lncRNA-056298 Regulates GAP43 and Promotes Cardiac Intrinsic Autonomic Nerve Remodelling in a Canine Model of Atrial Fibrillation Induction after Ganglionated Plexus Ablation.

BACKGROUND: Cardiac intrinsic autonomic nerve remodelling has been reported to play an important role in the recurrence of atrial fibrillation after radiofrequency ablation, which significantly affects the long-term efficacy of this procedure. lncRNAs have been shown to interact in the pathological processes underlying heart diseases. However, the roles and mechanisms of lncRNAs in cardiac intrinsic autonomic nerve remodelling during atrial fibrillation reduction after ganglionated plexus ablation remain unknown. OBJECTIVES: The aim of this study was to investigate the mechanism by which lncRNA- 056298 modulates GAP43 to affect cardiac intrinsic autonomic nerve remodelling and facilitate the induction of atrial fibrillation after ganglionated plexus ablation. METHODS: A canine model of right atrial ganglionated plexus ablation was established. The atrial electrophysiological characteristics and neural markers were detected before and after 6 months of ganglionated plexus ablation. High-throughput sequencing was used to screen differentially expressed lncRNAs in target atrial tissues, and lncRNA- 056298 was selected to further explore its effects and mechanisms on cardiac intrinsic autonomic nerve remodelling. RESULTS: The induction rate of atrial fibrillation increased in dogs after ganglionated plexus ablation. Overexpression of lncRNA-056298 by lentivirus can shorten the atrial effective refractory period and increase the induction of atrial fibrillation. lncRNA- 056298 promoted cardiac intrinsic autonomic nerve remodelling via endogenous competition with cfa-miR-185 to induce transcription of its target gene GAP43, thereby affecting the induction of atrial fibrillation. CONCLUSIONS: lncRNA-056298 regulates GAP43 by sponging miR-185, which affects cardiac intrinsic autonomic nerve remodelling and mediates atrial fibrillation induction after ganglionated plexus ablation.

High-fat stimulation induces atrial neural remodeling by reducing NO production via the CRIF1/eNOS/P21 axi.

BACKGROUND: Autonomic remodeling of the atria plays a pivotal role in the development of atrial fibrillation (AF) and exerts a substantial influence on the progression of this condition. Hyperlipidemia is a predisposing factor for AF, but its effect on atrial nerve remodeling is unclear. The primary goal of this study was to explore the possible mechanisms through which the consumption of a high-fat diet (HFD) induces remodeling of atrial nerves, and to identify novel targets for clinical intervention. METHODS: Cell models were created in vitro by subjecting cells to palmitic acid (PA), while rat models were established by feeding them a high-fat diet. To investigate the interplay between cardiomyocytes and nerve cells in a co-culture system, we utilized Transwell cell culture plates featuring a pore size of 0.4 µm. The CCK-8 assay was employed to determine cell viability, fluorescent probe DCFH-DA and flow cytometry were utilized for measuring ROS levels, JC-1 was used to assess the mitochondrial membrane potential, the Griess method was employed to measure the nitric oxide (NO) level in the supernatant, a fluorescence-based method was used to measure ATP levels, and MitoTracker was utilized for assessing mitochondrial morphology. The expression of pertinent proteins was evaluated using western blotting (WB) and immunohistochemistry techniques. SNAP was used to treat nerve cells in order to replicate a high-NO atmosphere, and the level of nitroso was assessed using the iodoTMT reagent labeling method. RESULTS: The study found that cardiomyocytes' mitochondrial morphology and function were impaired under high-fat stimulation, affecting nitric oxide (NO) production through the CRIF1/SIRT1/eNOS axis. In a coculture model, overexpression of eNOS in cardiomyocytes increased NO expression. Moreover, the increased Keap1 nitrosylation within neuronal cells facilitated the entry of Nrf2 into the nucleus, resulting in an augmentation of P21 transcription and a suppression of proliferation. Atrial neural remodeling occurred in the HFD rat model and was ameliorated by increasing myocardial tissue eNOS protein expression with trimetazidine (TMZ). CONCLUSIONS: Neural remodeling is triggered by high-fat stimulation, which decreases the production of NO through the CRIF1/eNOS/P21 axis. Additionally, TMZ prevents neural remodeling and reduces the occurrence of AF by enhancing eNOS expression.

Mechanism of myocardial fibrosis regulation by IGF-1R in atrial fibrillation through the PI3K/Akt/FoxO3a pathway.

Atrial structural remodeling takes on a critical significance to the occurrence and maintenance of atrial fibrillation (AF). As revealed by recent data, insulin-like growth factor-1 receptor (IGF-1R) plays a certain role in tissue fibrosis. In this study, the mechanism of IGF-1R in atrial structural remodeling was examined based on in vivo and in vitro experiments. First, cluster analysis of AF hub genes was conducted, and then the molecular mechanism was proposed by which IGF-1R regulates myocardial fibrosis via the PI3K/Akt/FoxO3a pathway. Subsequently, the mentioned mechanism was verified in human cardiac fibroblasts (HCFs) and rats transduced with IGF-1 overexpression type 9 adeno-associated viruses. The results indicated that IGF-1R activation up-regulated collagen Ⅰ protein expression and Akt phosphorylation in HCFs and rat atrium. The administration of LY294002 reversed the above phenomenon, improved the shortening of atrial effective refractory period, and reduced the increased incidence of AF and atrial fibrosis in rats. The transfection of FoxO3a siRNA reduced the anti-fibrotic effect of LY294002 in HCFs. The above data revealed that activation of IGF-1R takes on a vital significance to atrial structural remodeling by facilitating myocardial fibrosis and expediting the occurrence and maintenance of AF through the regulation of the PI3K/Akt/FoxO3a signaling pathway.

Experimental full-domain mapping of quantum correlation in Clauser-Horne-Shimony-Holt scenarios.

Quantum correlation between two parties serves as an important resource in the surging applications of quantum information. The Bell nonlocality and quantum steering have been proposed to describe non-classical correlations against local-hidden-variable and local-hidden-state theories, respectively. To characterize the two types of non-classical correlations, various nonlocality and steering inequalities have been established, and the amount of inequality violation serves as an important indicator for many entanglement-based tasks. Quantum state tomography has been employed for measuring quantum states, while the method requires intensive computation and does not directly verify either nonlocality or steering over the full domain independent of established theories. Here, we experimentally map the full-domain correlation with bipartite states for nonlocality and quantum steering in CHSH scenarios. The measurement of the maps automatically accounts for detection imperfections. Furthermore, we demonstrate the application of the correlation maps in the entanglement-based quantum key distribution protocol with arbitrary bipartite states. The correlation maps show direct measurements and simple interpretations that can answer fundamental questions about nonlocality and quantum steering as well as contribute to quantum information applications in a straightforward manner.

Deep multiple instance learning for predicting chemotherapy response in non-small cell lung cancer using pretreatment CT images.

The individual prognosis of chemotherapy is quite different in non-small cell lung cancer (NSCLC). There is an urgent need to precisely predict and assess the treatment response. To develop a deep multiple-instance learning (DMIL) based model for predicting chemotherapy response in NSCLC in pretreatment CT images. Two datasets of NSCLC patients treated with chemotherapy as the first-line treatment were collected from two hospitals. Dataset 1 (163 response and 138 nonresponse) was used to train, validate, and test the DMIL model and dataset 2 (22 response and 20 nonresponse) was used as the external validation cohort. Five backbone networks in the feature extraction module and three pooling methods were compared. The DMIL with a pre-trained VGG16 backbone and an attention mechanism pooling performed the best, with an accuracy of 0.883 and area under the curve (AUC) of 0.982 on Dataset 1. While using max pooling and convolutional pooling, the AUC was 0.958 and 0.931, respectively. In Dataset 2, the best DMIL model produced an accuracy of 0.833 and AUC of 0.940. Deep learning models based on the MIL can predict chemotherapy response in NSCLC using pretreatment CT images and the pre-trained VGG16 with attention mechanism pooling yielded better predictions.

Functional Brain Connections Identify Sensorineural Hearing Loss and Predict the Outcome of Cochlear Implantation.

Identification of congenital sensorineural hearing loss (SNHL) and early intervention, especially by cochlear implantation (CI), are crucial for restoring hearing in patients. However, high accuracy diagnostics of SNHL and prognostic prediction of CI are lacking to date. To diagnose SNHL and predict the outcome of CI, we propose a method combining functional connections (FCs) measured by functional magnetic resonance imaging (fMRI) and machine learning. A total of 68 children with SNHL and 34 healthy controls (HC) of matched age and gender were recruited to construct classification models for SNHL and HC. A total of 52 children with SNHL that underwent CI were selected to establish a predictive model of the outcome measured by the category of auditory performance (CAP), and their resting-state fMRI images were acquired. After the dimensional reduction of FCs by kernel principal component analysis, three machine learning methods including the support vector machine, logistic regression, and k-nearest neighbor and their voting were used as the classifiers. A multiple logistic regression method was performed to predict the CAP of CI. The classification model of voting achieves an area under the curve of 0.84, which is higher than that of three single classifiers. The multiple logistic regression model predicts CAP after CI in SNHL with an average accuracy of 82.7%. These models may improve the identification of SNHL through fMRI images and prognosis prediction of CI in SNHL.

Analysis of lung biopsies using the 2015 WHO criteria and detection of sensitizing mutations--a single-institution experience of 5032 cases.

BACKGROUND: A specialized classification for small biopsies was added to the 2015 WHO classification of lung tumors. The purpose of this study is to explore and summarize the experience of applying the newly proposed classifications and criteria to clinical practice. METHODS: We used the 2015 WHO criteria to sort out 5032 small lung biopsies from a group of Chinese patients, and demonstrated their clinicopathological features, mutational status and the relationship between these factors. RESULTS: The most common diagnosis was primary lung carcinoma (3130, 62.2%), among which adenocarcinoma (1421, 28.2%) was the most frequent histological type. The mutational assays using ARMS-PCR technology demonstrated that EGFR was positive in 56.1% cases(499/889, from adenocarcinoma and NSCC, favor adenocarcinoma), ALK in 5.7% cases(12/211, from NSCC, which comprised all the primary lung carcinomas except small cell carcinomas), and ROS1 in 0.9% cases(2/211, from NSCC). Another 898 NSCC specimens went through an immunohistochemical (IHC) examination for ALK (D5F3) and 38 of them were positive (4.2%). The overall mutation rate of ALK was 4.5% (50/1119). There was no significant difference between ARMS-PCR and immunohistochemistry in the positive rate of ALK mutation detection (P = 0.359). EGFR mutations (P = 0.02) and ALK mutations (P < 0.001) both decreased with an increasing patient age. Furthermore, the amount of EGFR mutations was higher in adenocarcinoma (64.1% vs 34.1%, P < 0.001) than in NSCC, favor adenocarcinoma. In contrast, ALK mutations were more common in NSCC, favor adenocarcinoma (4.2% vs 8.4%, P = 0.021). CONCLUSIONS: This single-center study exhibited a large subset of small lung biopsies from a Chinese institution and demonstrated that applying the 2015 WHO classification for small lung biopsies can help predict the mutational status of primary lung carcinomas.

Molecular epidemiological survey of bacterial and parasitic pathogens in hard ticks from eastern China.

Ticks are able to transmit various pathogens-viruses, bacteria, and parasites-to their host during feeding. Several molecular epidemiological surveys have been performed to evaluate the risk of tick-borne pathogens in China, but little is known about pathogens circulating in ticks from eastern China. Therefore, this study aimed to investigate the presence of bacteria and parasites in ticks collected from Xuzhou, a 11258km2 region in eastern China. In the present study, ticks were collected from domestic goats and grasses in urban districts of Xuzhou region from June 2015 to July 2016. After tick species identification, the presence of tick-borne bacterial and parasitic pathogens, including Anaplasma phagocytophilum, Borrelia burgdorferi, Rickettsia sp., Bartonella sp., Babesia sp., and Theileria sp., was established via conventional or nested polymerase chain reaction assays (PCR) and sequence analysis. Finally, a total of 500 questing adult ticks, identified as Haemaphysalis longicornis, were investigated. Among them, 28/500 tick samples (5.6%) were infected with A. phagocytophilum, and 23/500 (4.6%) with Theileria luwenshuni, whereas co-infection with these pathogens was detected in only 1/51 (2%) of all infected ticks. In conclusion, H. longicornis is the dominant tick species in the Xuzhou region and plays an important role in zoonotic pathogen transmission. Both local residents and animals are at a significant risk of exposure to anaplasmosis and theileriosis, due to the high rates of A. phagocytophilum and T. luwenshuni tick infection.

Two-dimensional spatiotemporal focusing of femtosecond pulses and its applications in microscopy.

We demonstrate and theoretically analyze the two-dimensional spatiotemporal focusing of femtosecond pulses by utilizing a two-dimensional spectral disperser. Compared with spatiotemporal focusing with a diffraction grating, it can achieve widefield illumination with better sectioning ability for a multiphoton excitation process. By utilizing paraxial approximation, our analytical method improves the axial confinement ability and identifies that the free spectra range (FSR) of the two-dimensional spectral disperser affects the out-of-focus multiphoton excitation intensity due to the temporal self-imaging effect. Based on our numerical simulation, a FSR of 50 GHz is necessary to reduce the out-of-focus two-photon excitation by 2 orders of magnitude compared with that in a grating-based spatiotemporal focusing scheme for a 90-fs excitation laser pulse. We build a two-dimensional spatiotemporal focusing microscope using a virtually imaged phased array and achieve an axial resolution of 1.3 µm, which outperforms the resolution of conventional spatiotemporal focusing using a grating by a factor of 1.7, and demonstrate better image contrast inside a tissue-like phantom.

Enhancement of lateral resolution and optical sectioning capability of two-photon fluorescence microscopy by combining temporal-focusing with structured illumination.

We demonstrate super-resolution imaging with background fluorescence rejection by interferometric temporal focusing microscopy, in which temporal focusing is combined with structured illumination. The lateral resolution and the optical sectioning capability are simultaneously improved by factors of 1.6 and 1.4, respectively, compared to conventional temporal focusing microscopy. Fluorescent beads (200 nm diameter) that are difficult to distinguish from the background fluorescence in conventional temporal focusing microscopy, are clearly visualized by interferometric temporal focusing microscopy.