title: PeerJ description: Articles published in PeerJ link: https://peerj.com/articles/index.rss3?journal=peerj&page=117 creator: info@peerj.com PeerJ errorsTo: info@peerj.com PeerJ language: en title: Optimal control simulations tracking wearable sensor signals provide comparable running gait kinematics to marker-based motion capture link: https://peerj.com/articles/19035 last-modified: 2025-03-06 description: ObjectiveInertial measurement units (IMUs) offer a method for assessing gait beyond the confines of a laboratory. Signal noise and calibration errors pose significant obstacles to accurately estimating joint angles, particularly during dynamic activities such as running. Advancements in dynamic optimisation tools could enable a more comprehensive analysis with fewer sensors and/or low-quality data. The objective of this study was to compare two IMU-based modelling approaches (inverse kinematics and optimal control simulations) with optical marker-based motion capture in reconstructing running gait kinematics.MethodsSix participants performed treadmill running at three speeds whilst marker trajectories and IMU signals were collected concurrently. The subject-specific biomechanical model consisted of a 3D representation of the lower body and torso, with contact spheres added to simulate ground contact in the optimal control simulations. The objective of the optimal control simulations was to track the accelerations, angular velocities, and orientations of eight sensors with simulated signals from the model sensors. Additional constraints were enforced, reflecting physiological and biomechanical principles and targeting dynamic consistency. The objective of the IMU-based inverse kinematics was to minimize the difference between the input and simulated sensor orientations. The joint kinematics derived from both methods were compared against optical marker-based motion capture across a range of running speeds, evaluating the absolute and normalized root mean square errors.ResultsCompared with motion-capture joint angles, optimal control simulations resulted in lower absolute errors (RMSE 8° ± 1) that were consistent across all speeds. IMU-based inverse kinematics exhibited greater differences with motion capture (RMSE 12° ± 1), which was more significant at faster speeds. The largest absolute inaccuracies were observed in the sagittal angles when not normalizing for the joint range of motion. The computational times for the optimal control were 46 ± 60 min, whereas they were 19.3 ± 3.7 s for the IMU-based inverse kinematics.ConclusionsCompared with traditional IMU-based inverse kinematics, the optimal control approach provides a more comparative representation of joint kinematics from optical motion capture. This method can mitigate errors associated with closely tracking IMU noise and drift, and it offers a dynamic analysis that considers the underlying forces and torques producing movement. However, these advantages come at the expense of challenges in parameter selection and computational cost.SignificanceThese findings highlight the potential of using IMUs with optimal control methods to provide a comprehensive understanding of gait dynamics across diverse applications. IMU-based inverse kinematics remains a viable option for faster computation and when model fidelity is less of a concern. creator: Grace McConnochie creator: Aaron S. Fox creator: Clint Bellenger creator: Dominic Thewlis uri: https://doi.org/10.7717/peerj.19035 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2025 McConnochie et al. title: Detection of O25B-ST131 clone and blaCTX-M-15 gene in Escherichia coli isolated from patients with COVID-19 link: https://peerj.com/articles/19011 last-modified: 2025-03-06 description: BackgroundIsolation of blaCTX-M family of extended-spectrum beta-lactamases (ESBL) is a challenge in the field of microbiology in our locality that makes treatment fail and disseminate quickly.ObjectivesTo determine the prevalence of blaCTX-M-15 ESBL gene in Escherichia coli clone O25B-ST131 isolated from COVID-19 patients with different infections.MethodsThis cross-sectional study was conducted on 528 patients hospitalized due to COVID-19 infection with various symptoms from April to September 2021. Using standard culturing techniques, E. coli were isolated from patients’ various samples (urine, catheter tip, sputum, blood, endotracheal tube aspiration, pleural/peritoneal fluids, and throat swab). After the antibiotic susceptibility test, E. coli isolates that were resistant to more than one of the three cephalosporins (cefotaxime, ceftriaxone and ceftazidime) were tested for ESBL production using the double disc synergy test and combined disc test, then confirmed by genotypic detection of blaCTX-M-15 gene among clones of O25B-ST131 E. coli. Finally, it was sequenced and its incision number was received from NCBI.ResultsA total of 234 E. coli isolates were detected from various patients’ samples, and all isolates showed multiple degrees of antibiotic resistance, especially ceftriaxone, ceftazidime, and cefepime. The phenotypic test showed that 63.2% of E. coli isolates were positive for ESBL, of which 58.1% were confirmed by double disc synergy test (DDST) (p = 0.002), 83.8% by combined disc test (CDT1) (p < 0.001) and 60.1% by CDT2 (p < 0.001). However, CDT1 has a better agreement as a phenotypic screening test (72.5% with a kappa value of 0.24) than DDST and CDT2. Most E. coli isolates were positive for the blaCTX-M-15 gene (68.4%), of which 75% were positive for the O25B- ST131 clone.ConclusionsMost E. coli isolates were ESBL producers, held blaCTX-M-15 gene and were positive for the O25B-ST131 clone. creator: Khanda Abdulateef Anwar uri: https://doi.org/10.7717/peerj.19011 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Anwar title: Antibacterial activity of the endophytic fungal extracts and synergistic effects of combinations of ethylenediaminetetraacetic acid (EDTA) against Pseudomonas aeruginosa and Escherichia coli link: https://peerj.com/articles/19074 last-modified: 2025-03-05 description: The growing threat of antibiotic resistance in bacteria is a critical public health concern. Combining natural compounds with antimicrobial agents is an alternative approach to improve the antibacterial efficacy and safety of these agents. The strategy is to restore the effectiveness of existing antibiotics while minimizing the required concentrations of antibiotics or antimicrobial agents. This study aimed to isolate the endophytic fungi from medicinal plants, including Lantana camara, Orthosiphon aristatus, Mansonia gagei, Terminalia bellirica, Oroxylum indicum, Elaeagnus latifolia, Talinum paniculatum, and Capsicum annuum, and evaluate the combined antibacterial efficacy with selected antibiotics or ethylenediaminetetraacetic acid (EDTA) against Pseudomonas aeruginosa. The antimicrobial activity of the extracts was assessed using agar well diffusion and broth microdilution methods. The minimum inhibitory concentration (MIC) values of the extracts were 32–64 µg/mL against Escherichia coli, and 512–2,048 µg/mL against P. aeruginosa, respectively. Time-kill assays demonstrated the bacteriostatic effect of the extracts. The checkerboard microbroth dilution method was performed to determine the synergistic effect between endophytic fungal extracts and antibiotics or EDTA. The synergistic effect was observed in the extractions of endophytic fungi isolated from M. gagei, T. bellirica, O. indicum, E. latifolia, T. paniculatum, and C. annuum combined with EDTA against P. aeruginosa. Combinations of endophytic fungi with EDTA, which exhibited a synergistic effect, demonstrated bactericidal action against Gram-negative bacteria. The present study suggests that combining endophytic fungal extracts and EDTA could be an essential strategy for combating pathogenic Gram-negative bacteria. creator: Sirirak Rosdee creator: Sueptrakool Wisessombat creator: Malatee Tayeh creator: Ramitanun Malakul creator: Teva Phanaksri creator: Wipawadee Sianglum uri: https://doi.org/10.7717/peerj.19074 license: https://creativecommons.org/licenses/by-nc/4.0 rights: © 2025 Rosdee et al. title: Outcomes of metabolic syndrome and anxiety levels in light and heavy smokers link: https://peerj.com/articles/19069 last-modified: 2025-03-05 description: BackgroundThis study aimed to assess the impact of smoking status, as measured by pack-years (PY), on components of metabolic syndrome while considering the influence of anxiety.DesignThis cross-sectional study was conducted at a smoking cessation clinic in Turkey, enrolling individuals who visited the clinic in 2022. The Fagerstrom Test for Nicotine Dependence and the State-Trait Anxiety Inventory were utilized as assessment tools, while metabolic syndrome parameters (body mass index, hypertension, hyperglycemia, dyslipidemia) were evaluated. Smoking status was classified based on pack-years.ResultsThe study revealed a dose-dependent relationship between smoking status and essential metabolic factors such as systolic blood pressure (SBP), diastolic blood pressure (DBP), hemoglobin A1c (HbA1c), and low-density lipoprotein (LDL). Notably, triglyceride (TG) levels exhibited a significant increase, particularly at 25 pack years. While anxiety levels did not exhibit a significant correlation with smoking status, they demonstrated an upward trend with increasing SBP and DBP values. Anxiety levels did not exhibit a significant correlation with smoking status.ConclusionsA significant association was identified between nicotine addiction, as indicated by PY, and both metabolic syndrome parameters and anxiety levels. Early smoking cessation is strongly recommended for current smokers, and former smokers are advised to abstain from smoking to mitigate its adverse effects on metabolic syndrome components. These findings underscore the interconnectedness of cigarette smoking’s effects on both physical and mental health, emphasizing the necessity of comprehensive approaches encompassing both metabolic disorder management and mental health support within cessation programs. creator: Musa Şahin creator: Didem Yüzügüllü uri: https://doi.org/10.7717/peerj.19069 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2025 Şahin and Yüzügüllü title: Mass harvested per trunkload as a constraint to forage consumption by the African savanna elephant (Loxodonta africana) link: https://peerj.com/articles/19033 last-modified: 2025-03-05 description: BackgroundAfrican elephants can convert woodland to shrubland or grassland. Moderate conversion observed at low elephant densities may improve conditions for other animals, while extensive transformation at high densities may reduce plant and animal diversity. The threshold density separating facilitation from habitat destruction varies spatially and is partly determined by food choice, which differs between adult bulls and members of breeding herds. When elephants consume herbaceous forage, woodland damage is low but this increases when woody plants are the primary food source. Consequently, an understanding of diet selection by elephants is important for forecasting the degree of vegetation conversion. One hypothesis is that elephants select forage that provides the highest rate of intake. The mass harvested per trunkload is a constraint to intake and therefore this study sought to determine if trunkload mass changes seasonally; varies across common forage types utilised by elephants; and differs between adult bulls and members of breeding herds.MethodsMechanistic models were used to estimate the mass harvested per trunkload of green grass, mixed green and dry grass, forbs, and leaves and bark from woody plants across a heterogenous, semi-arid savanna at a daily time step for one annual cycle. Separate models were constructed for adult bulls and members of breeding herds.ResultsHarvestable mass changed seasonally for herbaceous forage and for leaves from woody plants but was constant for canopy bark. The maximum average trunkload mass of green grass was >75 times heavier than the bite mass reported for other grazers while trunkloads of leaves from woody plants were only eight times heavier than the bite mass reported for other browsers. This is attributed to the advantage provided by the trunk, which increases harvestable mass beyond the constraint of mouth volume, particularly when feeding on grass. Herbaceous forage yielded heavier trunkloads than leaves and bark from woody plants during the wet season, but this was reversed in the dry season. Adult bulls harvested heavier trunkloads than members of breeding herds for all forage types except forbs; and adult bulls harvested disproportionately large trunkloads of grass and bark.ConclusionThe strong correlation between the model outputs and well-established trends in the seasonal changes in elephants’ diet suggests that elephants are preferential foragers of the largest trunkload on offer. Consequently, they are grazers when suitable herbaceous forage is available, and browsers when it is scarce. Green grass provides adult bulls with disproportionately large trunkloads and, therefore, adult bulls are predicted to have a strong preference for green grass. Availability of suitable green grass during the dry season may therefore buffer woodlands from heavy impact by adult bulls. Consequently, where possible, protected areas with elephants should aim to include key grass resources. creator: Bruce W. Clegg creator: Timothy G. O’Connor uri: https://doi.org/10.7717/peerj.19033 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Clegg and O’Connor title: Characteristics of the retinal and choroidal thicknesses in myopic young adult males using swept-source optical coherence tomography link: https://peerj.com/articles/19030 last-modified: 2025-03-05 description: BackgroundChanges in retinal and choroidal structures are key biomarkers for predicting, diagnosing, and monitoring various ocular conditions, including myopia.ObjectiveTo assess the characteristics of the retinal and choroidal thicknesses in myopic young adult males using swept-source optical coherence tomography (SSOCT).MethodsThis cross-sectional comparative study included 198 young adults with a mean age of 21.87 ± 1.69 years, only male subjects were recruited for this study, comprising 102 diagnosed with myopia and 96 with emmetropia. Refraction was assessed using an autorefractometer, and comprehensive SSOCT scans were conducted to measure the thickness of the retina and choroid at nine predefined locations. Data analysis focused on identifying significant patterns and correlations between myopia and retinal and choroidal thickness.ResultsMyopic subjects with a mean of −2.66 ± 1.59D exhibited significantly decreased retinal thickness compared to emmetropic with a mean of 0.18 ± 0.39D, (p < 0.01). Similarly, their choroidal thickness was also significantly thinner (p < 0.01). The findings showed a weak but statistically significant inverse correlation between retinal thickness and the spherical equivalent of myopia (r = −0.257, p < 0.01). Correspondingly, a stronger inverse correlation was observed between choroidal thickness and the spherical equivalent of myopia (r = −0.306, p < 0.01). Choroidal thickness in all studied areas showed an inverse correlation with the degree of myopia (p < 0.05), except in the superior outer region, where the association was not statistically significant (p = 0.056).ConclusionThe study identified significant differences in the retinal and choroidal structures between myopic and emmetropic individuals. The use of SSOCT effectively detected these morphological changes in myopic young adults, offering valuable insights into myopia’s pathophysiology and potentially guiding targeted therapeutic strategies for myopia control. creator: Saif Hassan Alrasheed creator: Yazan Gammoh uri: https://doi.org/10.7717/peerj.19030 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2025 Alrasheed and Gammoh title: Soft anatomy and morphological variation in Daptomys peruviensis (Rodentia, Cricetidae), a rare ichthyomyine from the northwestern Amazonian forests link: https://peerj.com/articles/18997 last-modified: 2025-03-05 description: The recently resurrected genus Daptomys Anthony, 1929 includes poorly known small cricetid rodents that are widely distributed in tropical South America. Along with Neusticomys Anthony, 1921, these species are the most terrestrial members of the tribe, which is otherwise distinguished by adaptations that allow species to live in both aquatic and terrestrial environments. Newly collected Ecuadorean specimens provide complementary information of the craniodental and soft anatomy of Daptomys, focusing on rhinarium morphology, soft palate, stomach, caecum configuration, and other features. In addition, the phylogeny presented here, combined with species distribution models, suggests a simplified taxonomy indicating that Daptomys peruviensis (Musser & Gardner, 1974) has a wide distribution extending from Venezuela to Peru. In this novel scenario, Daptomys mussoi (Ochoa & Soriano, 1991) would be a junior synonym of D. peruviensis, and the application of a trinominal taxonomy appears premature. creator: Jorge Brito creator: Mateo A. Vega-Yánez creator: Jhandry P. Guaya-Ramos creator: Melanie Polo creator: Claudia Koch creator: Nicolás Tinoco creator: Ulyses F.J. Pardiñas uri: https://doi.org/10.7717/peerj.18997 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Brito et al. title: The extended impact of the COVID-19 pandemic on medical imaging case volumes: a retrospective study link: https://peerj.com/articles/18987 last-modified: 2025-03-05 description: ObjectiveThis study aims to investigate the long-term effects of the COVID-19 pandemic on medical imaging case volumes.MethodsThis retrospective study analyzed data from the Integrated Radiology Information System-Picture Archive and Communication System (RIS-PACS), including monthly medical imaging case volumes at a public hospital, spanning from January 2019 to December 2022. The study collected data on medical imaging examinations, comparing the pre COVID-19 period, which acted as a control group, with the periods following COVID-19, which were designated as cohort groups.ResultsThe total number of medical imaging procedures performed (n = 597,645) was found significantly different (F = 6.69, P < 0.001) between 2019 and 2022. Specifically, the bone mineral density/computed radiography (BMD/CR) modality experienced a significant decrease (P = 0.01) of the procedures performed in 2020 and 2021 compared to 2019. Conversely, the nuclear medicine/computed tomography (NM/CT) and computed tomography (CT) modalities demonstrated a significant increase of the procedures performed in 2021 (P = 0.04) and (P < 0.0001), respectively, and in 2022 (P = 0.0095) and (P < 0.0001), respectively, compared to the pre-pandemic year. The digital X-ray modality (DX) showed the highest volume (67.63%) of the performed procedures overall between 2019 and 2022. Meanwhile, magnetic resonance imaging (MR) and ultrasound (US) modalities experienced a slight drop in the number of procedures in 2020—4.47% for MR and 1.00% for US, which subsequently recovered by 22.15% and 19.74% in 2021, and 24.36% and 17.40% in 2022, respectively, compared to 2019.ConclusionThe COVID-19 pandemic initially led to a drop in the number of medical imaging procedures performed in 2020, with the most noticeable drop occurring during the early waves of the pandemic. However, this trend revealed a gradual recovery in the subsequent years, 2021 and 2022, as healthcare systems adapted, and pandemic-related restrictions were modified. creator: Fahad H. Alhazmi creator: Faisal A. Alrehily creator: Walaa Alsharif creator: Moawia Gameraddin creator: Kamal D. Alsultan creator: Hassan Ibrahim Alsaedi creator: Khalid M. Aloufi creator: Sultan Abdulwadoud Alshoabi creator: Osamah M. Abdulaal creator: Abdulaziz A. Qurashi uri: https://doi.org/10.7717/peerj.18987 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Alhazmi et al. title: Determining population structure from k-mer frequencies link: https://peerj.com/articles/18939 last-modified: 2025-03-05 description: BackgroundUnderstanding population structure within species provides information on connections among different populations and how they evolve over time. This knowledge is important for studies ranging from evolutionary biology to large-scale variant-trait association studies. Current approaches to determining population structure include model-based approaches, statistical approaches, and distance-based ancestry inference approaches.MethodsIn this work, we identify population structure from DNA sequence data using an alignment-free approach. We use the frequencies of short DNA substrings from across the genome (k-mers) with principal component analysis (PCA). K-mer frequencies can be viewed as a summary statistic of a genome and have the advantage of being easily derived from a genome by counting the number of times a k-mer occurred in a sequence. In contrast, most population structure work employing PCA uses multi-locus genotype data (SNPs, microsatellites, or haplotypes). No genetic assumptions must be met to generate k-mers, whereas current population structure approaches often depend on several genetic assumptions and can require careful selection of ancestry informative markers to identify populations. We compare our k-mer based approach to population structure estimated using SNPs with both empirical and simulated data.ResultsIn this work, we show that PCA is able to determine population structure just from the frequency of k-mers found in the genome. The application of PCA and a clustering algorithm to k-mer profiles of genomes provides an easy approach to detecting the number and composition of populations (clusters) present in the dataset. Using simulations, we show that results are at least comparable to population structure estimates using SNPs. When using human genomes from populations identified by the 1000 Genomes Project, the results are better than population structure estimates using SNPs from the same samples, and comparable to those found by a model-based approach using genetic markers from larger numbers of samples.ConclusionsThis study shows that PCA, together with the clustering algorithm, is able to detect population structure from k-mer frequencies and can separate samples of admixed and non-admixed origin. Using k-mer frequencies to determine population structure has the potential to avoid some challenges of existing methods and may even improve on estimates from small samples. creator: Yana Hrytsenko creator: Noah M. Daniels creator: Rachel S. Schwartz uri: https://doi.org/10.7717/peerj.18939 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Hrytsenko et al. title: Identifying leptospirosis hotspots in Selangor: uncovering climatic connections using remote sensing and developing a predictive model link: https://peerj.com/articles/18851 last-modified: 2025-03-05 description: BackgroundLeptospirosis is an endemic disease in countries with tropical climates such as South America, Southern Asia, and Southeast Asia. There has been an increase in leptospirosis incidence in Malaysia from 1.45 to 25.94 cases per 100,000 population between 2005 and 2014. With increasing incidence in Selangor, Malaysia, and frequent climate change dynamics, a study on the disease hotspot areas and their association with the hydroclimatic factors could enhance disease surveillance and public health interventions.MethodsThis ecological cross-sectional study utilised a geographic information system (GIS) and remote sensing techniques to analyse the spatiotemporal distribution of leptospirosis in Selangor from 2011 to 2019. Laboratory-confirmed leptospirosis cases (n = 1,045) were obtained from the Selangor State Health Department. Using ArcGIS Pro, spatial autocorrelation analysis (Moran’s I) and Getis-Ord Gi* (hotspot analysis) was conducted to identify hotspots based on the monthly aggregated cases for each subdistrict. Satellite-derived rainfall and land surface temperature (LST) data were acquired from NASA’s Giovanni EarthData website and processed into monthly averages. These data were integrated into ArcGIS Pro as thematic layers. Machine learning algorithms, including support vector machine (SVM), Random Forest (RF), and light gradient boosting machine (LGBM) were employed to develop predictive models for leptospirosis hotspot areas. Model performance was then evaluated using cross-validation and metrics such as accuracy, precision, sensitivity, and F1-score.ResultsMoran’s I analysis revealed a primarily random distribution of cases across Selangor, with only 20 out of 103 observed having a clustered distribution. Meanwhile, hotspot areas were mainly scattered in subdistricts throughout Selangor with clustering in the central region. Machine learning analysis revealed that the LGBM algorithm had the best performance scores compared to having a cross-validation score of 0.61, a precision score of 0.16, and an F1-score of 0.23. The feature importance score indicated river water level and rainfall contributes most to the model.ConclusionsThis GIS-based study identified a primarily sporadic occurrence of leptospirosis in Selangor with minimal spatial clustering. The LGBM algorithm effectively predicted leptospirosis hotspots based on the analysed hydroclimatic factors. The integration of GIS and machine learning offers a promising framework for disease surveillance, facilitating targeted public health interventions in areas at high risk for leptospirosis. creator: Muhammad Akram Ab Kadir creator: Rosliza Abdul Manaf creator: Siti Aisah Mokhtar creator: Luthffi Idzhar Ismail uri: https://doi.org/10.7717/peerj.18851 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Ab Kadir et al.