ABSTRACT
BACKGROUND: Spodoptera litura is a harmful pest that feeds on more than 80 species of plants, and can be infected and killed by Spodoptera litura nucleopolyhedrovirus (SpltNPV). SpltNPV-C3 is a type C SpltNPV clone, that was observed and collected in Japan. Compared with type A or type B SpltNPVs, SpltNPV-C3 can cause the rapid mortality of S. litura larvae. METHODS: In this study, occlusion bodies (OBs) and occlusion-derived viruses (ODVs) of SpltNPV-C3 were purified, and OBs were observed by scanning electron microscopy (SEM). ODVs were observed under a transmission electron microscope (TEM). RESULTS: Both OBs and ODVs exhibit morphological characteristics typical of nucleopolyhedroviruses (NPVs).The genome of SpltNPV-C3 was sequenced and analyzed; the total length was 148,634 bp (GenBank accession 780,426,which was submitted as SpltNPV-II), with a G + C content of 45%. A total of 149 predicted ORFs were found. A phylogenetic tree of 90 baculoviruses was constructed based on core baculovirus genes. LCâMS/MS was used to analyze the proteins of SpltNPV-C3; 34 proteins were found in the purified ODVs, 15 of which were core proteins. The structure of the complexes formed by per os infectivity factors 1, 2, 3 and 4 (PIF-1, PIF-2, PIF-3 and PIF-4) was predicted with the help of the AlphaFold multimer tool and predicted conserved sequences in PIF-3. SpltNPV-C3 is a valuable species because of its virulence, and the analysis of its genome and proteins in this research will be beneficial for pest control efforts.
Subject(s)
Nucleopolyhedroviruses , Proteome , Animals , Nucleopolyhedroviruses/genetics , Spodoptera , Chromatography, Liquid , Phylogeny , Tandem Mass Spectrometry , BaculoviridaeABSTRACT
BACKGROUND: Neuroimaging studies have revealed abnormal functional interaction during the processing of emotional faces in patients with major depressive disorder (MDD), thereby enhancing our comprehension of the pathophysiology of MDD. However, it is unclear whether there is abnormal directional interaction among face-processing systems in patients with MDD. METHODS: A group of patients with MDD and a healthy control group underwent a face-matching task during functional magnetic resonance imaging. Dynamic causal modelling (DCM) analysis was used to investigate effective connectivity between 7 regions in the face-processing systems. We used a Parametric Empirical Bayes model to compare effective connectivity between patients with MDD and controls. RESULTS: We included 48 patients and 44 healthy controls in our analyses. Both groups showed higher accuracy and faster reaction time in the shape-matching condition than in the face-matching condition. However, no significant behavioural or brain activation differences were found between the groups. Using DCM, we found that, compared with controls, patients with MDD showed decreased self-connection in the right dorsolateral prefrontal cortex (DLPFC), amygdala, and fusiform face area (FFA) across task conditions; increased intrinsic connectivity from the right amygdala to the bilateral DLPFC, right FFA, and left amygdala, suggesting an increased intrinsic connectivity centred in the amygdala in the right side of the face-processing systems; both increased and decreased positive intrinsic connectivity in the left side of the face-processing systems; and comparable task modulation effect on connectivity. LIMITATIONS: Our study did not include longitudinal neuroimaging data, and there was limited region of interest selection in the DCM analysis. CONCLUSION: Our findings provide evidence for a complex pattern of alterations in the face-processing systems in patients with MDD, potentially involving the right amygdala to a greater extent. The results confirm some previous findings and highlight the crucial role of the regions on both sides of face-processing systems in the pathophysiology of MDD.
Subject(s)
Amygdala , Depressive Disorder, Major , Facial Recognition , Magnetic Resonance Imaging , Humans , Depressive Disorder, Major/physiopathology , Depressive Disorder, Major/diagnostic imaging , Male , Female , Adult , Facial Recognition/physiology , Amygdala/diagnostic imaging , Amygdala/physiopathology , Brain/diagnostic imaging , Brain/physiopathology , Neural Pathways/physiopathology , Neural Pathways/diagnostic imaging , Bayes Theorem , Young Adult , Brain Mapping , Facial Expression , Middle Aged , Reaction Time/physiologyABSTRACT
Although the photoresponse cut-off wavelength of Si is about 1100 nm due to the Si bandgap energy, the internal photoemission effect (IPE) of the Au/Si junction in Schottky detector can extend the absorption wavelength, which makes it a promising candidate for the Si-based infrared detector. However, due to low light absorption, low photon-electron interaction, and poor electron injection efficiency, the near-infrared light detection efficiency of the Schottky detector is still insufficient. The synergistic effect of Si nano/microstructures with a strong light trapping effect and nanoscale Au films with surface plasmon enhanced absorption may provide an effective solution for improving the detection efficiency. In this paper, a large-area periodic Si microcone array covered by an Au film has successfully been fabricated by one-time dry etching based on the mature polystyrene microspheres lithography technique and vacuum thermal deposition, and its properties for hot electron-based near infrared photodetection are investigated. Optical measurements show that the 20 nm-thick Au covered Si microcone array exhibits a low reflectance and a strong absorption (about 85%) in wide wavelength range (900-2500 nm), and the detection responsivity can reach a value as high as 17.1 and 7.0 mA W-1at 1200 and 1310 nm under the front illumination, and 35.9 mA W-1at 1310 nm under the back illumination respectively. Three-dimensional finite difference time domain (3D-FDTD) simulation results show that the enhanced local electric field in the Au layer distributes near the air/Au interface under the front illumination and close to the Au/Si interface under the back illumination. The back illumination favors the injection of photo-generated hot electrons in Au layer into Si, which can explain the higher responsivity under the back illumination. Our research is expected to promote the practical application of Schottky photodetectors to Si-compatible near infrared photodetectors.
ABSTRACT
BACKGROUND: Theoretical and empirical evidence indicates the critical role of the default mode network (DMN) in the pathophysiology of the bipolar disorder (BD). This study aims to identify the specific brain regions of the DMN that is impaired in patients with BD. METHODS: A total of 56 patients with BD and 71 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Three commonly used functional indices, i.e., fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC), were utilized to identify the brain region showing abnormal spontaneous brain activity in patients with BD. Then, this region served as the seed region for resting-state functional connectivity (rsFC) analysis. RESULTS: Compared to the HC group, the BD group showed reduced fALFF, ReHo, and DC values in the left precuneus. Moreover, patients exhibited decreased rsFCs within the left precuneus and between the left precuneus and the medial prefrontal cortex. Additionally, there was diminished negative connectivity between the left precuneus and the left putamen, extending to the left insula (putamen/insula). The abnormalities in DMN functional connectivity were confirmed through various analysis strategies. CONCLUSIONS: Our findings provide convergent evidence for the abnormalities in the DMN, particularly located in the left precuneus. Decreased functional connectivity within the DMN and the reduced anticorrelation between the DMN and the salience network are found in patients with BD. These findings suggest that the DMN is a key aspect for understanding the neural basis of BD, and the altered functional patterns of DMN may be a potential candidate biomarker for diagnosis of BD.
Subject(s)
Bipolar Disorder , Default Mode Network , Magnetic Resonance Imaging , Humans , Bipolar Disorder/physiopathology , Bipolar Disorder/diagnostic imaging , Female , Male , Adult , Default Mode Network/physiopathology , Default Mode Network/diagnostic imaging , Nerve Net/physiopathology , Nerve Net/diagnostic imaging , Parietal Lobe/physiopathology , Parietal Lobe/diagnostic imaging , Connectome/methods , Prefrontal Cortex/physiopathology , Prefrontal Cortex/diagnostic imaging , Case-Control Studies , Young Adult , Middle Aged , Brain/physiopathology , Brain/diagnostic imaging , Brain MappingABSTRACT
BACKGROUND: Bipolar disorder (BD) is a complex mental illness characterized by different mood states, including depression, mania/hypomania, and euthymia. This study aimed to comprehensively evaluate dynamic changes in intrinsic brain activity by using dynamic fractional amplitude of low-frequency fluctuations (dfALFF) and dynamic degree centrality (dDC) in patients with BD euthymia or depression and healthy individuals. METHODS: The resting-state functional magnetic resonance imaging data were analyzed from 37 euthymic and 28 depressed patients with BD, as well as 85 healthy individuals. Using the sliding-window method, the dfALFF and dDC were calculated for each participant. These values were compared between the 3 groups using one-way analysis of variance (ANOVA). Additional analyses were conducted using different window lengths, step width, and window type to ensure the reliability of the results. RESULTS: The euthymic group showed significantly lower dfALFF and dDC values of the left and right cerebellum posterior lobe compared with the depressed and control groups (cluster level PFWE < 0.05), while the latter two groups were comparable. Brain regions showing significant group differences in the dfALFF analysis overlapped with those with significant differences in the dDC analysis. These results were consistent across different window lengths, step width, and window type. CONCLUSIONS: These findings suggested that patients with euthymic BD exhibit less flexibility of temporal functional activities in the cerebellum posterior lobes compared to either depressed patients or healthy individuals. These results could contribute to the development of neuropathological models of BD, ultimately leading to improved diagnosis and treatment of this complex illness.
Subject(s)
Bipolar Disorder , Humans , Bipolar Disorder/diagnosis , Reproducibility of Results , Brain , Cyclothymic Disorder , Cerebellum/diagnostic imaging , Magnetic Resonance Imaging/methodsABSTRACT
A spectrum of immune states resulting from tumor resident macrophages and T-lymphocytes in the solid tumor microenvironment correlates with patient outcomes. We hypothesized that in gastric cancer (GC), macrophages in a polarized immunosuppressive transcriptional state would be prognostic of poor survival. We derived transcriptomic signatures for M2 (M2TS, MRC1; MS4A4A; CD36; CCL13; CCL18; CCL23; SLC38A6; FGL2; FN1; MAF) and M1 (M1TS, CCR7; IL2RA; CXCL11; CCL19; CXCL10; PLA1A; PTX3) macrophages, and cytolytic T-lymphocytes (CTLTS, GZMA; GZMB; GZMH; GZMM; PRF1). Primary GC in a TCGA stomach cancer dataset was evaluated for signature expressions, and a log-rank test determined overall survival (OS) and the disease-free interval (DFI). In 341 TCGA GC entries, high M2TS expression was associated with histological types and later stages. Low M2TS expression was associated with significantly better 5-year OS and DFI. We validated M2TS in prospectively collected peritoneal fluid of a GC patient cohort (n = 28). Single-cell RNA sequencing was used for signature expression in CD68+CD163+ cells and the log-rank test compared OS. GC patients with high M2TS in CD68+CD163+ cells in their peritoneal fluid had significantly worse OS than those with low expression. Multivariate analyses confirmed M2TS was significantly and independently associated with survival. As an independent predictor of poor survival, M2TS may be prognostic in primary tumors and peritoneal fluid of GC patients.
Subject(s)
Stomach Neoplasms , Humans , Stomach Neoplasms/genetics , Peritoneum , Macrophages, Peritoneal , Biomarkers , Macrophages , Tumor Microenvironment/genetics , FibrinogenABSTRACT
In both the manufacturing and chemical industries, benzoquinone is a crucial chemical product. A perfect and economical method for making benzoquinone is the electrochemical oxidation of phenol, thanks to the traditional thermal catalytic oxidation of phenol process requires high cost, serious pollution and harsh reaction conditions. Here, a unique heterostructure electrocatalyst on nickel foam (NF) consisting of nickel sulfide and nickel oxide (Ni9S8-Ni15O16/NF) was produced, and this catalyst exhibited a low overpotential (1.35â V vs. RHE) and prominent selectivity (99 %) for electrochemical phenol oxidation reaction (EOP). Ni9S8-Ni15O16/NF is beneficial for lowering the reaction energy barrier and boosting reactivity in the EOP process according to density functional theory (DFT) calculations. Additionally, an alkali/acid hybrid flow cell was successfully established by connecting Ni9S8-Ni15O16/NF and commercial RuIr/Ti in series to catalyze phenol oxidation in an alkaline medium and hydrogen evolution in an acid medium, respectively. A cell voltage of only 0.60â V was applied to produce a current density of 10â mA cm-2. Meanwhile, the system continued to operate at 0.90â V for 12â days, showing remarkable long-term stability. The unique configuration of the acid-base hybrid flow cell electrolyzer provides valuable guidance for the efficient and environmentally friendly electrooxidation of phenol to benzoquinone.
ABSTRACT
Purpose: COVID-19 is rampant throughout the world, which has caused great damage to human lives and seriously hindered the development of the global economy. Aiming at the treatment of SARS-CoV-2, in this study, we proposed a novel fenobody strategy based on ferritin (Fe) self-assembly technology. Methods: The neutralizing nanobody H11-D4 of SARS-CoV-2 fused to the C-terminus of end-modified human ferritin was expressed in E. coli and silkworm baculovirus expression systems. A large number of nanoparticles were successfully self-assembled in silkworms, while relatively few nanoparticles can be observed in the treated products from E. coli by electron microscopy. Subsequently, the fenobody's expression level and neutralizing activity were then evaluated. Results: The results showed that the IC50 of H11-D4 and fenobody Fe-H11-D4 expressed in E. coli were 171.1 nmol L-1 and 20.87 nmol L-1, respectively. However, the IC50 of Fe-HD11-D4 expressed in silkworms was 1.46 nmol L-1 showing better neutralization activity. Conclusion: Therefore, fenobodies can be well self-assembled in silkworm baculovirus expression system, and ferritin self-assembly technology can effectively improve nanobody neutralization activity.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Ferritins , Escherichia coli , Antibodies, Neutralizing , Antibodies, ViralABSTRACT
Strain HUAS CB01T was a novel actinobacterium which was isolated from the rhizosphere soil of Cathaya argyrophylla, Chengbu Miao Autonomous County of Hunan Province, China. The strain formed well-growing substrate mycelium, diffusible pigments, and aerial mycelium, and differentiated into spiral-type spore chains composed of smooth-surface rod-shaped spores. Phylogenetic analysis on account of 16 S rRNA gene sequence demonstrated the strain HUAS CB01T was a member of the genus Streptomyces and had a close relationship with Streptomyces wuyuanensis CGMCC 4.7042 T (100%) and Streptomyces marianii ICN19T (99.86%). Genome-based comparisons indicated that strain HUAS CB01T could be distinctly different from its closest species, Streptomyces wuyuanensis CGMCC 4.7042 T, Streptomyces marianii ICN19T, with ANIm and dDDH results of 92.78% and 45.90%, 92.22% and 43.30%, respectively, far less than 96.7 and 70% cut-off points recommended for delineating species. The main cellular fatty acids concluded anteiso-C15:0, iso-C14:0, iso-C16:0, C16:0 and C16:1 2OH. The menaquinones were MK-9(H4), MK-9(H6) and MK-9(H8) and the whole-cell sugars consisted of ribose and mannose. The polar lipids included phosphatidyl ethanolamine, diphosphatidylglycerol, phosphatidylglycerol, mannosides and unidentified phospholipids. According to these genotypic and phenotypic characteristics, strain HUAS CB01T can be distinguished and representative to be a novel species of the genus Streptomyces, for which the name Streptomyces chengbuensis is proposed. The type strain is HUAS CB01T ( = MCCC 1K08666T = JCM 36277 T).
ABSTRACT
The application of traditional lateral flow immunoassay (LFIA)-based gold nanoparticles (AuNPs) to measure traces of target chemicals is usually challenging. In this study, we developed an integrated strategy based on molecular engineering and the spatial confinement of nanoparticles (NPs) to obtain ultrahigh quantum yields (QYs) of aggregation-induced emission (AIE) fluorescence NPs and employed them for the highly sensitive detection of T-2 toxin on the LFIA platform. Tetraethyl-4,4',4â³,4â´-(ethene-1,1,2,2-tetrayl)tetrabenzoate (TCPEME), an AIE luminogen, was designed using molecular engineering to lower the energy gap, achieving higher QYs (26.26%) than previous AIEgens (13.02%). Subsequently, TCPEME-doped fluorescence NPs (TFNPs) achieved ultrahigh QYs, up to 84.55%, which were generated from the strong restriction of the NP state, efficiently suppressing nonradiative relaxation channels verified by ultrafast electron dynamics. On the LFIA platform, the sensitivity of the designed TFNP-based LFIA (TFNP-LFIA) was 10.4-fold and 4.3-fold more sensitive than that of the AuNP-LFIA and TPENP-LFIA for detecting the T-2 toxin, respectively. In addition, TFNP-LFIA was used for detecting T-2 toxin in samples and showed satisfactory recoveries (79.5 to 122.0%) with CV (1.49 to 11.75%), which implied excellent application potential for TFNP-LFIA. Overall, dual improvement of the molecule in fluorescence performance originating from the molecular engineering and spatial confinement of NPs could be an efficient tool for promoting the development of high-performance reporters in LFIA.
Subject(s)
Metal Nanoparticles , T-2 Toxin , Gold/chemistry , Metal Nanoparticles/chemistry , Immunoassay , Limit of DetectionABSTRACT
BACKGROUND: Patients with major depressive disorder (MDD) have abnormal functional interaction among large-scale brain networks, indicated by aberrant effective connectivity of the default mode network (DMN), salience network (SN), and dorsal attention network (DAN). However, it remains unclear whether antidepressants can normalize the altered effective connectivity in MDD. METHODS: In this study, we collected resting-state functional magnetic resonance imaging data from 46 unmedicated patients with MDD at baseline and after 12 weeks of escitalopram treatment. We also collected data from 58 healthy controls (HCs) at the same time point with the same interval. Using spectral dynamic causal modeling and parametric empirical Bayes, we examined group differences, time effect and their interaction on the casual interactions among the regions of interest in the three networks. RESULTS: Compared with HCs, patients with MDD showed increased positive (excitatory) connections within the DMN, decreased positive connections within the SN and DAN, decreased absolute value of negative (inhibitory) connectivity from the SN and DAN to the DMN, and decreased positive connections between the DAN and the SN. Furthermore, we found that six connections related to the DAN showed decreased group differences in effective connectivity between MDD and HCs during follow-up compared to the baseline. CONCLUSIONS: Our findings suggest that escitalopram therapy can partly improve the disrupted effective connectivity among high-order brain functional networks in MDD. These findings deepened our understanding of the neural basis of antidepressants' effect on brain function in patients with MDD.
Subject(s)
Depressive Disorder, Major , Humans , Depressive Disorder, Major/diagnostic imaging , Depressive Disorder, Major/drug therapy , Escitalopram , Bayes Theorem , Brain Mapping/methods , Magnetic Resonance Imaging/methods , Neural Pathways/diagnostic imaging , Brain/diagnostic imaging , Antidepressive AgentsABSTRACT
Si-based emitters have been of great interest as an ideal light source for monolithic optical-electronic integrated circuits (MOEICs) on Si substrates. However, the general Si-based material is a diamond structure of cubic lattice with an indirect band gap, which cannot emit light efficiently. Here, hexagonal-Ge (H-Ge) nanostructures within a light-emitting metasurface consisting of a cubic-SiGe nanodisk array are reported. The H-Ge nanostructure is naturally formed within the cubic-Ge epitaxially grown on Si (001) substrates due to the strain-induced nanoscale crystal structure transformation assisted by far-from-equilibrium growth conditions. The direct-bandgap features of H-Ge nanostructures are observed and discussed, including a rather strong and linearly power-dependent photoluminescence (PL) peak around 1562 nm at room temperature and temperature-insensitive PL spectrum near room temperature. Given the direct-bandgap nature, the heterostructure of H-Ge/C-Ge, and the compatibility with the sophisticated Si technology, the H-Ge nanostructure has great potential for innovative light sources and other functional devices, particularly in Si-based MOEICs.
ABSTRACT
The aim of this study is to compare ecologically-valid measure (the Cambridge Prospective Memory Test, CAMPROMPT) and laboratory measure (eye-tracking paradigm) in assessing prospective memory (PM) in individuals with schizophrenia spectrum disorders (SSDs). In addition, eye-tracking indices are used to examine the relationship between PM and other cognitive domains in SSDs patients. Initially, the study sample was formed by 32 SSDs patients and 32 healthy control subjects (HCs) who were matched in sociodemographic profile and the performance on CAMPROMPT. An eye-tracking paradigm was employed to examine the differences in PM accuracy and key cognitive processes (e.g., cue monitoring) between the two groups. Additional 31 patients were then recruited to investigate the relationship between PM cue monitoring, other cognitive functions, and the severity of clinical symptoms within the SSDs group. The monitoring of PM cue was reflected in total fixation time and total fixation counts for distractor words. Cognitive functions were assessed using the Chinese version of the MATRICS Consensus Cognitive Battery (MCCB). The Positive and Negative Syndrome Scale (PANSS) was applied to assess psychopathology. SSDs patients exhibited fewer total fixation counts for distractor words and lower PM accuracy compared to HCs, even though they were priori matched on CAMPROMPT. Correlation analysis within the SSDs group (63 cases) indicated a negative correlation between PM accuracy and PANSS total score, and a positive correlation with working memory and attention/vigilance. Regression analysis within the SSDs group revealed that higher visual learning and lower PANSS total scores independently predicted more total fixation counts on distractor words. Impairment in cue monitoring is a critical factor in the PM deficits in SSDs. The eye-tracking laboratory paradigm has advantages over the ecologically-valid measurement in identifying the failure of cue detection, making it a more sensitive tool for PM deficits in patients with SSDs.
ABSTRACT
Cardiac fibrosis under chronic pressure overload is an end-stage adverse remodeling of heart. However, current heart failure treatments barely focus on anti-fibrosis and the effects are limited. We aimed to seek for a cardiac abundant and cardiac fibrosis specific piRNA, exploring its underlying mechanism and therapeutic potential. Whole transcriptome sequencing and the following verification experiments identified a highly upregulated piRNA (piRNA-000691) in transverse aortic constriction (TAC) mice, TAC pig, and heart failure human samples, which was abundant in heart and specifically expressed in cardiac fibroblasts. CFRPi was gradually increased along with the progression of heart failure, which was illustrated to promote cardiac fibrosis by gain- and loss-of-function experiments in vitro and in vivo. Knockdown of CFRPi in mice alleviated cardiac fibrosis, reversed decline of systolic and diastolic functions from TAC 6 weeks to 8 weeks. Mechanistically, CFRPi inhibited APLN, a protective peptide that increased in early response and became exhausted at late stage. Knockdown of APLN in vitro notably aggravated cardiac fibroblasts activation and proliferation. In vitro and in vivo evidence both indicated Pi3k-AKT-mTOR as the downstream effector pathway of CFRPi-APLN interaction. Collectively, we here identified CFPPi as a heart abundant and cardiac fibrosis specific piRNA. Targeting CFRPi resulted in a sustainable increase of APLN and showed promising therapeutical prospect to alleviate fibrosis, rescue late-stage cardiac dysfunction, and prevent heart failure.
Subject(s)
Cardiomyopathies , Heart Failure , Mice , Humans , Animals , Swine , Piwi-Interacting RNA , Phosphatidylinositol 3-Kinases/metabolism , Phosphatidylinositol 3-Kinases/pharmacology , Phosphatidylinositol 3-Kinases/therapeutic use , Signal Transduction , Heart Failure/genetics , Heart Failure/metabolism , Cardiomyopathies/metabolism , Fibroblasts/pathology , Fibrosis , Mice, Inbred C57BL , Ventricular Remodeling , Myocardium/pathologyABSTRACT
Thoracic echocardiography (TTE) can provide sufficient cardiac structure information, evaluate hemodynamics and cardiac function, and is an effective method for atrial septal defect (ASD) examination. This paper aims to study a deep learning method based on cardiac ultrasound video to assist in ASD diagnosis. We chose four standard views in pediatric cardiac ultrasound to identify atrial septal defects; the four standard views were as follows: subcostal sagittal view of the atrium septum (subSAS), apical four-chamber view (A4C), the low parasternal four-chamber view (LPS4C), and parasternal short-axis view of large artery (PSAX). We enlist data from 300 children patients as part of a double-blind experiment for five-fold cross-validation to verify the performance of our model. In addition, data from 30 children patients (15 positives and 15 negatives) are collected for clinician testing and compared to our model test results (these 30 samples do not participate in model training). In our model, we present a block random selection, maximal agreement decision, and frame sampling strategy for training and testing respectively, resNet18 and r3D networks are used to extract the frame features and aggregate them to build a rich video-level representation. We validate our model using our private dataset by five cross-validation. For ASD detection, we achieve 89.33 ± 3.13 AUC, 84.95 ± 3.88 accuracy, 85.70 ± 4.91 sensitivity, 81.51 ± 8.15 specificity, and 81.99 ± 5.30 F1 score. The proposed model is a multiple instances learning-based deep learning model for video atrial septal defect detection which effectively improves ASD detection accuracy when compared to the performances of previous networks and clinical doctors.
Subject(s)
Deep Learning , Echocardiography , Heart Septal Defects, Atrial , Humans , Heart Septal Defects, Atrial/diagnostic imaging , Child , Echocardiography/methods , Female , Male , Child, Preschool , Double-Blind Method , Infant , Image Interpretation, Computer-Assisted/methods , Video Recording , AdolescentABSTRACT
[This corrects the article DOI: 10.3389/fped.2023.1159342.].