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First evidence of Limoniidae (Diptera: Nematocera) in French amber from Oise
Abstract This paper describes three new species found as inclusions in Early Eocene amber from Oise (northern France). Two of these species belong to the genus Cheilotrichia: Cheilotrichia oisensis Kopeć, Krzemiński & Kania-Kłosok sp. nov, Cheilotrichia gallica Kopeć, Krzemiński & Kania-Kłosok sp. nov., while one represents the genus Dicranomyia : Dicranomyia (Dicranomyia) podenasi Kopeć, Krzemiński & Kania-Kłosok sp. nov. This marks the first discovery of Limoniidae representatives in Oise amber, the oldest known Eocene resin, dating back approximately 55–53 Ma (Early Eocene, Ypresian). Our analysis indicates that the species composition of Limoniidae (Diptera, Nematocera) in Oise amber differs from that in Baltic amber. Despite their similar geographical origins, these ambers were produced in different periods and by different trees. The study of Oise amber provides valuable insights into the fauna of the earliest Eocene. These new discoveries contribute to our understanding of the evolutionary history of Limoniidae, particularly during the Early Eocene.
The influence of origin and age of ducks on egg morphological composition and level and activity of lysozyme
Theoretical stress mechanism and structural integrity of viscoelastic propellant grains with variable Poisson’s ratio
Preparation of gold nanoparticles decorated UiO-66-NH2 incorporated epichlorohydrin and cyclodextrin as novel efficient catalyst in cross coupling and carbonylative reactions
Evaluation of the effect of ecological restoration in mineral resource cities and analysis of driving factors
Mathematical modelling of membrane oscillatory processes in a nonlinear viscoelastic medium via the Caputo-Fabrizio fractional operator
Enhancement the stability of the titanium/graphite photo-electrode in varying voltages for treatment of textile wastewater using reactive blue 19 as the model contaminant
Machine learning for predicting medical outcomes associated with acute lithium poisoning
Exploration of the soliton solutions of the (n+1) dimensional generalized Kadomstev Petviashvili equation using an innovative approach
Effect of heel height on patellofemoral joint stress during stair descent
A NLP analysis of digital demand for healthcare jobs in China
Enterococcus faecalis SI-FC-01 enhances the stress resistance and healthspan of C. elegans via AKT signaling pathway
Study on precision reliability evaluation method of harmonic drive based on NIPCE considering wear
Vision transformer and deep learning based weighted ensemble model for automated spine fracture type identification with GAN generated CT images
Abstract The most common causes of spine fractures, or vertebral column fractures (VCF), are traumas like falls, injuries from sports, or accidents. CT scans are affordable and effective at detecting VCF types in an accurate manner. VCF type identification in cervical, thoracic, and lumbar (C3-L5) regions is limited and sensitive to inter-observer variability. To solve this problem, this work introduces an autonomous approach for identifying VCF type by developing a novel ensemble model of Vision Transformers (ViT) and best-performing deep learning (DL) models. It assists orthopaedicians in easy and early identification of VCF types. The performance of numerous fine-tuned DL architectures, including VGG16, ResNet50, and DenseNet121, was investigated, and an ensemble classification model was developed to identify the best-performing combination of DL models. A ViT model is also trained to identify VCF. Later, the best-performing DL models and ViT were fused by weighted average technique for type identification. To overcome data limitations, an extended Deep Convolutional Generative Adversarial Network (DCGAN) and Progressive Growing Generative Adversarial Network (PGGAN) were developed. The VGG16-ResNet50-ViT ensemble model outperformed all ensemble models and got an accuracy of 89.98%. Extended DCGAN and PGGAN augmentation increased the accuracy of type identification to 90.28% and 93.68%, respectively. This demonstrates efficacy of PGGANs in augmenting VCF images. The study emphasizes the distinctive contributions of the ResNet50, VGG16, and ViT models in feature extraction, generalization, and global shape-based pattern capturing in VCF type identification. CT scans collected from a tertiary care hospital are used to validate these models.
Differential biomarker expression of blood and lymphatic vasculature in multi-organ-chips
Abstract Since the blood and lymphatic endothelium regulates homeostasis and inflammation during health and disease, establishment of vascularized Organ-on-Chip platforms with blood and lymphatic endothelial cells (BEC/LEC) is a pre-requisite to further advance the field of tissue engineering. Here, we aimed to determine whether characteristics of BECs and LECs cultured under flow in a multi-organ-chip (MOC) are influenced by shear stress or inflammation. Dermis-derived primary BECs and LECs were used to endothelialize a MOC followed by culture for up to 14 days at lymphatic and blood flow rates. Under blood flow, both cell types changed morphology, aligned in flow direction, and showed close cell-cell contacts as in in vivo blood vasculature. Under lymphatic flow, neither BEC nor LEC aligned, and both showed a cobblestone-appearance with limited intercellular contacts similar to lymphatics. Cells retained their cell type-specific phenotype and cytokine secretion profiles. CCL21 expression in LECs was rescued by flow, but diminished again with TNFα exposure, together with the LEC-specific markers PROX1 and TFF3. Homeostatic cytokine secretion was higher in BECs, but the response to TNFα was more pronounced in LECs. Results indicate that BEC and LEC phenotype and cytokine secretion is mostly an intrinsic property with only morphology and CCL21 being influenced by flow.
Deformation and force analysis of reinforced soil Bridge abutment under dynamic vehicle loading
Chronic chlorothalonil exposure inhibits locomotion and interferes with the gut-liver axis in Pelophylax nigromaculatus tadpoles
Abstract Chlorothalonil is a widely used fungicide that has a negative effect on individual movement, but its impact pathway needs further refinement. Here, the effects of exposure to chlorothalonil on the locomotion behavior of Pelophylax nigromaculatus tadpoles (GS23) were measured at three different levels (0 µg/L, 10 µg/L, and 50 µg/L), and the possible pathways of its effects were analyzed from the gut-liver axis. Chlorothalonil exposure levels of 10 µg/L and 50 µg/L significantly reduced the average speed of P. nigromaculatus tadpoles by 26% and 32.7%, respectively, and significantly decreased the locomotor frequency by 27.1% and 58.6%, respectively. Gut microbiota analysis revealed chlorothalonil exposure significantly increased the abundance of Firmicutes, while significantly decreased the abundance of Actinobacteriota, Pseudomonas, and Rhodococcus. Metabolomics analysis identified that chlorothalonil treatment changed amino acid-related metabolism pathways in the gut and liver and altered the glycerophospholipid metabolism pathway in the liver. This study indicated that chlorothalonil can affect individual locomotor abilities and interfering with the gut-liver axis of aquatic animals. These findings establish that chlorothalonil compromises aquatic organism motility through a multi-target mechanism involving gut microbiota modulation, amino acid metabolic interference, and hepatic lipid pathway disruption.
Maintenance of time-restricted eating and high-intensity interval training in women with overweight/obesity 2 years after a randomized controlled trial
Abstract Time-restricted eating (TRE) and high-intensity interval training (HIIT) improve cardiometabolic health in individuals with overweight/obesity, with high adherence rates in supervised settings. Long-term maintenance of TRE and HIIT in real-world settings is unknown. In our previous TREHIIT trial, 131 women (body mass index (BMI) ≥ 27 kg/m2) were randomized to 7 weeks of TRE (eating window 10-h/day), HIIT (3 sessions/week), a combination (TREHIIT), or no intervention (CON). We investigated self-reported continuation of TRE and/or HIIT after 2 years. Fifty-nine participants (39.0 years (standard deviation (SD) 6.1), BMI 30.7 kg/m2 (SD 4.2)) attended the follow-up. Of those who completed the 7-week TRE or HIIT intervention, 46% maintained TRE and 45% continued HIIT for 2 years. There were no statistically significant (at p < .01) between-group differences in cardiometabolic outcomes, but non-significant lower body mass in HIIT (-4.2 kg, 95% confidence interval (CI), -7.7 to -0.7, p = .019) and visceral fat in TREHIIT (-18 cm2, CI, -33 to -4, p = .015) versus CON. After 2 years, HIIT and TREHIIT had ~ 4 kg lower fat mass and ~ 20 cm² lower visceral fat (both p < .001) compared with baseline. A short-term TRE and HIIT intervention may promote long-term lifestyle changes and health benefits. Future studies should collect objective adherence data to understand long-term maintenance of TRE and HIIT.