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.
Background: Understanding 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.
Methods: In 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.
Results: In 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.
Conclusions: This 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.
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.
Background: Leptospirosis 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.
Methods: This 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.
Results: Moran'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.
Conclusions: This 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.
Background: This 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.
Design: This 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.
Results: The 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.
Conclusions: A 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.
Background: EDTA-dependent pseudothrombocytopenia (EDTA-PTCP) is an in vitro phenomenon that may lead to expensive, time-consuming, and invasive diagnostic procedures as well as unnecessary patient treatment. The purpose of this study was to explore the effects of time, anticoagulant and detection channel on the platelet (PLT) count of EDTA-PTCP samples, and to suggest a better method for correcting spurious low PLT counts.
Methods: In this study, 43 identified EDTA-PTCP samples were collected. The Sysmex XN-9100, Mindray BC-6900 and Mindray BC-5390 haematology analysers were used to test these EDTA-PTCP samples on the following detection channels at different time points: PLT count by impedance method (PLT-I), PLT count by optical method (PLT-O) and PLT count by fluorescent staining (PLT-F).
Results: EDTA-PTCP was time-dependent and small PLT agglutination occurred in most of the corresponding citrate-treated samples. Our results further demonstrated that the detection channel significantly affected the PLT count of the EDTA-PTCP samples. The XN-9100 PLT-F channel exhibited a greater dissociative effect than the XN-9100 PLT-I and PLT-O channels. Moreover, blood samples processed in the PLT-O channel of the Mindray hematology analyzer showed the highest PLT count in EDTA-K2 tubes compared to the other detection channels.
Conclusion: Our data showed that time, anticoagulant and detection channel significantly affected the PLT count in the EDTA-PTCP samples. For the EDTA-PTCP samples, the simplest retest method was to use the PLT-O channel of the Mindray automatic blood analyser within 30 min. In addition, changing the sodium citrate anticoagulant and using the XN-9100 PLT-F channel within 15 min were also suitable for correcting the spurious low PLT of the EDTA-PTCP samples.
While it is established that complement receptor molecules on the surface of erythrocytes are crucial for the clearance of immune complexes in the body, the molecular mechanisms underlying the interaction between macrophages and erythrocytes in pigs remain inadequately understood. Consequently, we built a detection system with a closed-circulation flow chamber and a constant flow pump. Additionally, we optimized parameters including system flow velocity and fluid shear force. In the circulatory system, our study measured the fluorescence intensity of erythrocyte and pulmonary alveolar macrophages (PAMs) surfaces before and after the blockade of complement receptor 1 (CR1)-like receptors and Fc receptors. The results indicated that porcine erythrocytes and PAMs exhibited a diminished rate of change in fluorescence intensity under the blocked condition. Through transmission electron microscopy, it was observed that PAMs effectively removed sensitized GFP-E. coli adhering immunologically to porcine erythrocytes. The findings indicate that PAMs effectively removed sensitized GFP-E. coli from the surface immunoadhesion of porcine erythrocytes, facilitated by the mediation of surface CR1-like receptors and Fc receptors.
Background: Amino acids, as the main flavor substances of umami in tea, are also the primary components determining the taste of tea, which is positively correlated with the quality and grade of tea. The Guizhou Plateau is located in the core area of the origin of the tea plant and has abundant tea germplasm. However, there are relatively few studies using genome-wide association studies (GWAS) to mine genes related to amino acid content in tea plants in the Guizhou Plateau.
Results: In this study, 78,819 high-quality single nucleotide polymorphisms (SNPs) markers were identified from 212 tea accessions composed by our group in the previous study by genotyping sequencing technology (GBS), and the population structure, genetic diversity, and GWAS of 212 tea accessions resources of tea were analysed. Phylogenetic tree and population structure analysis divided all germplasm into four inferred groups (Q1, Q2, Q3, Q4). By analysing the eight SNPs associated with amino acids obtained by GWAS, four candidate genes that may be related to amino acids were identified. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was used to verify the expression levels of four candidate genes, suggesting that there may be a potential gene that is important for the accumulation of amino acid content.
Conclusions: This study provides new information for the in-depth analysis of the genetic mechanism of amino acid content in tea plants and provides important genetic resources for accelerating the cultivation of new tea varieties with suitable amino acid content.
Background: Venous thromboembolism is a significant complication after knee replacement. The short-term efficacy disparities between different types of graduated elastic compression stockings (GCS) among patients undergoing total/unicompartmental knee replacement remain unclear.
Objective: The aim of the trial was to compare the efficacies on hemodynamics and morphology of femoral vein between two types of GCS, providing more evidence on GCS prophylaxis among patients undergoing total/unicompartmental knee replacement.
Methods: In this single center, double-blind, parallel design, randomized trial, 141 adult patients who underwent selective, unilateral total/unicompartmental knee replacement operation for the first time were enrolled, with 71 were assigned to type A GCS and 70 to type B GCS, respectively. Compressed ultrasound of the lower extremity was conducted before the operation (without GCS, as preoperative baseline) and within 24 hours post operation (postoperative baseline , with GCS, and with GCS + ankle pump). The relative changes in TV and PV, as well as the diameter of the femoral vein in the healthy leg, were assessed both before and after GCS application following the knee replacement surgery.
Results: The median ages were 67.0 years in type A group and 68.0 years in type B group. All parameters of femoral vein were comparable between type A and type B GCSs. Compared with postoperative baseline, GCS + ankle pump significantly reduced femoral vein diameter and improved the TV in both GCS types; GCS and GCS + ankle pump also significantly increased the TV (median 1.2%, IQR -21.4% to 58.6%, P = 0.0384; median 14.0%, IQR -24.3% to 93.0%, P = 0.0019, respectively) in left leg, while not significant in right leg.
Conclusion: The efficacies of two GCSs were comparable, and both were effective in improving velocity and morphology of femoral veins of the healthy legs among patients undergoing knee replacement, especially in improving TVs of femoral veins for left leg.
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：