ABSTRACT
Somatic mutations have been identified in 10% to 63% of focal cortical dysplasia type II samples, primarily linked to the mTOR pathway. When the causative genetic mutations are not identified, this opens the possibility of discovering new pathogenic genes or pathways that could be contributing to the condition. In our previous study, we identified a novel candidate pathogenic somatic variant of IRS-1 c.1791dupG in the brain tissue of a child with focal cortical dysplasia type II. This study further explored the variant's role in causing type II focal cortical dysplasia through in vitro overexpression in 293T and SH-SY5Y cells and in vivo evaluation via in utero electroporation in fetal brains, assessing effects on neuronal migration, morphology, and network integrity. It was found that the mutant IRS-1 variant led to hyperactivity of p-ERK, increased cell volume, and was predominantly associated with the MAPK signaling pathway. In vivo, the IRS-1 c.1791dupG variant induced abnormal neuron migration, cytomegaly, and network hyperexcitability. Notably, the ERK inhibitor GDC-0994, rather than the mTOR inhibitor rapamycin, effectively rescued the neuronal defects. This study directly highlighted the ERK signaling pathway's role in the pathogenesis of focal cortical dysplasia II and provided a new therapeutic target for cases of focal cortical dysplasia II that are not treatable by rapamycin analogs.
Subject(s)
Insulin Receptor Substrate Proteins , MAP Kinase Signaling System , Mutation , Humans , Insulin Receptor Substrate Proteins/genetics , Insulin Receptor Substrate Proteins/metabolism , MAP Kinase Signaling System/genetics , Animals , Malformations of Cortical Development, Group I/genetics , Malformations of Cortical Development, Group I/metabolism , Brain/metabolism , Brain/pathology , Neurons/metabolism , Neurons/pathology , Cell Movement/genetics , HEK293 Cells , Female , Focal Cortical Dysplasia , EpilepsyABSTRACT
It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is present in patients with schizophrenia, yet there are inconsistencies in the relevant findings. Moreover, little is known about their association with brain gene expression profiles. In this study, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control VMHC differences from both the discovery (meta-analysis, including 9 studies with a total of 386 patients and 357 controls) and replication (separate group-level comparisons within two datasets, including a total of 258 patients and 287 controls) phases were performed to identify genes associated with VMHC alterations. Enrichment analyses were conducted to characterize the biological functions and specific expression of identified genes, and Neurosynth decoding analysis was performed to examine the correlation between cognitive-related processes and VMHC alterations in schizophrenia. In the discovery and replication phases, patients with schizophrenia exhibited consistent VMHC changes compared to controls, which were correlated with a series of cognitive-related processes; meta-regression analysis revealed that illness duration was negatively correlated with VMHC abnormalities in the cerebellum and postcentral/precentral gyrus. The abnormal VMHC patterns were stably correlated with 1287 genes enriched for fundamental biological processes like regulation of cell communication, nervous system development, and cell communication. In addition, these genes were overexpressed in astrocytes and immune cells, enriched in extensive cortical regions and wide developmental time windows. The present findings may contribute to a more comprehensive understanding of the molecular mechanisms underlying VMHC alterations in patients with schizophrenia.
Subject(s)
Schizophrenia , Humans , Schizophrenia/diagnostic imaging , Schizophrenia/genetics , Magnetic Resonance Imaging , Brain , Brain Mapping , Gene ExpressionABSTRACT
There is a wide variety of cancer cells that can be linked to the presence of TPX2. However, there is not a lot of evidence regarding its role in the development and maintenance of clear cell renal cell carcinoma (ccRCC). In our study, bioinformatics analysis was performed to obtain differentially expressed mRNAs and miR-NAs in ccRCC. Survival curves predicted correlation of TPX2 expression with patient survival. The upstream regulatory miRNA of TPX2 was predicted to be miRNA-27b-3p through database, and dual luciferase assay verified the targeted relationship. qRT-PCR and Western blot were employed for examination of TPX2 mRNA and protein expression in ccRCC cells. Proliferation, invasion, migration and cell cycle were detected by CCK-8, colony formation, wound healing, Transwell, and flow cytometry assays. The results showed that TPX2 showed very high expression in ccRCC, and patients with higher TPX2 expression had shorter relative survival. Low miRNA-27b-3p expression was found in ccRCC. Knockdown of TPX2 or forced expression of miRNA-27b-3p in ccRCC cells inhibited cell proliferation, migration, invasion, and arrested cell division in G0/G1 phase. Dual luciferase reporter presented that miRNA-27b-3p targeted TPX2 to inhibit its expression. Rescue experiments demonstrated that the miRNA-27b-3p/ TPX2 axis affected the biological functions of ccRCC cells. Concurrent overexpression of miRNA-27b-3p and TPX2 inhibited the facilitating effect of TPX2 on ccRCC cell growth. The results revealed novel regulatory mechanisms involved in ccRCC progression, hoping that it may spark an insight for later discovery about the new therapeutic targets for ccRCC.
Subject(s)
Carcinoma, Renal Cell , Carcinoma , Kidney Neoplasms , MicroRNAs , Humans , Carcinoma, Renal Cell/genetics , Carcinoma, Renal Cell/pathology , Cell Cycle Proteins/genetics , Cell Line, Tumor , Cell Movement/genetics , Cell Proliferation/genetics , Kidney Neoplasms/genetics , Kidney Neoplasms/pathology , Luciferases , MicroRNAs/genetics , MicroRNAs/metabolism , Microtubule-Associated Proteins/geneticsABSTRACT
INTRODUCTION: Cardioneuroablation (CNA) has proven effectiveness in addressing hypervagotonia symptoms, such as neurocardiogenic syncope. METHODS AND RESULTS: In this case, we present the first-time application of CNA in a case of vago-glossopharyngeal neuralgia (VGPN). A 59-year-old female with near-syncope, sinus bradycardia, and sinus pauses triggered by recurrent right-sided neck pain was diagnosed with VGPN. The patient underwent successful treatment with carbamazepine and CNA. Subsequent follow-up revealed the sustained absence of sinus bradycardia or pauses, even upon neck pain resurgence after discontinuing carbamazepine. CONCLUSION: In this patient, CNA successfully prevented pauses associated with VGPN, avoiding permanent pacemaker implantation.
ABSTRACT
OBJECTIVES: To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR). METHODS: In this prospective study, two groups of 40 participants each underwent abdominal contrast-enhanced scans with full-dose SECT (120-kVp images, DLIR and IR algorithms) or reduced-dose DECT (40- to 60-keV virtual monochromatic images [VMIs], DLIR algorithm), with 122 and 106 metastases, respectively. Groups were matched by age, sex ratio, body mass index, and cross-sectional area. Noise power spectrum of liver images and task-based transfer function of metastases were calculated to assess the noise texture and low-contrast resolution. The image noise, signal-to-noise ratios (SNR) of liver and portal vein, liver-to-lesion contrast-to-noise ratio (LLR), lesion conspicuity, lesion detection rate, and the subjective image quality metrics were compared between groups on 1.25-mm reconstructed images. RESULTS: Compared to 120-kVp images with IR, 40- and 50-keV VMIs with DLIR showed similar noise texture and LLR, similar or higher image noise and low-contrast resolution, improved SNR and lesion conspicuity, and similar or better perceptual image quality. When compared to 120-kVp images with DLIR, 50-keV VMIs with DLIR had similar low-contrast resolution, SNR, LLR, lesion conspicuity, and perceptual image quality but lower frequency noise texture and higher image noise. For the detection of hepatic metastases, reduced-dose DECT by 34% maintained observer lesion detection rates. CONCLUSION: DECT assisted with DLIR enables a 34% dose reduction for detecting hepatic metastases while maintaining comparable perceptual image quality to full-dose SECT. CLINICAL RELEVANCE STATEMENT: Reduced-dose dual-energy CT with deep learning image reconstruction is as accurate as standard-dose single-energy CT for the detection of liver metastases and saves more than 30% of the radiation dose. KEY POINTS: ⢠The 40- and 50-keV virtual monochromatic images (VMIs) with deep learning image reconstruction (DLIR) improved lesion conspicuity compared with 120-kVp images with iterative reconstruction while providing similar or better perceptual image quality. ⢠The 50-keV VMIs with DLIR provided comparable perceptual image quality and lesion conspicuity to 120-kVp images with DLIR. ⢠The reduction of radiation by 34% by DLIR in low-keV VMIs is clinically sufficient for detecting low-contrast hepatic metastases.
Subject(s)
Deep Learning , Liver Neoplasms , Humans , Prospective Studies , Liver Neoplasms/diagnostic imaging , Tomography, X-Ray Computed/methods , Algorithms , Radiographic Image Interpretation, Computer-Assisted/methods , Radiation Dosage , Image Processing, Computer-Assisted/methodsABSTRACT
OBJECTIVE: This study aimed to evaluate the image quality and lesion conspicuity of the deep learning image reconstruction (DLIR) algorithm compared with standard image reconstruction algorithms on abdominal enhanced computed tomography (CT) scanning with a wide range of body mass indexes (BMIs). METHODS: A total of 112 participants who underwent contrast-enhanced abdominal CT scans were divided into three groups according to BMIs: the 80-kVp group (BMI ≤ 23.9 kg/m2), 100-kVp group (BMI 24-28.9 kg/m2), and 120-kVp group (BMI ≥ 29 kg/m2). All images were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction-V of 50% level (IR), and DLIR at low, medium, and high levels (DL, DM, and DH, respectively). Subjective noise, artifact, overall image quality, and low- and high-contrast hepatic lesion conspicuity were all graded on a 5-point scale. The CT attenuation value (in HU), image noise, and contrast-to-noise ratio (CNR) were quantified and compared. RESULTS: DM and DH improved the qualitative and quantitative parameters compared with FBP and IR for all three BMI groups. DH had the lowest image noise and highest CNR value, while DM had the highest subjective overall image quality and low- and high-contrast lesion conspicuity scores for the three BMI groups. Based on the FBP, the improvement in image quality and lesion conspicuity of DM and DH images was greater in the 80-kVp group than in the 100-kVp and 120-kVp groups. CONCLUSION: For all BMIs, DLIR improves both image quality and hepatic lesion conspicuity, of which DM would be the best choice to balance both. CLINICAL RELEVANCE STATEMENT: The study suggests that utilizing DLIR, particularly at the medium level, can significantly enhance image quality and lesion visibility on abdominal CT scans across a wide range of BMIs. KEY POINTS: ⢠DLIR improved the image quality and lesion conspicuity across a wide range of BMIs. ⢠DLIR at medium level had the highest subjective parameters and lesion conspicuity scores among all reconstruction levels. ⢠On the basis of the FBP, the 80-kVp group had improved image quality and lesion conspicuity more than the 100-kVp and 120-kVp groups.
Subject(s)
Deep Learning , Humans , Body Mass Index , Tomography, X-Ray Computed/methods , Algorithms , Phantoms, Imaging , Radiographic Image Interpretation, Computer-Assisted/methods , Radiation Dosage , Image Processing, Computer-AssistedABSTRACT
OBJECTIVES: To develop a CT-based radiomics model for preoperative prediction of lymph node (LN) metastasis in perihilar cholangiocarcinoma (pCCA). METHODS: The study enrolled consecutive pCCA patients from three independent Chinese medical centers. The Boruta algorithm was applied to build the radiomics signature for the primary tumor and LN. The k-means algorithm was employed to cluster the selected LNs based on the radiomics signature LN. Support vector machines were used to construct the prediction models. The diagnostic efficiency was measured by the area under the receiver operating characteristic curve (AUC). The optimal model was evaluated in terms of calibration, clinical usefulness, and prognostic value. RESULTS: A total of 214 patients were included in the study (mean age: 61.6 years ± 9.4; 130 male). The selected LNs were classified into two clusters, which were significantly correlated with LN metastasis in all cohorts (p < 0.001). The model incorporated the clinical risk factors, radiomics signature primary tumor, and the LN cluster obtained the best discrimination, with AUC values of 0.981 (95% CI: 0.962-1), 0.896 (95% CI: 0.810-0.982), and 0.865 (95% CI: 0.768-0.961) in the training, internal validation, and external validation cohorts, respectively. High-risk patients predicted by the optimal model had shorter overall survival than low-risk patients (median, 13.7 vs. 27.3 months, p < 0.001). CONCLUSIONS: The study proposed a radiomics model with good performance to predict LN metastasis in pCCA. As a noninvasive preoperative prediction tool, this model may help in patient risk stratification and personalized treatment. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics model accurately predicts lymph node metastasis in perihilar cholangiocarcinoma patients. This noninvasive preoperative tool can aid in patient risk stratification and personalized treatment, potentially improving patient outcomes. KEY POINTS: ⢠The radiomics model based on contrast-enhanced CT is a useful tool for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma. ⢠Radiomics features extracted from lymph nodes show great potential for predicting lymph node metastasis. ⢠The study is the first to identify a lymph node phenotype with a high probability of metastasis based on radiomics.
Subject(s)
Bile Duct Neoplasms , Klatskin Tumor , Humans , Male , Middle Aged , Lymphatic Metastasis/pathology , Klatskin Tumor/diagnostic imaging , Klatskin Tumor/surgery , Radiomics , Retrospective Studies , Tomography, X-Ray Computed/methods , Lymph Nodes/pathology , Bile Duct Neoplasms/diagnostic imaging , Bile Duct Neoplasms/surgery , Bile Duct Neoplasms/pathologyABSTRACT
Evidence highlights that dopamine (DA) system dysregulation and prefrontal cortex (PFC) dysfunction may underlie the pathophysiology of schizophrenia. However, the associations among DA genes, PFC morphometry, and schizophrenia have not yet been fully clarified. Based on the brain gene expression dataset from Allen Human Brain Atlas and structural magnetic resonance imaging data (NDIS = 1727, NREP = 408), we first identified 10 out of 22 PFC subregions whose gray matter volume (GMV) covariance profiles were reliably associated with their DA genes coexpression profiles, then four out of the identified 10 PFC subregions demonstrated abnormally increased GMV covariance with the hippocampus, insula, and medial frontal areas in schizophrenia patients (NCASE = 100; NCONTROL = 102). Moreover, based on a schizophrenia postmortem expression dataset, we found that the DA genes coexpression of schizophrenia was significantly reduced between the middle frontal gyrus and hippocampus, in which 21 DA genes showed significantly unsynchronized expression changes, and the 21 genes' brain expression were enriched in brain activity invoked by working memory, reward, speech production, and episodic memory. Our findings indicate the DA genes selectively regulate the structural covariance of PFC subregions by their coexpression profiles, which may underlie the disrupted GMV covariance and impaired cognitive functions in schizophrenia.
Subject(s)
Dopamine , Gene Expression Regulation , Gray Matter , Prefrontal Cortex , Schizophrenia , Prefrontal Cortex/diagnostic imaging , Prefrontal Cortex/metabolism , Schizophrenia/diagnostic imaging , Schizophrenia/genetics , Schizophrenia/metabolism , Dopamine/metabolism , Gray Matter/diagnostic imaging , Gray Matter/metabolism , Memory, Short-Term , Memory, Episodic , Reward , Speech , Humans , Male , Female , Adolescent , Young Adult , Adult , Datasets as Topic , Magnetic Resonance ImagingABSTRACT
OBJECTIVE: We sought to investigate the impact of individualized exercise guidance during pregnancy on the incidence of macrosomia and the mediating effect of gestational weight gain (GWG). DESIGN: A prospective randomized clinical trial. SETTING: A Hospital in Xingtai District, Hebei Province. POPULATION: Older than 20 years of age, mid-pregnancy, and singleton pregnant women without contraindications to exercise during pregnancy. METHODS: A randomized clinical trial was conducted from December 2021 to September 2022 to compare the effects of standard prenatal care with individualized exercise guidance on the incidence of macrosomia. MAIN OUTCOME MEASURE: Incidence of macrosomia. RESULTS: In all, 312 singleton women were randomized into an intervention group (N = 162) or a control group (N = 150). Participants who received individualized exercise guidance had a significantly lower incidence of macrosomia (3.73% vs. 13.61%, P = 0.002) and infants large for gestational age (9.94% vs. 19.73%, P = 0.015). However, no differences were observed in the rate of preterm birth (1.86% vs. 3.40%, P = 0.397) or the average gestational age at birth (39.14 ± 1.51 vs. 38.69 ± 1.85, P = 0.258). Mediation analysis revealed that GWG mediated the effect of exercise on reducing the incidence of macrosomia. CONCLUSION: Individualized exercise guidance may be a preventive tool for macrosomia, and GWG mediates the effect of exercise on reducing the incidence of macrosomia. However, evidence does not show that exercise increases the rate of preterm birth or affects the average gestational age at birth. TRIAL REGISTRATION: The trial is registered at www.clinicaltrails.gov [registration number: NCT05760768; registration date: 08/03/2023 (retrospectively registered)].
Subject(s)
Exercise , Fetal Macrosomia , Gestational Weight Gain , Prenatal Care , Humans , Female , Fetal Macrosomia/prevention & control , Pregnancy , Adult , Prenatal Care/methods , Prospective Studies , Incidence , China/epidemiology , Infant, NewbornABSTRACT
BACKGROUND: This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CUPID performance of experienced senior and junior radiologists. MATERIALS AND METHODS: This prospective cross-sectional study was conducted at Shenzhen University General Hospital between September 2022 and June 2023, and focused on mid-trimester fetuses. All ultrasound images of the six standard planes, that enabled the evaluation of nine biometric measurements, were included to compare the performance of CUPID through subjective and objective assessments. RESULTS: There were 642 fetuses with a mean (±SD) age of 22 ± 2.82 weeks at enrollment. In the subjective quality assessment, out of 642 images representing nine biometric measurements, 617-635 images (90.65-96.11%) of CUPID caliper placements were determined to be accurately placed and did not require any adjustments. Whereas, for the junior category, 447-691 images (69.63-92.06%) were determined to be accurately placed and did not require any adjustments. In the objective measurement indicators, across all nine biometric parameters and estimated fetal weight (EFW), the intra-class correlation coefficients (ICC) (0.843-0.990) and Pearson correlation coefficients (PCC) (0.765-0.978) between the senior radiologist and CUPID reflected good reliability compared with the ICC (0.306-0.937) and PCC (0.566-0.947) between the senior and junior radiologists. Additionally, the mean absolute error (MAE), percentage error (PE), and average error in days of gestation were lower between the senior and CUPID compared to the difference between the senior and junior radiologists. The specific differences are as follows: MAE (0.36-2.53 mm, 14.67 g) compared to (0.64- 8.13 mm, 38.05 g), PE (0.94-9.38%) compared to (1.58-16.04%), and average error in days (3.99-7.92 days) compared to (4.35-11.06 days). In the time-consuming task, CUPID only takes 0.05-0.07 s to measure nine biometric parameters, while senior and junior radiologists require 4.79-11.68 s and 4.95-13.44 s, respectively. CONCLUSIONS: CUPID has proven to be highly accurate and efficient software for automatically measuring fetal biometry, gestational age, and fetal weight, providing a precise and fast tool for assessing fetal growth and development.
Subject(s)
Artificial Intelligence , Fetal Weight , Pregnancy , Female , Humans , Infant , Cross-Sectional Studies , Prospective Studies , Reproducibility of Results , Ultrasonography, Prenatal/methods , Fetus/diagnostic imaging , Fetal Development , Gestational Age , Software , BiometryABSTRACT
AMPA receptors are members of the glutamate receptor family and mediate a fast component of excitatory synaptic transmission at virtually all central synapses. Thus, their functional characteristics are a critical determinant of brain function. We evaluate intolerance of each GRIA gene to genetic variation using 3DMTR and report here the functional consequences of 52 missense variants in GRIA1-4 identified in patients with various neurological disorders. These variants produce changes in agonist EC50, response time course, desensitization, and/or receptor surface expression. We predict that these functional and localization changes will have important consequences for circuit function, and therefore likely contribute to the patients' clinical phenotype. We evaluated the sensitivity of variant receptors to AMPAR-selective modulators including FDA-approved drugs to explore potential targeted therapeutic options.
Subject(s)
Nervous System Diseases , Humans , Nervous System Diseases/genetics , Synaptic Transmission/physiology , Receptors, AMPA/genetics , Receptors, AMPA/metabolism , Synapses/metabolismABSTRACT
Genome-wide association studies (GWASs) have identified multiple susceptibility loci for Alzheimer's disease (AD), which is characterized by early and progressive damage to the hippocampus. However, the association of hippocampal gene expression with AD and the underlying neurobiological pathways remain largely unknown. Based on the genomic and transcriptomic data of 111 hippocampal samples and the summary data of two large-scale meta-analyses of GWASs, a transcriptome-wide association study (TWAS) was performed to identify genes with significant associations between hippocampal expression and AD. We identified 54 significantly associated genes using an AD-GWAS meta-analysis of 455,258 individuals; 36 of the genes were confirmed in another AD-GWAS meta-analysis of 63,926 individuals. Fine-mapping models further prioritized 24 AD-related genes whose effects on AD were mediated by hippocampal expression, including APOE and two novel genes (PTPN9 and PCDHA4). These genes are functionally related to amyloid-beta formation, phosphorylation/dephosphorylation, neuronal apoptosis, neurogenesis and telomerase-related processes. By integrating the predicted hippocampal expression and neuroimaging data, we found that the hippocampal expression of QPCTL and ERCC2 showed significant difference between AD patients and cognitively normal elderly individuals as well as correlated with hippocampal volume. Mediation analysis further demonstrated that hippocampal volume mediated the effect of hippocampal gene expression (QPCTL and ERCC2) on AD. This study identifies two novel genes associated with AD by integrating hippocampal gene expression and genome-wide association data and reveals candidate hippocampus-mediated neurobiological pathways from gene expression to AD.
Subject(s)
Alzheimer Disease/genetics , Genetic Predisposition to Disease/genetics , Genome-Wide Association Study/methods , Hippocampus/metabolism , Polymorphism, Single Nucleotide , Transcriptome/genetics , Aged , Aged, 80 and over , Alzheimer Disease/diagnostic imaging , Female , Gene Regulatory Networks/genetics , Genomics/methods , Hippocampus/diagnostic imaging , Humans , Magnetic Resonance Imaging/methods , Male , Whole Genome Sequencing/methodsABSTRACT
OBJECTIVES: To investigate the effects of different concentrations of adapalene on the morphology and functions of neuroblastoma cell line SH-SY5Y, as well as its role in inducing cell differentiation and apoptosis. METHODS: SH-SY5Y cells were divided into control group, low concentration (0.1 µM and 1 µM) adapalene groups, and high concentration (10 µM) adapalene group. Time-lapse microscopy was used to observe the morphological changes of SH-SY5Y cells. Immunofluorescence staining was performed to detect the expression of neuronal specific marker ßIII-tubulin and mature neuronal marker neurofilament heavy polypeptide (NFH). Multi-electrode array was used to record the electrophysiological features of SH-SY5Y cells. Cell apoptosis was evaluated using a cell apoptosis detection kit. RESULTS: Low concentrations of adapalene promoted the formation of neurite outgrowth in SH-SY5Y cells, with the neurites interconnected to form a network. Spontaneous discharge activity was observed in SH-SY5Y cells treated with low concentrations of adapalene. Compared to the control group, the expression of ßIII-tubulin and NFH increased in the 1 µM adapalene group, while the level of cell apoptosis increased in the high concentration adapalene group (P<0.05). CONCLUSIONS: Low concentrations of adapalene can induce differentiation of SH-SY5Y cells into mature functional neurons, while high concentrations of adapalene can induce apoptosis in SH-SY5Y cells.
Subject(s)
Neuroblastoma , Tubulin , Humans , Neurons , Cell Differentiation , Apoptosis , Cell Line, TumorABSTRACT
The self-accelerating beams such as the Airy beam show great potentials in many applications including optical manipulation, imaging and communication. However, their superior features during linear propagation could be easily corrupted by optical nonlinearity or spatial incoherence individually. Here we investigate how the interaction of spatial incoherence and nonlinear propagation affect the beam quality of Airy beam, and find that the two destroying factors can in fact balance each other. Our results show that the influence of coherence and nonlinearity on the propagation of partially incoherent Airy beams (PIABs) can be formulated as two exponential functions that have factors of opposite signs. With appropriate spatial coherence length, the PIABs not only resist the corruption of beam profile caused by self-focusing nonlinearity, but also exhibits less anomalous diffraction caused by the self-defocusing nonlinearity. Our work provides deep insight into how to maintain the beam quality of self-accelerating Airy beams by exploiting the interaction between partially incoherence and optical nonlinearity. Our results may bring about new possibilities for optimizing partially incoherent structured field and developing related applications such as optical communication, incoherent imaging and optical manipulations.
ABSTRACT
Plant cellulose is synthesized by rosette-structured cellulose synthase (CESA) complexes (CSCs). Each CSC is composed of multiple subunits of CESAs representing three different isoforms. Individual CESA proteins contain conserved catalytic domains for catalyzing cellulose synthesis, other domains such as plant-conserved sequences, and class-specific regions that are thought to facilitate complex assembly and CSC trafficking. Because of the current lack of atomic-resolution structures for plant CSCs or CESAs, the molecular mechanism through which CESA catalyzes cellulose synthesis and whether its catalytic activity influences efficient CSC transport at the subcellular level remain unknown. Here, by performing chemical genetic analyses, biochemical assays, structural modeling, and molecular docking, we demonstrate that Endosidin20 (ES20) targets the catalytic site of CESA6 in Arabidopsis (Arabidopsis thaliana). Chemical genetic analysis revealed important amino acids that potentially participate in the catalytic activity of plant CESA6, in addition to previously identified conserved motifs across kingdoms. Using high spatiotemporal resolution live cell imaging, we found that inhibiting the catalytic activity of CESA6 by ES20 treatment reduced the efficiency of CSC transport to the plasma membrane. Our results demonstrate that ES20 is a chemical inhibitor of CESA activity and trafficking that represents a powerful tool for studying cellulose synthesis in plants.
Subject(s)
Arabidopsis Proteins/chemistry , Arabidopsis Proteins/metabolism , Arabidopsis/drug effects , Cellulose/biosynthesis , Glucosyltransferases/antagonists & inhibitors , Glucosyltransferases/chemistry , Glucosyltransferases/metabolism , Arabidopsis/metabolism , Arabidopsis Proteins/genetics , Bacterial Proteins/genetics , Bacterial Proteins/metabolism , Catalytic Domain , Dose-Response Relationship, Drug , Enzyme Inhibitors/pharmacology , Fluorescence Recovery After Photobleaching , Glucosyltransferases/genetics , Luminescent Proteins/genetics , Luminescent Proteins/metabolism , Molecular Docking Simulation , Mutation , Plants, Genetically Modified , Protein ConformationABSTRACT
Human hippocampal volume has been separately associated with single nucleotide polymorphisms (SNPs), DNA methylation and gene expression, but their causal relationships remain largely unknown. Here, we aimed at identifying the causal relationships of SNPs, DNA methylation, and gene expression that are associated with hippocampal volume by integrating cross-omics analyses with genome editing, overexpression and causality inference. Based on structural neuroimaging data and blood-derived genome, transcriptome and methylome data, we prioritized a possibly causal association across multiple molecular phenotypes: rs1053218 mutation leads to cg26741686 hypermethylation, thus leads to overactivation of the associated ANKRD37 gene expression in blood, a gene involving hypoxia, which may result in the reduction of human hippocampal volume. The possibly causal relationships from rs1053218 to cg26741686 methylation to ANKRD37 expression obtained from peripheral blood were replicated in human hippocampal tissue. To confirm causality, we performed CRISPR-based genome and epigenome-editing of rs1053218 homologous alleles and cg26741686 methylation in mouse neural stem cell differentiation models, and overexpressed ANKRD37 in mouse hippocampus. These in-vitro and in-vivo experiments confirmed that rs1053218 mutation caused cg26741686 hypermethylation and ANKRD37 overexpression, and cg26741686 hypermethylation favored ANKRD37 overexpression, and ANKRD37 overexpression reduced hippocampal volume. The pairwise relationships of rs1053218 with hippocampal volume, rs1053218 with cg26741686 methylation, cg26741686 methylation with ANKRD37 expression, and ANKRD37 expression with hippocampal volume could be replicated in an independent healthy young (n = 443) dataset and observed in elderly people (n = 194), and were more significant in patients with late-onset Alzheimer's disease (n = 76). This study revealed a novel causal molecular association mechanism of ANKRD37 with human hippocampal volume, which may facilitate the design of prevention and treatment strategies for hippocampal impairment.
Subject(s)
DNA Methylation , Hippocampus , Aged , Animals , Humans , Mice , Alleles , Alzheimer Disease/genetics , DNA Methylation/genetics , Epigenome , Hippocampus/metabolism , Polymorphism, Single Nucleotide/geneticsABSTRACT
OBJECTIVE: To investigate the clinical features and potential pathogenesis mechanism of de novo CLPTM1 variants associated with epilepsy. METHODS: Identify de novo genetic variants associated with epilepsy by reanalyzing trio-based whole-exome sequencing data. We analyzed the clinical characteristics of patients with these variants and performed functional in vitro studies in cells expressing mutant complementary DNA for these variants using whole-cell voltage-clamp current recordings and outside-out patch-clamp recordings from transiently transfected human embryonic kidney (HEK) cells. RESULTS: Two de novo missense variants related to epilepsy were identified in the CLPTM1 gene. Functional studies indicated that CLPTM1-p.R454H and CLPTM1-p.R568Q variants reduced the γ-aminobutyric acid A receptor (GABAA R) current response amplitude recorded under voltage clamp compared to the wild-type receptors. These variants also reduced the charge transfer and altered the time course of desensitization and deactivation following rapid removal of GABA. The surface expression of the GABAA R γ2 subunit from the CLPTM1-p.R568Q group was significantly reduced compared to CLPTM1-WT. SIGNIFICANCE: This is the first report of functionally relevant variants within the CLPTM1 gene. Patch-clamp recordings showed that these de novo CLPTM1 variants reduce GABAA R currents and charge transfer, which should promote excitation and hypersynchronous activity. This study may provide insights into the molecular mechanisms of the CLPTM1 variants underlying the patients' phenotypes, as well as for exploring potential therapeutic targets for epilepsy.
Subject(s)
Epilepsy , Receptors, GABA-A , Humans , Receptors, GABA-A/genetics , Receptors, GABA-A/metabolism , Epilepsy/genetics , Mutation, Missense/genetics , Phenotype , gamma-Aminobutyric Acid , Membrane Proteins/genetics , Membrane Proteins/metabolismABSTRACT
Acitretin is an oral drug approved by the Food and Drug Administration that is commonly used to treat psoriasis. In recent years, acitretin has been identified as a candidate drug for the treatment of Alzheimer's disease, but its role in neuronal development is still unclear. In this study, the human neuroblastoma cell line SH-SY5Y was used as a model to study neuronal differentiation. We found that acitretin effectively promoted the differentiation of SH-SY5Y cells into neuronal cells and upregulated the expression of the neuronal marker ß-III tubulin and the mature neuronal marker NFH. Differentially expressed genes were identified by RNA sequencing and analyzed by bioinformatics approaches. The results showed that genes associated with neuron development-related pathways, such as SSPO and KCNT1, had significant changes in expression. Analysis showed that PRKCA and CAMK2B may play important roles in the process by which acitretin promotes neurodevelopment. Through whole-cell patch clamping and a microelectrode array assay, we found that acitretin-treated neurons generated electrical spikes similar to those generated by mature neurons. This study provided evidence to support an accessible and safe model of neuron-like cells and verified that acitretin can promote the differentiation of neurons and has the potential to treat brain tumors and neurodevelopmental and neurodegenerative diseases.
Subject(s)
Acitretin , Neuroblastoma , Humans , Acitretin/pharmacology , Acitretin/metabolism , Cell Line, Tumor , Neuroblastoma/metabolism , Neurons/metabolism , Cell Differentiation/physiology , Potassium Channels, Sodium-Activated/metabolism , Nerve Tissue Proteins/metabolismABSTRACT
OBJECTIVES: To compare the image quality and hepatic metastasis detection of low-dose deep learning image reconstruction (DLIR) with full-dose filtered back projection (FBP)/iterative reconstruction (IR). METHODS: A contrast-detail phantom consisting of low-contrast objects was scanned at five CT dose index levels (10, 6, 3, 2, and 1 mGy). A total of 154 participants with 305 hepatic lesions who underwent abdominal CT were enrolled in a prospective non-inferiority trial with a three-arm design based on phantom results. Data sets with full dosage (13.6 mGy) and low dosages (9.5, 6.8, or 4.1 mGy) were acquired from two consecutive portal venous acquisitions, respectively. All images were reconstructed with FBP (reference), IR (control), and DLIR (test). Eleven readers evaluated phantom data sets for object detectability using a two-alternative forced-choice approach. Non-inferiority analyses were performed to interpret the differences in image quality and metastasis detection of low-dose DLIR relative to full-dose FBP/IR. RESULTS: The phantom experiment showed the dose reduction potential from DLIR was up to 57% based on the reference FBP dose index. Radiation decreases of 30% and 50% resulted in non-inferior image quality and hepatic metastasis detection with DLIR compared to full-dose FBP/IR. Radiation reduction of 70% by DLIR performed inferiorly in detecting small metastases (< 1 cm) compared to full-dose FBP (difference: -0.112; 95% confidence interval [CI]: -0.178 to 0.047) and full-dose IR (difference: -0.123; 95% CI: -0.182 to 0.053) (p < 0.001). CONCLUSION: DLIR enables a 50% dose reduction for detecting low-contrast hepatic metastases while maintaining comparable image quality to full-dose FBP and IR. KEY POINTS: ⢠Non-inferiority study showed that deep learning image reconstruction (DLIR) can reduce the dose to oncological patients with low-contrast lesions without compromising the diagnostic information. ⢠Radiation dose levels for DLIR can be reduced to 50% of full-dose FBP and IR for detecting low-contrast hepatic metastases, while maintaining comparable image quality. ⢠The reduction of radiation by 70% by DLIR is clinically acceptable but insufficient for detecting small low-contrast hepatic metastases (< 1 cm).
Subject(s)
Deep Learning , Liver Neoplasms , Humans , Algorithms , Image Processing, Computer-Assisted , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/secondary , Phantoms, Imaging , Prospective Studies , Radiation Dosage , Radiographic Image Interpretation, Computer-Assisted/methods , Tomography, X-Ray Computed/methodsABSTRACT
Soil microbes assemble in highly complex and diverse microbial communities, and microbial diversity patterns and their drivers have been studied extensively. However, diversity correlations and co-occurrence patterns between bacterial, fungal, and archaeal domains and between microbial functional groups in arid regions remain poorly understood. Here we assessed the relationships between the diversity and abundance of bacteria, fungi, and archaea and explored how environmental factors influence these relationships. We sampled soil along a 1500-km-long aridity gradient in temperate grasslands of Inner Mongolia (China) and sequenced the 16S rRNA gene of bacteria and archaea and the ITS2 gene of fungi. The diversity correlations and co-occurrence patterns between bacterial, fungal, and archaeal domains and between different microbial functional groups were evaluated using α-diversity and co-occurrence networks based on microbial abundance. Our results indicate insignificant correlations among the diversity patterns of bacterial, fungal, and archaeal domains using α-diversity but mostly positive correlations among diversity patterns of microbial functional groups based on α-diversity and co-occurrence networks along the aridity gradient. These results suggest that studying microbial diversity patterns from the perspective of functional groups and co-occurrence networks can provide additional insights on patterns that cannot be accessed using only overall microbial α-diversity. Increase in aridity weakens the diversity correlations between bacteria and fungi and between bacterial and archaeal functional groups, but strengthens the positive diversity correlations between bacterial functional groups and between fungal functional groups and the negative diversity correlations between bacterial and fungal functional groups. These variations of the diversity correlations are associated with the different responses of microbes to environmental factors, especially aridity. Our findings demonstrate the complex responses of microbial community structure to environmental conditions (especially aridity) and suggest that understanding diversity correlations and co-occurrence patterns between soil microbial groups is essential for predicting changes in microbial communities under future climate change in arid regions.