixed model. PeerJ 12:e17390 https://doi.org/10.7717/peerj.17390
Altered vaginal cervical microbiota diversity contributes to HPV-induced cervical cancer via inflammation regulation
Background Cancer has surpassed infectious diseases and heart ailments, taking the top spot in the disease hierarchy. Cervical cancer is a significant concern for women due to high incidence and mortality rates, linked to the human papillomavirus (HPV). HPV infection leads to precancerous lesions progressing to cervical cancer. The cervix’s external os, near the vagina, hosts various microorganisms. Evidence points to the link between vaginal microbiota and HPV-induced cervical cancer. Cervical cancer onset aligns with an imbalanced Th1/Th2 immune response, but the role of vaginal microbiota in modulating this imbalance is unclear. Methods In this study, we collected vaginal samples from 99 HPV-infected patients across varying degrees of lesions, alongside control groups. These samples underwent bacterial DNA sequencing. Additionally, we employed Elisa kits to quantify the protein expression levels of Th1/Th2 cytokines IL2, IL12, IL5, IL13, and TNFa within the centrifuged supernatant of vaginal-cervical secretions from diverse research subjects. Subsequently, correlation analyses were conducted between inflammatory factors and vaginal microbiota. Results Our findings highlighted a correlation between decreased Lactobacillus and increased Gardenerella presence with HPV-induced cervical cancer. Functionally, our predictive analysis revealed the predominant enrichment of the ABC transporter within the vaginal microbiota of cervical cancer patients. Notably, these microbiota alterations exhibited correlations with the production of Th1/Th2 cytokines, which are intimately tied to tumor immunity. Conclusions This study suggests the potential involvement of vaginal microbiota in the progression of HPV-induced cervical cancer through Th1/Th2 cytokine regulation. This novel insight offers a fresh perspective for early cervical cancer diagnosis and future prevention strategies.
Yang et al. (2024) Altered vaginal cervical microbiota diversity contributes to HPV-induced cervical cancer via inflammation regulation. PeerJ 12:e17415 https://doi.org/10.7717/peerj.17415
Use of machine learning to identify protective factors for death from COVID-19 in the ICU: a retrospective study
Background Patients in serious condition due to COVID-19 often require special care in intensive care units (ICUs). This disease has affected over 758 million people and resulted in 6.8 million deaths worldwide. Additionally, the progression of the disease may vary from individual to individual, that is, it is essential to identify the clinical parameters that indicate a good prognosis for the patient. Machine learning (ML) algorithms have been used for analyzing complex medical data and identifying prognostic indicators. However, there is still an urgent need for a model to elucidate the predictors related to patient outcomes. Therefore, this research aimed to verify, through ML, the variables involved in the discharge of patients admitted to the ICU due to COVID-19. Methods In this study, 126 variables were collected with information on demography, hospital length stay and outcome, chronic diseases and tumors, comorbidities and risk factors, complications and adverse events, health care, and vital indicators of patients admitted to an ICU in southern Brazil. These variables were filtered and then selected by a ML algorithm known as decision trees to identify the optimal set of variables for predicting patient discharge using logistic regression. Finally, a confusion matrix was performed to evaluate the model’s performance for the selected variables. Results Of the 532 patients evaluated, 180 were discharged: female (16.92%), with a central venous catheter (23.68%), with a bladder catheter (26.13%), and with an average of 8.46- and 23.65-days using bladder catheter and submitted to mechanical ventilation, respectively. In addition, the chances of discharge increase by 14% for each additional day in the hospital, by 136% for female patients, 716% when there is no bladder catheter, and 737% when no central venous catheter is used. However, the chances of discharge decrease by 3% for each additional year of age and by 9% for each other day of mechanical ventilation. The performance of the training data presented a balanced accuracy of 0.81, sensitivity of 0.74, specificity of 0.88, and the kappa value was 0.64. The test performance had a balanced accuracy of 0.85, sensitivity 0.75, specificity 0.95, and kappa value of 0.73. The McNemar test found that there were no significant differences in the error rates in the training and test data, suggesting good classification. This work showed that female, the absence of a central venous catheter and bladder catheter, shorter mechanical ventilation, and bladder catheter duration were associated with a greater chance of hospital discharge. These results may help develop measures that lead to a good prognosis for the patient.
Dos Santos et al. (2024) Use of machine learning to identify protective factors for death from COVID-19 in the ICU: a retrospective study. PeerJ 12:e17428 https://doi.org/10.7717/peerj.17428
Tick hazard in the South Downs National Park (UK): species, distribution, key locations for future interventions, site density, habitats
Background South Downs National Park (SDNP) is UK’s most visited National Park, and a focus of tick-borne Lyme disease. The first presumed UK autochthonous cases of tick-borne encephalitis and babesiosis were recorded in 2019–20. SDNP aims to conserve wildlife and encourage recreation, so interventions are needed that reduce hazard without negatively affecting ecosystem health. To be successful these require knowledge of site hazards. Methods British Deer Society members submitted ticks removed from deer. Key potential intervention sites were selected and six 50 m2 transects drag-sampled per site (mostly twice yearly for 2 years). Ticks were identified in-lab (sex, life stage, species), hazard measured as tick presence, density of ticks (all life stages, DOT), and density of nymphs (DON). Sites and habitat types were analysed for association with hazard. Distribution was mapped by combining our results with records from five other sources. Results A total of 87 Ixodes ricinus (all but one adults, 82% F) were removed from 14 deer (10 Dama dama; three Capreolus capreolus; one not recorded; tick burden, 1–35) at 12 locations (commonly woodland). Five key potential intervention sites were identified and drag-sampled 2015–16, collecting 623 ticks (238 on-transects): 53.8% nymphs, 42.5% larvae, 3.7% adults (13 M, 10 F). Ticks were present on-transects at all sites: I. ricinus at three (The Mens (TM); Queen Elizabeth Country Park (QECP); Cowdray Estate (CE)), Haemaphysalis punctata at two (Seven Sisters Country Park (SSCP); Ditchling Beacon Nature Reserve (DBNR)). TM had the highest DOT at 30/300 m2 (DON = 30/300 m2), followed by QECP 22/300 m2 (12/300 m2), CE 8/300 m2 (6/300 m2), and SSCP 1/300 m2 (1/300 m2). For I. ricinus, nymphs predominated in spring, larvae in the second half of summer and early autumn. The overall ranking of site hazard held for DON and DOT from both seasonal sampling periods. DBNR was sampled 2016 only (one adult H. punctata collected). Woodland had significantly greater hazard than downland, but ticks were present at all downland sites. I. ricinus has been identified in 33/37 of SDNPs 10 km2 grid squares, Ixodes hexagonus 10/37, H. punctata 7/37, Dermacentor reticulatus 1/37. Conclusions Mapping shows tick hazard broadly distributed across SDNP. I. ricinus was most common, but H. punctata’s seeming range expansion is concerning. Recommendations: management of small heavily visited high hazard plots (QECP); post-visit precaution signage (all sites); repellent impregnated clothing for deerstalkers; flock trials to control H. punctata (SSCP, DBNR). Further research at TM may contribute to knowledge on ecological dynamics underlying infection density and predator re-introduction/protection as public health interventions. Ecological research on H. punctata would aid control. SDNP Authority is ideally placed to link and champion policies to reduce hazard, whilst avoiding or reducing conflict between public health and ecosystem health.
Middleton et al. (2024) Tick hazard in the South Downs National Park (UK): species, distribution, key locations for future interventions, site density, habitats. PeerJ 12:e17483 https://doi.org/10.7717/peerj.17483
Effects of wind speed and wind direction on crop yield forecasting using dynamic time warping and an ensembled learning model
The cultivation of cashew crops carries numerous economic advantages, and countries worldwide that produce this crop face a high demand. The effects of wind speed and wind direction on crop yield prediction using proficient deep learning algorithms are less emphasized or researched. We propose a combination of advanced deep learning techniques, specifically focusing on long short-term memory (LSTM) and random forest models. We intend to enhance this ensemble model using dynamic time warping (DTW) to assess the spatiotemporal data (wind speed and wind direction) similarities within Jaman North, Jaman South, and Wenchi with their respective production yield. In the Bono region of Ghana, these three areas are crucial for cashew production. The LSTM-DTW-RF model with wind speed and wind direction achieved an R2 score of 0.847 and the LSTM-RF model without these two key features R2 score of (0.74). Both models were evaluated using the augmented Dickey-Fuller (ADF) test, which is commonly used in time series analysis to assess stationarity, where the LSTM-DTW-RF achieved a 90% level of confidence, while LSTM-RF attained an 87.99% level. Among the three municipalities, Jaman South had the highest evaluation scores for the model, with an RMSE of 0.883, an R2 of 0.835, and an MBE of 0.212 when comparing actual and predicted values for Wenchi. In terms of the annual average wind direction, Jaman North recorded (270.5 SW°), Jaman South recorded (274.8 SW°), and Wenchi recorded (272.6 SW°). The DTW similarity distance for the annual average wind speed across these regions fell within specific ranges: Jaman North (±25.72), Jaman South (±25.89), and Wenchi (±26.04). Following the DTW similarity evaluation, Jaman North demonstrated superior performance in wind speed, while Wenchi excelled in wind direction. This underscores the potential efficiency of DTW when incorporated into the analysis of environmental factors affecting crop yields, given its invariant nature. The results obtained can guide further exploration of DTW variations in combination with other machine learning models to predict higher cashew yields. Additionally, these findings emphasize the significance of wind speed and direction in vertical farming, contributing to informed decisions for sustainable agricultural growth and development.
Bediako-Kyeremeh et al. (2024) Effects of wind speed and wind direction on crop yield forecasting using dynamic time warping and an ensembled learning model. PeerJ 12:e16538 https://doi.org/10.7717/peerj.16538
Preeclampsia in pregnant women with COVID-19: a prospective cohort study from two tertiary hospitals in Southern Brazil
Background COVID-19 is an infectious pathology that shows vascular changes during pregnancy, as well as in the placentas. The main objectives of this study were to estimate the prevalence and the risk factors for preeclampsia in hospitalized pregnant women with COVID-19. As well as comparing maternal and perinatal outcomes in hospitalized pregnant women with COVID-19 and preeclampsia with those without preeclampsia. Methods Prospective cohort study of 100 hospitalized pregnant women from two tertiary hospitals, diagnosed with COVID-19, and divided into two groups: PE+ group (pregnant women with COVID-19 and preeclampsia) and PE- group (pregnant women with COVID-19 without preeclampsia). These pregnant women had prevalence, risk factors, maternal and perinatal data analyzed. Results The prevalence of preeclampsia was 11%. Severe COVID-19 was the main risk factor for preeclampsia (OR = 8.18 [CI 1.53–43.52]), as well as fetal growth restriction was the main perinatal outcome (OR = 8.90 [CI 1.52–38.4]). Comorbidities were more frequent in the PE+ group (63.6% vs 31.5%, p = 0.03), as well as prematurity (81.8% vs 41.6%, p = 0.02), low birth weight (63.6% vs 24.7%, p = 0.01), and the need for neonatal intensive care admission of the newborn (63.6% vs 27.0%, p = 0.03). Pregnant women with PE had twice as long a length of stay in the intensive care unit (RR = 2.35 [CI 1.34–4.14]). Although maternal mortality was more frequent among pregnant women with PE, it was not statistically significant. Conclusions Prevalence of preeclampsia in hospitalized pregnant women with COVID-19 was 11%. Severe COVID-19 was the main risk factor for preeclampsia and associated comorbidities increased the risk for developing preeclampsia. Long length of stay in the intensive care unit was the main maternal outcome and fetal growth restriction was the main perinatal outcome of preeclampsia.
Sobieray et al. (2024) Preeclampsia in pregnant women with COVID-19: a prospective cohort study from two tertiary hospitals in Southern Brazil. PeerJ 12:e17481 https://doi.org/10.7717/peerj.17481
Using bioluminescence as a tool for studying diversity in marine zooplankton and dinoflagellates: an initial assessment
Bioluminescence is light chemically produced by an organism. It is widespread across all major marine phyla and has evolved multiple times, resulting in a high diversity of spectral properties and first flash kinetic parameters (FFKP). The bioluminescence of a system is often a good proxy for planktonic biomass. The species-specific parameters of bioluminescent displays can be measured to identify species in situ and describe planktonic biodiversity. Most bioluminescent organisms will flash when mechanically stimulated i.e., when subjected to supra-threshold levels of shear stress. Here we compare first flash kinetic parameters such as flash duration, peak intensity, rise time, decay time, first-flash mechanically stimulated light and e-folding time obtained with the commercially available Underwater Bioluminescence Assessment Tool (UBAT). We provide descriptions of the first flash kinetic parameters of several species of dinoflagellates Pyrocystis fusiformis, Pyrocystis noctiluca, Pyrodinium bahamense, Lingulodinium polyedra, Alexandrium monilatum and two zooplankton (the ctenophore Mnemiopsis leidyi and the larvacean Oikopleura sp.). FFKPs are then compared and discussed using non-parametric analyses of variance (ANOVAs), hierarchical clustering and a linear discriminant analysis to assess the ability to use bioluminescence signatures for identification. Once the first flash kinetic parameters of a bioluminescent species have been described, it is possible to detect its presence using emissions collected by in situ bathyphotometers. Assessing abundance and diversity of bioluminescent species may therefore be possible.
Letendre et al. (2024) Using bioluminescence as a tool for studying diversity in marine zooplankton and dinoflagellates: an initial assessment. PeerJ 12:e17516 https://doi.org/10.7717/peerj.17516
Stress adaptive plasticity from Aegilops tauschii introgression lines improves drought and heat stress tolerance in bread wheat (Triticum aestivum L.)
Aegilops tauchii is a D-genome donor of hexaploid wheat and is a potential source of genes for various biotic and abiotic stresses including heat and drought. In the present study, we used multi-stage evaluation technique to understand the effects of heat and drought stresses on Ae. tauschii derived introgression lines (ILs). Preliminary evaluation (during stage-I) of 369 ILs for various agronomic traits identified 59 agronomically superior ILs. In the second stage (stage-II), selected ILs (i.e., 59 ILs) were evaluated for seedling heat (at 30 °C and 35 °C) and drought (at 20% poly-ethylene glycol; PEG) stress tolerance under growth chambers (stage-II). Heat and drought stress significantly reduced the seedling vigour by 59.29 and 60.37 percent, respectively. Genotype × treatment interaction analysis for seedling vigour stress tolerance index (STI) identified IL-50, IL-56, and IL-68 as high-performing ILs under heat stress and IL-42 and IL-44 as high-performing ILs under drought stress. It also revealed IL-44 and IL-50 as the stable ILs under heat and drought stresses. Furthermore, in the third stage (stage-III), selected ILs were evaluated for heat and drought stress tolerance under field condition over two cropping seasons (viz., 2020–21 and 2021–22), which significantly reduced the grain yield by 72.79 and 48.70 percent, respectively. Stability analysis was performed to identify IL-47, IL-51, and IL-259 as the most stable ILs in stage-III. Tolerant ILs with specific and wider adaptability identified in this study can serve as the potential resources to understand the genetic basis of heat and drought stress tolerance in wheat and they can also be utilized in developing high-yielding wheat cultivars with enhanced heat and drought stress tolerance.
Gudi et al. (2024) Stress adaptive plasticity from Aegilops tauschii introgression lines improves drought and heat stress tolerance in bread wheat (Triticum aestivum L.). PeerJ 12:e17528 https://doi.org/10.7717/peerj.17528