RESUMEN
We propose a visual Simultaneous Localization and Mapping (SLAM) algorithm that integrates target detection and clustering techniques in dynamic scenarios to address the vulnerability of traditional SLAM algorithms to moving targets. The proposed algorithm integrates the target detection module into the front end of the SLAM and identifies dynamic objects within the visual range by improving the YOLOv5. Feature points associated with the dynamic objects are disregarded, and only those that correspond to static targets are utilized for frame-to-frame matching. This approach effectively addresses the camera pose estimation in dynamic environments, enhances system positioning accuracy, and optimizes the visual SLAM performance. Experiments on the TUM public dataset and comparison with the traditional ORB-SLAM3 algorithm and DS-SLAM algorithm validate that the proposed visual SLAM algorithm demonstrates an average improvement of 85.70 and 30.92% in positioning accuracy in highly dynamic scenarios. In comparison to the DynaSLAM system using MASK-RCNN, our system exhibits superior real-time performance while maintaining a comparable ATE index. These results highlight that our pro-posed SLAM algorithm effectively reduces pose estimation errors, enhances positioning accuracy, and showcases enhanced robustness compared to conventional visual SLAM algorithms.
RESUMEN
Corneal infection is a major public health concern worldwide and the most common cause of unilateral corneal blindness. Toxic effects of different microorganisms, such as bacteria and fungi, worsen keratitis leading to corneal perforation even with optimal drug treatment. The cornea forms the main refractive surface of the eye. Diseases affecting the cornea can cause severe visual impairment. Therefore, it is crucial to analyze the risk of corneal perforation and visual impairment in corneal ulcer patients for making early treatment strategies. The modeling of a fully automated prognostic model system was performed in two parts. In the first part, the dataset contained 4973 slit lamp images of corneal ulcer patients in three centers. A deep learning model was developed and tested for segmenting and classifying five lesions (corneal ulcer, corneal scar, hypopyon, corneal descementocele, and corneal neovascularization) in the eyes of corneal ulcer patients. Further, hierarchical quantification was carried out based on policy rules. In the second part, the dataset included clinical data (name, gender, age, best corrected visual acuity, and type of corneal ulcer) of 240 patients with corneal ulcers and respective 1010 slit lamp images under two light sources (natural light and cobalt blue light). The slit lamp images were then quantified hierarchically according to the policy rules developed in the first part of the modeling. Combining the above clinical data, the features were used to build the final prognostic model system for corneal ulcer perforation outcome and visual impairment using machine learning algorithms such as XGBoost, LightGBM. The ROC curve area (AUC value) evaluated the model's performance. For segmentation of the five lesions, the accuracy rates of hypopyon, descemetocele, corneal ulcer under blue light, and corneal neovascularization were 96.86, 91.64, 90.51, and 93.97, respectively. For the corneal scar lesion classification, the accuracy rate of the final model was 69.76. The XGBoost model performed the best in predicting the 1-month prognosis of patients, with an AUC of 0.81 (95% CI 0.63-1.00) for ulcer perforation and an AUC of 0.77 (95% CI 0.63-0.91) for visual impairment. In predicting the 3-month prognosis of patients, the XGBoost model received the best AUC of 0.97 (95% CI 0.92-1.00) for ulcer perforation, while the LightGBM model achieved the best performance with an AUC of 0.98 (95% CI 0.94-1.00) for visual impairment.
Asunto(s)
Úlcera de la Córnea , Aprendizaje Automático , Humanos , Úlcera de la Córnea/diagnóstico , Pronóstico , Femenino , Masculino , Persona de Mediana Edad , Anciano , Adulto , Aprendizaje Profundo , Curva ROC , Agudeza Visual , Anciano de 80 o más AñosRESUMEN
Maintaining homeostasis within the intestinal microbiota is imperative for assessing the health status of hosts, and dysbiosis within the intestinal microbiota is closely associated with canine intestinal diseases. In recent decades, the modulation of canine intestinal health through probiotics and prebiotics has emerged as a prominent area of investigation. Evidence indicates that probiotics and prebiotics play pivotal roles in regulating intestinal health by modulating the intestinal microbiota, fortifying the epithelial barrier, and enhancing intestinal immunity. This review consolidates literature on using probiotics and prebiotics for regulating microbiota homeostasis in canines, thereby furnishing references for prospective studies and formulating evaluation criteria.
RESUMEN
Diabetic nephropathy (DN) is a primary diabetic complication ascribed to the pathological changes in renal microvessels. This study investigated the nuclear factor erythroid 2-related factor 2 (Nrf2)/Kelch ECH associating protein (Keap1)/antioxidant response element (ARE) signaling pathway impact of chitooligosaccharides (COS) with a certain degree of polymerization (DP) on DN mouse models and high glucose-damaged human kidney 2 (HK-2) cells. The findings indicated that COS effectively reduced the renal function indexes (uric acid [UA], urinary albumin excretion rate [UAER], urine albumin-to-creatinine ratio [UACR], blood urea nitrogen [BUN], and creatinine [Cre]) of DN mice. It increased (p < .05) the superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) antioxidant enzyme activity in the serum and kidneys, and decreased (p < .05) the malondialdehyde (MDA) content. The mechanistic investigation showed that COS significantly increased (p < .05) Nrf2 and downstream target gene (GCLM, GCLC, HO-1, and NQO-1) expression, and substantially decreased (p < .05) Keap1 expression. The protein level was consistent with the messenger RNA (mRNA) level in in vitro and in vivo models. The docking data indicated that COS and Keap1 protein binding included six hydrogen bond formation processes (Gly364, Arg415, Arg483, His436, Ser431, and Arg380). The COS intervention mechanism may be related to the Nrf2/Keap1/ARE antioxidant pathway. Therefore, it provides a scientific basis for COS application in developing special medical food for DN patients.
RESUMEN
Whole-genome genotyping (WGG) stands as a pivotal element in genomic-assisted plant breeding. Nevertheless, sequencing-based approaches for WGG continue to be costly, primarily owing to the high expenses associated with library preparation and the laborious protocol. During prior development of foreground and background integrated genotyping by sequencing (FBI-seq), we discovered that any sequence-specific primer (SP) inherently possesses the capability to amplify a massive array of stable and reproducible non-specific PCR products across the genome. Here, we further improved FBI-seq by replacing the adapter ligated by Tn5 transposase with an arbitrary degenerate (AD) primer. The protocol for the enhanced FBI-seq unexpectedly mirrors a simplified thermal asymmetric interlaced (TAIL)-PCR, a technique that is widely used for isolation of flanking sequences. However, the improved TAIL-PCR maximizes the primer-template mismatched annealing capabilities of both SP and AD primers. In addition, leveraging of next-generation sequencing enhances the ability of this technique to assay tens of thousands of genome-wide loci for any species. This cost-effective, user-friendly, and powerful WGG tool, which we have named TAIL-PCR by sequencing (TAIL-peq), holds great potential for widespread application in breeding programs, thereby facilitating genome-assisted crop improvement.
RESUMEN
OBJECTIVE: To develop an AI-assisted MRI model to identify surgical target areas in pediatric hip and periarticular infections. METHODS: A retrospective study was conducted on the pediatric patients with hip and periarticular infections who underwent Magnetic Resonance Imaging(MRI)examinations from January 2010 to January 2023 in three hospitals in China. A total of 7970 axial Short Tau Inversion Recovery (STIR) images were selected, and the corresponding regions of osteomyelitis (label 1) and abscess (label 2) were labeled using the Labelme software. The images were randomly divided into training group, validation group, and test group at a ratio of 7:2:1. A Mask R-CNN model was constructed and optimized, and the performance of identifying label 1 and label 2 was evaluated using receiver operating characteristic (ROC) curves. Calculation of the average time it took for the model and specialists to process an image in the test group. Comparison of the accuracy of the model in the interpretation of MRI images with four orthopaedic surgeons, with statistical significance set at P < 0.05. RESULTS: A total of 275 patients were enrolled, comprising 197 males and 78 females, with an average age of 7.10 ± 3.59 years, ranging from 0.00 to 14.00 years. The area under curve (AUC), accuracy, sensitivity, specificity, precision, and F1 score for the model to identify label 1 were 0.810, 0.976, 0.995, 0.969, 0.922, and 0.957, respectively. The AUC, accuracy, sensitivity, specificity, precision, and F1 score for the model to identify label 2 were 0.890, 0.957, 0.969, 0.915, 0.976, and 0.972, respectively. The model demonstrated a significant speed advantage, taking only 0.2 s to process an image compared to average 10 s required by the specialists. The model identified osteomyelitis with an accuracy of 0.976 and abscess with an accuracy of 0.957, both statistically better than the four orthopaedic surgeons, P < 0.05. CONCLUSION: The Mask R-CNN model is reliable for identifying surgical target areas in pediatric hip and periarticular infections, offering a more convenient and rapid option. It can assist unexperienced physicians in pre-treatment assessments, reducing the risk of missed and misdiagnosis.
Asunto(s)
Imagen por Resonancia Magnética , Osteomielitis , Humanos , Masculino , Femenino , Imagen por Resonancia Magnética/métodos , Niño , Estudios Retrospectivos , Adolescente , Osteomielitis/diagnóstico por imagen , Preescolar , Lactante , Articulación de la Cadera/diagnóstico por imagen , Articulación de la Cadera/cirugía , Articulación de la Cadera/patología , China , Absceso/diagnóstico por imagen , Absceso/cirugía , Curva ROCRESUMEN
Autophagy can be classified as degradative and secretory based on distinct functions. The small GTPase proteins Rab8a and Rab37 are responsible for secretory autophagy-mediated exocytosis of IL-1ß, insulin, and TIMP1 (tissue inhibitor of 54 metalloproteinase 1). Other Rab family members participating in secretory autophagy are poorly understood. Herein, we identified 26 overlapped Rab proteins in purified autophagosomes of mouse pancreatic ß-cell "Min-6" and human lung cancer cell "CL1-5-Q89L" with high secretory autophagy tendency by LC-MS/MS proteomics analysis. Six Rab proteins (Rab8a, Rab11b, Rab27a, Rab35, Rab37, and Rab7a) were detected in autophagosomes of four cell lines, associating them with autophagy-related vesicle trafficking. We used CL1-5-Q89L cell line model to evaluate the levels of Rab proteins colocalization with autophagy LC3 proteins and presence in purified autophagosomes. We found five Rab proteins (Rab8a, Rab11b, Rab27a, Rab35, and Rab37) are highly expressed in the autophagosome compared to the normal control by immunoblotting under active secretion conditions. However, only Rab8a, Rab35, and Rab37 showing high colocalization with LC3 protein by cofocal microscopy. Despite the discrepancy between the image and immunoblotting analysis, our data sustains the speculation that Rab8a, Rab11b, Rab27a, Rab35, and Rab37 are possibly associated with the secretory autophagy machinery. In contrast, Rab7a shows low colocalization with LC3 puncta and low level in the autophagosome, suggesting it regulates different vesicle trafficking machineries. Our findings open a new direction toward exploring the role of Rab proteins in secretory autophagy-related cargo exocytosis and identifying the cargoes and effectors regulated by specific Rab proteins.
Asunto(s)
Autofagosomas , Autofagia , Proteínas de Unión al GTP rab , Proteínas de Unión al GTP rab/metabolismo , Autofagia/fisiología , Humanos , Animales , Ratones , Autofagosomas/metabolismo , Línea Celular Tumoral , Proteínas Asociadas a Microtúbulos/metabolismo , Proteómica/métodos , Espectrometría de Masas en TándemRESUMEN
BACKGROUND: Detecting potential depression and identifying the critical predictors of depression among older adults with chronic diseases are essential for timely intervention and management of depression. Therefore, risk prediction models (RPMs) of depression in elderly people should be further explored. METHODS: A total of 3959 respondents aged 60 years or over from the wave four survey of the China Health and Retired Longitudinal Study (CHARLS) were included in this study. We used five machine learning (ML) algorithms and three data balancing techniques to construct RPMs of depression and calculated feature importance scores to determine which features are essential to depression. RESULTS: The prevalence of depression was 19.2 % among older Chinese adults with chronic diseases in the wave four survey. The random forest (RF) model was more accurate than the other models after balancing the data using the Synthetic Minority Oversampling Technique (SMOTE) algorithm, with an area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC) of 0.957 and 0.920, respectively, a balanced accuracy of 0.891 and a sensitivity of 0.875. Furthermore, we further identified several important predictors between male and female patients via constructed sex-stratified models. LIMITATIONS: Further research on the clinical impact studies of our models and external validation are needed. CONCLUSIONS: After several techniques were used to address class imbalance issues, most RPMs achieved satisfactory accuracy in predicting depression among elderly people with chronic diseases. RPMs may thus become valuable screening tools for both older individuals and healthcare practitioners to assess the risk of depression.
Asunto(s)
Depresión , Aprendizaje Automático , Humanos , Femenino , Masculino , Anciano , Enfermedad Crónica , Estudios Longitudinales , China/epidemiología , Persona de Mediana Edad , Depresión/epidemiología , Depresión/psicología , Prevalencia , Algoritmos , Anciano de 80 o más Años , Factores de Riesgo , Medición de Riesgo/estadística & datos numéricos , Factores SexualesRESUMEN
BACKGROUND: Enhancer RNAs (eRNAs) play a crucial role in transcriptional regulation. While significant progress has been made in understanding epigenetic regulation mediated by eRNAs, research on the construction of eRNA-mediated gene regulatory networks (eGRN) and the identification of critical network components that influence complex traits is lacking. RESULTS: Here, employing the pig as a model, we conducted a comprehensive study using H3K27ac histone ChIP-seq and RNA-seq data to construct eRNA expression profiles from multiple tissues of two distinct pig breeds, namely Enshi Black (ES) and Duroc. In addition to revealing the regulatory landscape of eRNAs at the tissue level, we developed an innovative network construction and refinement method by integrating RNA-seq, ChIP-seq, genome-wide association study (GWAS) signals and enhancer-modulating effects of single nucleotide polymorphisms (SNPs) measured by self-transcribing active regulatory region sequencing (STARR-seq) experiments. Using this approach, we unraveled eGRN that significantly influence the growth and development of muscle and fat tissues, and identified several novel genes that affect adipocyte differentiation in a cell line model. CONCLUSIONS: Our work not only provides novel insights into the genetic basis of economic pig traits, but also offers a generalizable approach to elucidate the eRNA-mediated transcriptional regulation underlying a wide spectrum of complex traits for diverse organisms.
Asunto(s)
Redes Reguladoras de Genes , Estudio de Asociación del Genoma Completo , Animales , Porcinos/genética , Epigénesis Genética , Regulación de la Expresión Génica , MúsculosRESUMEN
Campylobacter jejuni (C. jejuni) is a common pathogen that often causes diarrhea, loss of appetite, and even enteritis in domestic cats, affecting their growth and development, especially in kittens under 6 months of age. Oral passive immunization with chicken yolk antibody Y has been proved effective for the treatment of gastrointestinal pathogen infections due to its high specificity. In this study, C. jejuni was isolated from diarrheal cat feces, and the specific egg yolk antibody Y against C. jejuni was demonstrated to effectively inhibit its proliferation in vitro experiments. To evaluate the effect of anti-C. jejuni IgY, the mouse C. jejuni infection model was established and it was found that IgY could alleviate C. jejuni-induced clinical symptoms. Consistent with these results, the reduction of pro-inflammatory factors and intestinal colonization by C. jejuni in the IgY-treated groups, especially in the high dose group. We then evaluated the protective effect of IgY on young Ragdoll cats infected with C. jejuni. This specific antibody reduced the rate of feline diarrhea, protected the growth of young cats, inhibited systemic inflammatory hyperactivation, and increased fecal short-chain fatty acid concentrations. Notably, IgY may have a protective role by changing intestinal amino acid metabolism and affecting C. jejuni chemotaxis. Collectively, specific IgY is a promising therapeutic strategy for C. jejuni-induced cat diarrhea.
RESUMEN
The fundamental mechanisms by which a diet affects susceptibility to or modifies autoimmune diseases are poorly understood. Excess dietary salt intake acts as a risk factor for autoimmune diseases; however, little information exists on the impact of salt intake on type 1 diabetes. To elucidate the potential effect of high salt intake on autoimmune diabetes, nonobese diabetic (NOD) mice were fed a high-salt diet (HSD) or a normal-salt diet (NSD) from 6 to 12 weeks of age and monitored for diabetes development. Our results revealed that the HSD accelerated diabetes progression with more severe insulitis in NOD mice in a CD4+ T-cell-autonomous manner when compared with the NSD group. Moreover, expression of IL-21 and SPAK in splenic CD4+ T cells from HSD-fed mice was significantly upregulated. Accordingly, we generated T-cell-specific SPAK knockout (CKO) NOD mice and demonstrated that SPAK deficiency in T cells significantly attenuated diabetes development in NOD mice by downregulating IL-21 expression in CD4+ T cells. Furthermore, HSD-triggered diabetes acceleration was abolished in HSD-fed SPAK CKO mice when compared with HSD-fed NOD mice, suggesting an essential role of SPAK in salt-exacerbated T-cell pathogenicity. Finally, pharmacological inhibition of SPAK activity using a specific SPAK inhibitor (closantel) in NOD mice ameliorated diabetogenesis, further illuminating the potential of a SPAK-targeting immunotherapeutic approach for autoimmune diabetes. Here, we illustrate that a substantial association between salt sensitivity and the functional impact of SPAK on T-cell pathogenicity is a central player linking high-salt-intake influences to immunopathophysiology of diabetogenesis in NOD mice.
Asunto(s)
Diabetes Mellitus Tipo 1 , Interleucinas , Cloruro de Sodio Dietético , Ratones , Animales , Diabetes Mellitus Tipo 1/genética , Proteínas Serina-Treonina Quinasas/metabolismo , Ratones Endogámicos NOD , Linfocitos T CD4-Positivos/metabolismoRESUMEN
BACKGROUND/AIMS: To improve the accuracy of pterygium screening and detection through smartphones, we established a fusion training model by blending a large number of slit-lamp image data with a small proportion of smartphone data. METHOD: Two datasets were used, a slit-lamp image dataset containing 20 987 images and a smartphone-based image dataset containing 1094 images. The RFRC (Faster RCNN based on ResNet101) model for the detection model. The SRU-Net (U-Net based on SE-ResNeXt50) for the segmentation models. The open-cv algorithm measured the width, length and area of pterygium in the cornea. RESULTS: The detection model (trained by slit-lamp images) obtained the mean accuracy of 95.24%. The fusion segmentation model (trained by smartphone and slit-lamp images) achieved a microaverage F1 score of 0.8981, sensitivity of 0.8709, specificity of 0.9668 and area under the curve (AUC) of 0.9295. Compared with the same group of patients' smartphone and slit-lamp images, the fusion model performance in smartphone-based images (F1 score of 0.9313, sensitivity of 0.9360, specificity of 0.9613, AUC of 0.9426, accuracy of 92.38%) is close to the model (trained by slit-lamp images) in slit-lamp images (F1 score of 0.9448, sensitivity of 0.9165, specificity of 0.9689, AUC of 0.9569 and accuracy of 94.29%). CONCLUSION: Our fusion model method got high pterygium detection and grading accuracy in insufficient smartphone data, and its performance is comparable to experienced ophthalmologists and works well in different smartphone brands.
Asunto(s)
Conjuntiva/anomalías , Pterigion , Teléfono Inteligente , Humanos , Pterigion/diagnóstico , Córnea , Lámpara de HendiduraRESUMEN
The development and growth of porcine skeletal muscle determine pork quality and yield. While genetic regulation of porcine skeletal muscle development has been extensively studied using various omics data, the role of transposable elements (TEs) in this context has been less explored. To bridge this gap, we constructed a comprehensive atlas of TE expression throughout the developmental stages of porcine skeletal muscle. This was achieved by integrating porcine TE genomic coordinates with whole-transcriptome RNA-Seq data from 27 developmental stages. We discovered that in pig skeletal muscle, active Tes are closely associated with active epigenomic marks, including low levels of DNA methylation, high levels of chromatin accessibility, and active histone modifications. Moreover, these TEs include 6074 self-expressed TEs that are significantly enriched in terms of muscle cell development and myofibril assembly. Using the TE expression data, we conducted a weighted gene co-expression network analysis (WGCNA) and identified a module that is significantly associated with muscle tissue development as well as genome-wide association studies (GWAS) of the signals of pig meat and carcass traits. Within this module, we constructed a TE-mediated gene regulatory network by adopting a unique multi-omics integration approach. This network highlighted several established candidate genes associated with muscle-relevant traits, including HES6, CHRNG, ACTC1, CHRND, MAMSTR, and PER2, as well as novel genes like ENSSSCG00000005518, ENSSSCG00000033601, and PIEZO2. These novel genes hold promise for regulating muscle-related traits in pigs. In summary, our research not only enhances the TE-centered dissection of the genetic basis underlying pork production traits, but also offers a general approach for constructing TE-mediated regulatory networks to study complex traits or diseases.
RESUMEN
Eusocial pollinators are crucial elements in global agriculture. The honeybees and bumblebees are associated with a simple yet host-restricted gut community, which protect the hosts against pathogen infections. Recent genome mining has led to the discovery of biosynthesis pathways of bioactive natural products mediating microbe-microbe interactions from the gut microbiota. Here, we investigate the diversity of biosynthetic gene clusters in the bee gut microbiota by analyzing 477 genomes from cultivated bacteria and metagenome-assembled genomes. We identify 744 biosynthetic gene clusters (BGCs) covering multiple chemical classes. While gene clusters for the post-translationally modified peptides are widely distributed in the bee guts, the distribution of the BGC classes varies significantly in different bee species among geographic locations, which is attributed to the strain-level variation of bee gut members in the chemical repertoire. Interestingly, we find that Gilliamella strains possessing a thiopeptide-like BGC show potent activity against the pathogenic Melissococcus plutonius. The spectrometry-guided genome mining reveals a RiPP-encoding BGC from Gilliamella with a 10 amino acid-long core peptide exhibiting antibacterial potentials. This study illustrates the widespread small-molecule-encoding BGCs in the bee gut symbionts and provides insights into the bacteria-derived natural products as potential antimicrobial agents against pathogenic infections.
Asunto(s)
Antiinfecciosos , Productos Biológicos , Abejas/genética , Animales , Metagenoma , Bacterias/genética , Bacterias/metabolismo , Péptidos/genética , Péptidos/farmacología , Péptidos/metabolismo , Antiinfecciosos/farmacología , Antiinfecciosos/metabolismo , Productos Biológicos/metabolismoRESUMEN
Understanding the mechanism of slow lithium ion (Li+) transport kinetics in LiFePO4 is not only practically important for high power density batteries but also fundamentally significant as a prototypical ion-coupled electron transfer process. Substantial evidence has shown that the slow ion transport kinetics originates from the coupled transfer between electrons and ions and the phase segregation of Li+. Combining a model Hamiltonian analysis and DFT calculations, we reveal that electrostatic interactions play a decisive role in coupled charge transfer and Li+ segregation. The obtained potential energy surfaces prove that ion-electron coupled transfer is the optimal reaction pathway due to electrostatic attractions between Li+ and e- (Fe2+), while prohibitively large energy barriers are required for separate electron tunneling or ion hopping to overcome the electrostatic energy between the Li+-e- (Fe2+) pair. The model reveals that Li+-Li+ repulsive interaction in the [010] transport channels together with Li+-e- (Fe2+)-Li+ attractive interaction along the [100] direction cause the phase segregation of Li+. It explains why the thermodynamically stable phase interface between Li-rich and Li-poor phases in LiFePO4 is perpendicular to [010] channels.
RESUMEN
BACKGROUND: Antinuclear antibodies (ANAs) are crucial in diagnosing autoimmune diseases, mainly systemic lupus erythematosus (SLE). This study aimed to compare the performance of chemiluminescence assay (CLIA) and line immunoassay (LIA) in detecting ANAs in patients with autoimmune diseases, evaluate their diagnostic accuracy for SLE, and develop a novel diagnostic model using CLIA-detected antibodies for SLE. Specimens from patients with autoimmune diseases and physical examination specimens were collected to parallel detect specific antibodies. Individual antibodies' diagnostic performance and a model combining multiple antibodies were assessed. The findings provide valuable insights into improving the diagnosis of SLE through innovative approaches. AIM: To compare the performance of CLIA and LIA in detecting ANAs in patients with autoimmune diseases, assess their accuracy for SLE, and develop a novel diagnostic model using CLIA-detected antibodies for SLE. METHODS: Specimens have been obtained from 270 patients with clinically diagnosed autoimmune disorders, as well as 130 physical examination specimens. After that, parallel detection of anti-double-stranded DNA (dsDNA) antibody, anti-histone (Histone) antibody, anti-nucleosome (Nuc) antibody, anti-Smith (Sm) antibody, anti-ribosomal P protein (Rib-P) antibody, anti-sicca syndrome A (Ro60) antibody, anti-sicca syndrome A (Ro52) antibody, anti-sicca syndrome (SSB) antibody, anti-centromere protein B (Cenp-B) antibody, anti-DNA topoisomerase 1 (Scl-70) antibody, anti-histidyl tRNA synthetase (Jo-1) antibody, and anti-mitochondrial M2 (AMA-M2) antibody was performed using CLIA and LIA. The detection rates, compliance rates, and diagnostic performance for SLE were compared between the two methodologies, followed by developing a novel diagnostic model for SLE. RESULTS: CLIA and LIA exhibited essentially comparable detection rates for anti-dsDNA antibody, anti-Histone antibody, anti-Nuc antibody, anti-Sm antibody, anti-Rib-P antibody, anti-Ro60 antibody, anti-Ro52 antibody, anti-SSB antibody, anti-Cenp-B antibody, anti-DNAScl-70 antibody, anti-Jo-1 antibody and anti-AMA-M2 antibody (P > 0.05). The two methods displayed identical results for the detection of anti-dsDNA antibody, anti-Histone antibody, anti-Nuc antibody, anti-Sm antibody, anti-Ro60 antibody, anti-Ro52 antibody, anti-SSB antibody, anti-Cenp-B antibody, anti-Scl-70 antibody, and anti-AMA-M2 antibody (Kappa > 0.7, P < 0.05), but showed a moderate agreement for the detection of anti-Rib-P antibody and anti-Jo-1 antibody (Kappa = 0.671 and 0.665; P < 0.05). In addition, the diagnostic performance of these antibodies detected by both methods was similar for SLE. The diagnostic model's area under the curve values, sensitivity, and specificity, including an anti-dsDNA antibody and an anti-Ro60 antibody detected by CLIA, were 0.997, 0.962, and 0.978, respectively. These values were higher than the diagnostic performance of individual antibodies. CONCLUSION: CLIA and LIA demonstrated excellent overall consistency in detecting ANA profiles. A diagnostic model based on CLIA-detected antibodies can successfully contribute to developing a novel technique for detecting SLE.
RESUMEN
Copy number variations (CNVs) are crucial structural genomic variants affecting complex traits in humans and livestock animals. The current study was designed to conduct a comprehensive comparative copy number variation analysis among three breeds, Debao (DB), Baise (BS), and Warmblood (WB), with a specific focus on identifying genomic regions associated with miniature features in horses. Using whole-genome next-generation resequencing data, we identified 18,974 CNVs across 31 autosomes. Among the breeds, we found 4279 breed-specific CNV regions (CNVRs). Baise, Debao, and Warmblood displayed 2978, 986, and 895 distinct CNVRs, respectively, with 202 CNVRs shared across all three breeds. After removing duplicates, we obtained 1545 CNVRs from 26 horse genomes. Functional annotation reveals enrichment in biological functions, including antigen processing, cell metabolism, olfactory conduction, and nervous system development. Debao horses have 970 genes overlapping with CNVRs, possibly causing their small size and mountainous adaptations. We also found that the genes GHR, SOX9, and SOX11 may be responsible for the miniature features of the Debao horse by analyzing their overlapping CNVRs. Overall, this study offers valuable insights into the widespread presence of CNVs in the horse genome. The findings contribute to mapping horse CNVs and advance research on unique miniature traits observed in the Debao horse.
Asunto(s)
Variaciones en el Número de Copia de ADN , Genoma , Humanos , Caballos/genética , Animales , Variaciones en el Número de Copia de ADN/genética , Genoma/genética , Genómica , Fenotipo , Polimorfismo de Nucleótido SimpleRESUMEN
BACKGROUND: Dry eye disease (DED) is a multifactorial disease in ocular surface, and inflammation plays an etiological role. Berberine (BBR) has shown efficacy in treating inflammatory diseases. Yet, there was no adequate information related to the therapeutic effects of BBR for DED. PURPOSE: To detect the effects and explore the potential mechanisms of BBR on DED. STUDY DESIGN: In vitro, in vivo study and network pharmacology analysis were involved. METHOD: The human corneal epithelium cells viability was evaluated with different concentrations of BBR. Dry eye murine model was established by exposing to the desiccating stress, and Ciclosporin (CSA), BBR eye drops or vehicle were topical administration for 7 days. The phenol red cotton tests, Oregon-green-dextran staining and Periodic acid-Schiff staining were performed and evaluated the dry eye after treatment. Inflammation and apoptosis levels of ocular surface were quantified. The potential targets related to berberine and dry eye were collected from databases. The Protein-Protein interaction network analysis and GO & KEGG enrichment analysis were realized by STRING database, Metascape platform and Cytoscape software to find core targets and signaling pathways. The SchrÖdinger software was used to molecular docking and PyMOL software to visualization. Finally, the levels of PI3K/AKT/NFκB and MAPK pathways were detected. RESULT: The data revealed BBR could rescue impaired HCE under hyperosmotic conditions. In addition, BBR eye drops could ameliorate dry eye. And BBR eye drops suppressed the inflammatory factors and CD4+T cells infiltration in conjunctiva. Besides, BBR eye drops protected ocular surface by avoiding the severe apoptosis and decreasing the level of MMP-3 and MMP-9. 148 common targets intersection between BBR and dry eye were found via network pharmacology analysis. Core proteins and core pathways were identified through PPI and GO&KEGG enrichment analysis. Molecular docking displayed excellent binding between BBR and those core targets. Finally, in vivo study verified that BBR eye drops had a therapeutic effect in dry eye by inhibiting PI3K/AKT/NFκB and MAPK pathways. CONCLUSION: The research provided convincing evidence that BBR could be a candidate drug for dry eye.
Asunto(s)
Berberina , Síndromes de Ojo Seco , Ratones , Humanos , Animales , Proteínas Proto-Oncogénicas c-akt/metabolismo , Fosfatidilinositol 3-Quinasas/metabolismo , Berberina/química , Simulación del Acoplamiento Molecular , Apoptosis , FN-kappa B/metabolismo , Inflamación/tratamiento farmacológico , Soluciones Oftálmicas/farmacología , Síndromes de Ojo Seco/tratamiento farmacológico , Síndromes de Ojo Seco/metabolismoRESUMEN
Chronic kidney disease (CKD) is an inflammatory disease characterized by the deterioration of renal function, which imposes a significant burden on the healthcare system. In the recent decades, the ageing of the population and the increase of ozone pollution have accelerated. However, epidemiological associations between long-term ozone exposure and renal function in susceptible populations are understudied. In this study, we aimed to investigate the association of 1 y ozone exposure with renal function among the older adults in Xiamen City, China. We recruited 6024 eligible participants with a median age of 65.00 years, estimated their ozone exposure data, and collected questionnaires on demographic status and lifestyle factors as well as information on healthcare access. A generalized linear model was used to assess the association. An increase of 10 µg/m3 of 1 y ozone exposure was negatively associated with the estimated glomerular filtration rate (eGFR) [-3.12 (95% CI: -4.76, -1.48)]. The associations were stronger in men, non-smokers, and those with hypertension or T2DM. Clinical indicators of high-density lipoprotein, low-density lipoprotein, triglycerides, and total cholesterol were the main mediators to regulate the ozone-renal function association. Our results suggested that long-term ozone exposure is a potential risk factor for renal function in Chinese middle-aged and elderly adults.
Asunto(s)
Pueblos del Este de Asia , Exposición a Riesgos Ambientales , Ozono , Insuficiencia Renal Crónica , Anciano , Humanos , Masculino , Persona de Mediana Edad , Envejecimiento , Pueblo Asiatico , Tasa de Filtración Glomerular , Ozono/toxicidadRESUMEN
Utilizing large-scale epigenomics data, deep learning tools can predict the regulatory activity of genomic sequences, annotate non-coding genetic variants, and uncover mechanisms behind complex traits. However, these tools primarily rely on human or mouse data for training, limiting their performance when applied to other species. Furthermore, the limited exploration of many species, particularly in the case of livestock, has led to a scarcity of comprehensive and high-quality epigenetic data, posing challenges in developing reliable deep learning models for decoding their non-coding genomes. The cross-species prediction of the regulatory genome can be achieved by leveraging publicly available data from extensively studied organisms and making use of the conserved DNA binding preferences of transcription factors within the same tissue. In this study, we introduced DeepSATA, a novel deep learning-based sequence analyzer that incorporates the transcription factor binding affinity for the cross-species prediction of chromatin accessibility. By applying DeepSATA to analyze the genomes of pigs, chickens, cattle, humans, and mice, we demonstrated its ability to improve the prediction accuracy of chromatin accessibility and achieve reliable cross-species predictions in animals. Additionally, we showcased its effectiveness in analyzing pig genetic variants associated with economic traits and in increasing the accuracy of genomic predictions. Overall, our study presents a valuable tool to explore the epigenomic landscape of various species and pinpoint regulatory deoxyribonucleic acid (DNA) variants associated with complex traits.