Search Results (44)

Transcriptomic profiling has shown that exposure to PM_2.5, a common air pollutant, can modulate gene expression, which has been linked to negative health effects and diseases. However, there are few population-based cohort studies on the association between PM_2.5 exposure and specific gene set expression. In this study, we used an unbiased transcriptomic profiling approach to examine gene expression in a mouse model exposed to PM_2.5 and to identify PM_2.5-responsive genes. The gene expressions were further validated in both the human cell lines and a population-based cohort study. Two cohorts of healthy older adults (aged ≥ 65 years) were recruited from regions characterized by differing levels of PM_2.5. Logistic regression and decision tree algorithms were then utilized to construct predictive models for PM_2.5 exposure based on these gene expression profiles. Our results indicated that the expression of five genes (FAM102B, PPP2R1B, OXR1, ITGAM, and PRP38B) increased with PM_2.5 exposure in both cell-based assay and population-based cohort studies. Furthermore, the predictive models demonstrated high accuracy in classifying high-and-low PM_2.5 exposure, potentially supporting the integration of gene biomarkers into public health practices. Full article

Background: The biologics derived from human amniotic membranes (AMs) demonstrate potential pain-inhibitory effects in clinical settings. However, the molecular basis underlying this therapeutic effect remains elusive. HC-HA/PTX3 is a unique water-soluble regenerative matrix that is purified from human AMs. We examined whether HC-HA/PTX3 can modulate the gene networks and transcriptional signatures in the dorsal root ganglia (DRG) neurons transmitting peripheral sensory inputs to the spinal cord. Methods: We conducted bulk RNA-sequencing (RNA-seq) of mouse DRG neurons after treating them with HC-HA/PTX3 (15 µg/mL) for 10 min and 24 h in culture. Differential gene expression analysis was performed using the limma package, and Gene Ontology (GO) and protein–protein interaction (PPI) analyses were conducted to identify the networks of pain-related genes. Western blotting and in vitro calcium imaging were used to examine the protein levels and signaling of pro-opiomelanocortin (POMC) in DRG neurons. Results: Compared to the vehicle-treated group, 24 h treatment with HC-HA/PTX3 induced 2047 differentially expressed genes (DEGs), which were centered on the ATPase activity, receptor–ligand activity, and extracellular matrix pathways. Importantly, PPI analysis revealed that over 50 of these DEGs are closely related to pain and analgesia. Notably, HC-HA/PTX3 increased the expression and signaling pathway of POMC, which may affect opioid analgesia. Conclusions: HC-HA/PTX3 induced profound changes in the gene expression in DRG neurons, centered around various neurochemical mechanisms associated with pain modulation. Our findings suggest that HC-HA/PTX3 may be an important biological active component in human AMs that partly underlies its pain inhibitory effect, presenting a new strategy for pain treatment. Full article

The fatigue performance of steel–concrete composite beams is crucial for ensuring structural safety. To account for the member’s multiaxial stress state, this study employed the critical surface method, using fatigue damage parameters as an evaluation index for assessing fatigue performance. Static and fatigue performance tests on steel–concrete beams were conducted to identify failure characteristics, which informed the development of a finite element model that incorporates concrete damage. Using the SWT model, the most unfavorable loading parameters were determined by analyzing critical paths on the test beams, providing a basis for predicting how initial defects impact fatigue performance. The impact of initial defects on the fatigue performance of the composite beam is assessed using this criterion. The results indicate that the discrepancy between the actual and predicted load capacities of the test beam is within 5%, and cyclic loading significantly affects the test beam’s mechanical properties, resulting in a 27% reduction in load capacity and a 48% increase in deflection after 2 million cycles. Finite element modeling reveals that components experience multiaxial stress, with test beam mechanical property changes aligning with predicted fatigue damage parameters, confirming the reliability of using these parameters as a criterion. As the strength of the composite beams diminished due to pore defects, the fatigue damage parameter escalated, increasing the likelihood of crack formation. However, once the concrete’s strength fell to a level where the pegs were insufficiently constrained, the structural damage pattern shifted, and the fatigue damage parameter subsequently decreased. Full article

MicroRNAs are small regulatory molecules that control gene expression. An emerging property of muscle miRNAs is the cooperative regulation of transcriptional and epitranscriptional events controlling muscle phenotype. miR-155 has been related to muscular dystrophy and muscle cell atrophy. However, the function of miR-155 and its molecular targets in muscular dystrophies remain poorly understood. Through in silico and in vitro approaches, we identify distinct transcriptional profiles induced by miR-155-5p in muscle cells. The treated myotubes changed the expression of 359 genes (166 upregulated and 193 downregulated). We reanalyzed muscle transcriptomic data from dystrophin-deficient patients and detected overlap with gene expression patterns in miR-155-treated myotubes. Our analysis indicated that miR-155 regulates a set of transcripts, including Aldh1l, Nek2, Bub1b, Ramp3, Slc16a4, Plce1, Dync1i1, and Nr1h3. Enrichment analysis demonstrates 20 targets involved in metabolism, cell cycle regulation, muscle cell maintenance, and the immune system. Moreover, digital cytometry confirmed a significant increase in M2 macrophages, indicating miR-155’s effects on immune response in dystrophic muscles. We highlight a critical miR-155 associated with disease-related pathways in skeletal muscle disorders. Full article

Laryngeal cancer poses a significant global health burden, with late-stage diagnoses contributing to reduced survival rates. This study explores the application of deep convolutional neural networks (DCNNs), specifically the Densenet201 architecture, in the computer-aided diagnosis of laryngeal cancer using laryngoscopic images. Our dataset comprised images from two medical centers, including benign and malignant cases, and was divided into training, internal validation, and external validation groups. We compared the performance of Densenet201 with other commonly used DCNN models and clinical assessments by experienced clinicians. Densenet201 exhibited outstanding performance, with an accuracy of 98.5% in the training cohort, 92.0% in the internal validation cohort, and 86.3% in the external validation cohort. The area under the curve (AUC) values consistently exceeded 92%, signifying robust discriminatory ability. Remarkably, Densenet201 achieved high sensitivity (98.9%) and specificity (98.2%) in the training cohort, ensuring accurate detection of both positive and negative cases. In contrast, other DCNN models displayed varying degrees of performance degradation in the external validation cohort, indicating the superiority of Densenet201. Moreover, Densenet201’s performance was comparable to that of an experienced clinician (Clinician A) and outperformed another clinician (Clinician B), particularly in the external validation cohort. Statistical analysis, including the DeLong test, confirmed the significance of these performance differences. Our study demonstrates that Densenet201 is a highly accurate and reliable tool for the computer-aided diagnosis of laryngeal cancer based on laryngoscopic images. The findings underscore the potential of deep learning as a complementary tool for clinicians and the importance of incorporating advanced technology in improving diagnostic accuracy and patient care in laryngeal cancer diagnosis. Future work will involve expanding the dataset and further optimizing the deep learning model. Full article

Obesity is a growing public health problem associated with increased risk of type 2 diabetes, cardiovascular disease, nonalcoholic fatty liver disease (NAFLD) and cancer. Here, we identify microRNA-22 (miR-22) as an essential rheostat involved in the control of lipid and energy homeostasis as well as the onset and maintenance of obesity. We demonstrate through knockout and transgenic mouse models that miR-22 loss-of-function protects against obesity and hepatic steatosis, while its overexpression promotes both phenotypes even when mice are fed a regular chow diet. Mechanistically, we show that miR-22 controls multiple pathways related to lipid biogenesis and differentiation. Importantly, genetic ablation of miR-22 favors metabolic rewiring towards higher energy expenditure and browning of white adipose tissue, suggesting that modulation of miR-22 could represent a viable therapeutic strategy for treatment of obesity and other metabolic disorders. Full article

In recent years, non-grain production of cultivated land (NGPCL) has become increasingly prominent in China, seriously affecting food production and threatening the country’s food security. However, there is a lack of large-scale and high-precision methods for remote sensing identification of NGPCL. From the perspective of effective management of cultivated land resources, the characteristics of the spatial patterns of NGPCL, both on a large scale and at a patch scale, need to be further studied. For solving this problem, this paper uses the Google Earth engine (GEE) cloud computing platform and multi-source remote sensing data with a machine learning algorithm to determine the occurrence of NGPCL in Anhui province in 2019, and then uses nine selected landscape pattern indexes to analyze the spatial patterns of NGPCL from two aspects, specifically, economic development level and topography. The results show that: (1) terrain features, radar features, and texture features are beneficial to the extraction of NGPCL; (2) the degree of separation obtained by using an importance evaluation approach shows that spectral features have the highest importance, followed by index features with red edges, texture features, index features without red edges, radar features, and terrain features; and (3) the cultivated land in Anhui province in 2019 is mainly planted with food crops, and the phenomenon of NGPCL is more likely to occur in areas with high economic development levels and flat terrain. Aided by the GEE cloud platform, multi-source remote sensing data, and machine learning algorithm, the remote sensing monitoring approach utilized in this study could accurately, quickly, and efficiently determine NGPCL on a regional scale. Full article

This article studies the partial eigenstructure assignment (PEA) problem for a type of linear time-invariant (LTI) system. By introducing a dynamic output feedback controller, the closed-loop system is similar to a given arbitrary constant matrix, so the desired closed-loop eigenstructure can be obtained. Different from the normal eigenstructure assignment, only a part of the left and right generalized eigenvectors is assigned to the closed-loop system to remove complicated constraints, which reflects the partial eigenstructure assignment. Meanwhile, based on the solutions to the generalized Sylvester equations (GSEs), two arbitrary parameter matrices representing the degrees of freedom are presented to obtain the parametric form of the coefficient matrices of the dynamic compensator and the partial eigenvector matrices. Finally, an illustrative example and the simulation results prove the excellent effectiveness and feasibility of parametric method we proposed. Full article

Lampriform fishes (Lampriformes), which primarily inhabit deep-sea environments, are large marine fishes varying from the whole-body endothermic opah to the world’s longest bony fish-giant oarfish, with species morphologies varying from long and thin to deep and compressed, making them an ideal model for studying the adaptive radiation of teleost fishes. Moreover, this group is important from a phylogenetic perspective owing to their ancient origins among teleosts. However, knowledge about the group is limited, which is, at least partially, due to the dearth of recorded molecular data. This study is the first to analyze the mitochondrial genomes of three lampriform species (Lampris incognitus, Trachipterus ishikawae, and Regalecus russelii) and infer a time-calibrated phylogeny, including 68 species among 29 orders. Our phylomitogenomic analyses support the classification of Lampriformes as monophyletic and sister to Acanthopterygii; hence, addressing the longstanding controversy regarding the phylogenetic status of Lampriformes among teleosts. Comparative mitogenomic analyses indicate that tRNA losses existed in at least five Lampriformes species, which may reveal the mitogenomic structure variation associated with adaptive radiation. However, codon usage in Lampriformes did not change significantly, and it is hypothesized that the nucleus transported the corresponding tRNA, which led to function substitutions. The positive selection analysis revealed that atp8 and cox3 were positively selected in opah, which might have co-evolved with the endothermic trait. This study provides important insights into the systematic taxonomy and adaptive evolution studies of Lampriformes species. Full article

The family of Papilionidae (Lepidoptera: Papilionoidea) is a group of butterflies with high ecological and conservation value. The Hengduan Mountains (HMDs) in Southwest China is an important diversity centre for these butterflies. However, the spatial distribution pattern and the climate vulnerability of Papilionidae butterflies in the HDMs remain unknown to date. The lack of such knowledge has already become an obstacle in formulating effective butterfly conservation strategies. The present research compiled a 59-species dataset with 1938 occurrence points. The Maxent model was applied to analyse the spatial pattern of species richness in subfamilies Parnassiinae and Papilioninae, as well as to predict the response under the influence of climate change. The spatial pattern of both subfamilies in the HDMs has obvious elevation prevalence, with Parnassiinae concentrated in the subalpine to alpine areas (2500–5500 m) in western Sichuan, northwestern Yunnan and eastern Tibet, while Papilioninae is concentrated in the low- to medium-elevation areas (1500–3500 m) in the river valleys of western Yunnan and western Sichuan. Under the influence of climate change, both subfamilies would exhibit northward and upward range shifts. The majority of Parnassiinae species would experience drastic habitat contraction, resulting in lower species richness across the HDMs. In contrast, most Papilioninae species would experience habitat expansion, and the species richness would also increase significantly. The findings of this research should provide new insights and a clue for butterfly diversity and climatic vulnerability in southwestern China. Future conservation efforts should be focused on species with habitat contraction, narrow-ranged distribution and endemicity with both in situ and ex situ measures, especially in protected areas. Commercialised collecting targeting these species must also be regulated by future legislation. Full article

Oxide metallurgy technology can improve the microstructure of a coarse-grained heat-affected zone (CGHAZ) but introduces extra inclusions. Local corrosion behavior of the CGHAZ of a Zr–Ti–Al–RE deoxidized steel was investigated in this work using theoretical calculations and experimental verification. The modified inclusions have a (Zr–Mg–Al–Ca–RE)O_x core claded by a CaS and TiN shell. CaS dissolves first, followed by the oxide core, leaving TiN parts. This confirms that the addition of rare earth can reduce lattice distortion and prevent a galvanic couple between the inclusions and the matrix, while the chemical dissolution of CaS causes localized acidification, resulting in the pitting corrosion initiation. Full article

In this paper, a novel silicon super-junction (SJ) MOSFET embedded with a soft reverse recovery body diode is proposed and studied by numerical simulation. The device introduces an n⁺-buffer layer between the n⁻-buffer layer and the n⁺-substrate to improve the reverse recovery behaviour of its body diode. The n⁺-buffer layer provides residual carriers during the reverse recovery process, reduces the overshoot voltage, and suppresses oscillation. Simulated results demonstrate that the increment of the on-resistance and the drain-to-source overshoot voltage can be respectively kept below 5% and 20 V, if a 10 μm n⁺-buffer layer whose impurity concentration ranges from 4 × 10¹⁵ cm⁻³ to 6 × 10¹⁶ cm⁻³ is used. In addition, the fabrication process is the same as that of the conventional SJ-MOSFET. These features make the proposed SJ-MOSFET suitable for inverter applications. Full article

A transmission tower-line system consists of many towers and cables, which is a long-span structure. Due to topographical restrictions, the structure inevitably passes through wide areas prone to landslide hazards. The landslide causes the failure of the tower foundation and threatens the safety of the power transmission system. Therefore, the aim of this study was to investigate the collapse patterns of a transmission tower-line structure under landslides. The explicit analysis method was used to deal with the nonlinear dynamic response equations of the structure. To prove the effect of the landslides on the collapse patterns of the transmission tower-line structure, two foundation failure cases (Case 1 and Case 2) under landslides were considered. For each case, the displacement responses at tower tops and the progressive collapse behavior were analyzed, which illustrate that the failure patterns of the tower-line structure under landslides are dominated by two factors, i.e., the failure mode of the tower foundation and the pulling effect of cables. The overall tilting and hinge formation in the middle of the tower body are the main collapse patterns of the structure under Case 1 and Case 2, respectively. In addition, because of the pulling of cables, the collapse of one tower induced by the landslides always triggers the local failure of neighboring tower heads. Full article

Background: Age is an independent risk factor of the progress and prognosis of atrial fibrillation (AF). However, ablation outcomes between elderly and younger patients with AF remain elusive. Methods: Cochrane Library, Embase, PubMed, and Web of Science were systematically searched up to 1 April 2022. Studies comparing AF ablation outcomes between elderly and younger patients and comprising outcomes of AF ablation for elderly patients were included. Trial sequential analysis (TSA) was performed to adjust for random error and lower statistical power in our meta-analysis. Subgroup analysis identified possible determinants of outcome impact for elderly patients after ablation. Moreover, linear and quadratic prediction fit plots with confidence intervals were performed, as appropriate. Results: A total of 27 studies with 113,106 AF patients were eligible. Compared with the younger group, the elderly group was significantly associated with a lower rate of freedom from AF (risk ratio [RR], 0.95; p = 0.008), as well as a higher incidence of safety outcomes (cerebrovascular events: RR, 1.64; p = 0.000; serious hemorrhage complications: RR, 1.50; p = 0.035; all-cause death: RR, 2.61; p = 0.003). Subgroup analysis and quadratic prediction fit analysis revealed the follow-up time was the potential determinant of freedom from AF for elderly patients after AF ablation. Conclusions: Our meta-analysis suggests that elderly patients may have inferior efficacy and safety outcomes to younger patients with AF ablation. Moreover, the follow-up time may be a potential determinant of outcome impact on freedom from AF for elderly patients after AF ablation. Full article

Gambierdiscus is a dinoflagellate genus widely distributed throughout tropical and subtropical regions. Some members of this genus can produce a group of potent polycyclic polyether neurotoxins responsible for ciguatera fish poisoning (CFP), one of the most significant food-borne illnesses associated with fish consumption. Ciguatoxins and maitotoxins, the two major toxins produced by Gambierdiscus, act on voltage-gated channels and TRPA1 receptors, consequently leading to poisoning and even death in both humans and animals. Over the past few decades, the occurrence and geographic distribution of CFP have undergone a significant expansion due to intensive anthropogenic activities and global climate change, which results in more human illness, a greater public health impact, and larger economic losses. The global spread of CFP has led to Gambierdiscus and its toxins being considered an environmental and human health concern worldwide. In this review, we seek to provide an overview of recent advances in the field of Gambierdiscus and its associated toxins based on the existing literature combined with re-analyses of current data. The taxonomy, phylogenetics, geographic distribution, environmental regulation, toxin detection method, toxin biosynthesis, and pharmacology and toxicology of Gambierdiscus are summarized and discussed. We also highlight future perspectives on Gambierdiscus and its associated toxins. Full article