Biodegradable microspheres come into sight: A promising biomaterial for delivering drug to the posterior segment of the eyeball.

Posterior segment disease acts as a major cause of irreversible visual impairments. Successful treatment of posterior segment disease requires the efficient delivery of therapeutic substances to the targeted lesion. However, the complex ocular architecture makes the bioavailability of topically applied drugs extremely low. Invasive delivery approaches like intravitreal injection may cause adverse complications. To enhance the efficiency, several biomedical engineering systems have been developed to increase the penetration efficiency and improve the bioavailability of drugs at the posterior segments. Advantageously, biodegradable microspheres are found to deliver the therapeutic agents in a controlled fashion. The microspheres prepared from novel biomaterials can realize the prolonged release at the posterior segment with minimum side effects. Moreover, it will be degraded automatically into products that are non-toxic to the human body without the necessity of secondary operation to remove the residual polymer matrix. Additionally, biodegradable microspheres have decent thermoplasticity, adjustable hydrophilicity, controlled crystallinity, and high tensile strength, which make them suitable for intraocular delivery. In this review, we introduce the latest advancements in microsphere production technology and elaborate on the biomaterials that are used to prepare microspheres. We discuss systematically the pharmacological characteristics of biodegradable microspheres and compare their potential advantages and limitations in the treatment of posterior segment diseases. These findings would enrich our knowledge of biodegradable microspheres and cast light into the discovery of effective biomaterials for ocular drug delivery.

Single-cell omics: experimental workflow, data analyses and applications.

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Application of metal artifact reduction algorithm in reducing metal artifacts in post-surgery pediatric low radiation dose spine computed tomography (CT) images.

Background: The commonly used methods for removing metal-induced beam hardening artifacts often rely on the use of high energy photons with either high tube voltage or high energy virtual monoenergetic images in dual-energy computed tomography (CT), the radiation dose was usually relatively high in order to generate adequate signals. This retrospective study is designed to evaluate the application of a metal artifact reduction (MAR) algorithm in reducing pedicle screw metal-caused beam hardening artifacts in post-surgery pediatric low radiation dose spine CT images. Methods: Seventy-seven children (3-15 years) who had undergone a low dose CT with 140 or 100 kV were enrolled. The radiation dose was 1.40 mGy for the 3-8 years old and 2.61 mGy for 9-15 years old children. There were 116 pedicle screws evaluated. The raw data were reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) at 50% strength, ASIR-V with MAR (AV-MAR), deep learning image reconstruction (DLIR) at high strength and DLIR with MAR (DL-MAR). The image quality concerning pedicle screws was evaluated objectively in terms of the length of beam-hardening artifact (LHA) and artifact index (AI), and subjectively using a 4-point scale (4 points: best, 3 points: acceptable). Results: Both AV-MAR and DL-MAR significantly reduced metal-induced beam hardening artifacts with smaller LHA (15.76±10.12 mm, a reduction of 57.24% and 15.66±10.49 mm, a reduction of 57.40%, respectively), and AI value (62.50±33.51, a reduction of 64.65% and 61.03±32.61, a reduction of 65.01%, respectively) compared to ASIR-V and DLIR (all P<0.01), The subjective image quality scores concerning the screws were 3.37±0.49 and 3.47±0.50 with AV-MAR and DL-MAR, respectively, higher than the respective value of 1.73±0.44 and 1.76±0.43 without MAR (all P<0.01). Conclusions: MAR significantly reduces the low-density artifacts caused by metal screws in post-surgery pediatric low-dose spine CT images, across different tube voltages, radiation dose levels and reconstruction algorithms. Combining DL-MAR further improves the overall image quality under low radiation dose conditions.

Nitrogen-cycling microbial communities respond differently to nitrogen addition under two contrasting grassland soil types.

Introduction: The impact of nitrogen (N) deposition on the soil N-transforming process in grasslands necessitates further investigation into how N input influences the structural composition and diversity of soil N-cycling microbial communities across different grassland types. Methods: In this study, we selected two types of grassland soils in northwest Liaoning, temperate steppe and warm-temperate shrub, and conducted short-term N addition experiments using organic N, ammonium N, and nitrate N as sources with three concentration gradients to simulate N deposition. Illumina MiSeq sequencing technology was employed to sequence genes associated with N-cycling microbes including N-fixing, ammonia-oxidizing and denitrifying bacteria, and ammonia-oxidizing archaea. Results and discussion: The results revealed significant alterations in the structural composition and diversity of the N-cycling microbial community due to N addition, but the response of soil microorganisms varied inconsistent among different grassland types. Ammonium transformation rates had a greater impact on soils from temperate steppes while nitrification rates were more influential for soils from warm-temperate shrubs. Furthermore, the influence of the type of N source on soil N-cycling microorganisms outweighed that of its quantity applied. The ammonium type of nitrogen source is considered the most influential driving factor affecting changes in the structure of the microbial community involved in nitrogen transformation, while the amount of low nitrogen applied primarily determines the composition of soil bacterial communities engaged in nitrogen fixation and nitrification. Different groups of N-cycling microorganisms exhibited distinct responses to varying levels of nitrogen addition with a positive correlation observed between their composition, diversity, and environmental factors examined. Overall findings suggest that short-term nitrogen deposition may sustain dominant processes such as soil-N fixation within grasslands over an extended period without causing significant negative effects on northwestern Liaoning's grassland ecosystems within the next decade.

Performance evaluation of deep learning image reconstruction algorithm for dual-energy spectral CT imaging: A phantom study.

OBJECTIVES: To evaluate the performance of deep learning image reconstruction (DLIR) algorithm in dual-energy spectral CT (DEsCT) as a function of radiation dose and image energy level, in comparison with filtered-back-projection (FBP) and adaptive statistical iterative reconstruction-V (ASIR-V) algorithms. METHODS: An ACR464 phantom was scanned with DEsCT at four dose levels (3.5 mGy, 5 mGy, 7.5 mGy, and 10 mGy). Virtual monochromatic images were reconstructed at five energy levels (40 keV, 50 keV, 68 keV, 74 keV, and 140 keV) using FBP, 50% and 100% ASIR-V, DLIR at low (DLIR-L), medium (DLIR-M), and high (DLIR-H) settings. The noise power spectrum (NPS), task-based transfer function (TTF) and detectability index (d') were computed and compared among reconstructions. RESULTS: NPS area and noise increased as keV decreased, with DLIR having slower increase than FBP and ASIR-V, and DLIR-H having the lowest values. DLIR had the best 40 keV/140 keV noise ratio at various energy levels, DLIR showed higher TTF (50%) than ASIR-V for all materials, especially for the soft tissue-like polystyrene insert, and DLIR-M and DLIR-H provided higher d' than DLIR-L, ASIR-V and FBP in all dose and energy levels. As keV increases, d' increased for acrylic insert, and d' of the 50 keV DLIR-M and DLIR-H images at 3.5 mGy (7.39 and 8.79, respectively) were higher than that (7.20) of the 50 keV ASIR-V50% images at 10 mGy. CONCLUSIONS: DLIR provides better noise containment for low keV images in DEsCT and higher TTF(50%) for the polystyrene insert over ASIR-V. DLIR-H has the lowest image noise and highest detectability in all dose and energy levels. DEsCT 50 keV images with DLIR-M and DLIR-H show potential for 65% dose reduction over ASIR-V50% withhigher d'.

In defense of local descriptor-based few-shot object detection.

State-of-the-art image object detection computational models require an intensive parameter fine-tuning stage (using deep convolution network, etc). with tens or hundreds of training examples. In contrast, human intelligence can robustly learn a new concept from just a few instances (i.e., few-shot detection). The distinctive perception mechanisms between these two families of systems enlighten us to revisit classical handcraft local descriptors (e.g., SIFT, HOG, etc.) as well as non-parametric visual models, which innately require no learning/training phase. Herein, we claim that the inferior performance of these local descriptors mainly results from a lack of global structure sense. To address this issue, we refine local descriptors with spatial contextual attention of neighbor affinities and then embed the local descriptors into discriminative subspace guided by Kernel-InfoNCE loss. Differing from conventional quantization of local descriptors in high-dimensional feature space or isometric dimension reduction, we actually seek a brain-inspired few-shot feature representation for the object manifold, which combines data-independent primitive representation and semantic context learning and thus helps with generalization. The obtained embeddings as pattern vectors/tensors permit us an accelerated but non-parametric visual similarity computation as the decision rule for final detection. Our approach to few-shot object detection is nearly learning-free, and experiments on remote sensing imageries (approximate 2-D affine space) confirm the efficacy of our model.

Immune checkpoint B7-H3 is a therapeutic vulnerability in prostate cancer harboring PTEN and TP53 deficiencies.

Checkpoint immunotherapy has yielded meaningful responses across many cancers but has shown modest efficacy in advanced prostate cancer. B7 homolog 3 protein (B7-H3/CD276) is an immune checkpoint molecule and has emerged as a promising therapeutic target. However, much remains to be understood regarding B7-H3's role in cancer progression, predictive biomarkers for B7-H3-targeted therapy, and combinatorial strategies. Our multi-omics analyses identified B7-H3 as one of the most abundant immune checkpoints in prostate tumors containing PTEN and TP53 genetic inactivation. Here, we sought in vivo genetic evidence for, and mechanistic understanding of, the role of B7-H3 in PTEN/TP53-deficient prostate cancer. We found that loss of PTEN and TP53 induced B7-H3 expression by activating transcriptional factor Sp1. Prostate-specific deletion of Cd276 resulted in delayed tumor progression and reversed the suppression of tumor-infiltrating T cells and NK cells in Pten/Trp53 genetically engineered mouse models. Furthermore, we tested the efficacy of the B7-H3 inhibitor in preclinical models of castration-resistant prostate cancer (CRPC). We demonstrated that enriched regulatory T cells and elevated programmed cell death ligand 1 (PD-L1) in myeloid cells hinder the therapeutic efficacy of B7-H3 inhibition in prostate tumors. Last, we showed that B7-H3 inhibition combined with blockade of PD-L1 or cytotoxic T lymphocyte-associated protein 4 (CTLA-4) achieved durable antitumor effects and had curative potential in a PTEN/TP53-deficient CRPC model. Given that B7-H3-targeted therapies have been evaluated in early clinical trials, our studies provide insights into the potential of biomarker-driven combinatorial immunotherapy targeting B7-H3 in prostate cancer, among other malignancies.

Alternative splicing of GSDMB modulates killer lymphocyte-triggered pyroptosis.

Granzyme A from killer lymphocytes cleaves gasdermin B (GSDMB) and triggers pyroptosis in targeted human tumor cells, eliciting antitumor immunity. However, GSDMB has a controversial role in pyroptosis and has been linked to both anti- and protumor functions. Here, we found that GSDMB splicing variants are functionally distinct. Cleaved N-terminal (NT) fragments of GSDMB isoforms 3 and 4 caused pyroptosis, but isoforms 1, 2, and 5 did not. The nonfunctional isoforms have a deleted or modified exon 6 and therefore lack a stable belt motif. The belt likely contributes to the insertion of oligomeric GSDMB-NTs into the membrane. Consistently, noncytotoxic GSDMB-NTs blocked pyroptosis caused by cytotoxic GSDMB-NTs in a dominant-negative manner. Upon natural killer (NK) cell attack, GSDMB3-expressing cells died by pyroptosis, whereas GSDMB4-expressing cells died by mixed pyroptosis and apoptosis, and GSDMB1/2-expressing cells died only by apoptosis. GSDMB4 partially resisted NK cell-triggered cleavage, suggesting that only GSDMB3 is fully functional. GSDMB1-3 were the most abundant isoforms in the tested tumor cell lines and were similarly induced by interferon-γ and the chemotherapy drug methotrexate. Expression of cytotoxic GSDMB3/4 isoforms, but not GSDMB1/2 isoforms that are frequently up-regulated in tumors, was associated with better outcomes in bladder and cervical cancers, suggesting that GSDMB3/4-mediated pyroptosis was protective in those tumors. Our study indicates that tumors may block and evade killer cell-triggered pyroptosis by generating noncytotoxic GSDMB isoforms. Therefore, therapeutics that favor the production of cytotoxic GSDMB isoforms by alternative splicing may improve antitumor immunity.

BART-D2 subtype of EBV encoded BART miRNA cluster 1 region is strongly associated with endemic nasopharyngeal carcinoma.

Epstein-Barr virus (EBV)-encoded BamHI A rightward transcript (BART) microRNAs (miRNAs) play important roles in viral infection and tumorigenesis. The association of sequence variations in the BART miRNA cluster 1 region with diseases remains unclear. Herein, 6 types and 11 subtypes of BART cluster 1 were identified in 354 tumors and healthy donors (HDs) from nasopharyngeal carcinoma (NPC)-endemic and nonendemic China (genotyped data), and 905 EBV genomes retrieved from GenBank from diseased and normal people from around the world (archived data). The distributions of BART cluster 1 types/subtypes between NPC-endemic and nonendemic China; between Asian regions and Africa/Europe & Australia & United States; and among Asian regions (NPC-endemic China, NPC-nonendemic East Asia and Southeast Asia) were significantly different (p < 0.001). The subtype BART-D2 was not found outside Asia and was only common in NPC-endemic China. More importantly, BART-D2 had a higher frequency in NPCs than in HDs in NPC-endemic China (genotyped data, 78.0% vs. 44.1%, p < 0.001; achieved data, 89.3% vs. 43.7%, p < 0.001), and was also more frequent in NPCs than in HDs, gastric carcinomas, and lymphomas in NPC-nonendemic China (genotyped data, 27.9% vs. 1.9%, 2.4%, and 0.0%, p < 0.001). BART-D2 was preferentially linked with the high-risk subtypes for NPC previously reported, 162476C or 163364T, in the BALF2 gene, and was associated with NPC risk (p < 0.01). In vitro experiments showed that BART-D2 affected the expression of some mature BART miRNAs. These findings demonstrate geographically restricted variations of BART cluster 1 and identify distinct subtype that is confined to NPC-endemic China and is associated with NPC.

CHD1, a multifaceted epigenetic remodeler in prostate cancer.

Chromatin remodeling proteins contribute to DNA replication, transcription, repair, and recombination. The chromodomain helicase DNA-binding (CHD) family of remodelers plays crucial roles in embryonic development, hematopoiesis, and neurogenesis. As the founding member, CHD1 is capable of assembling nucleosomes, remodeling chromatin structure, and regulating gene transcription. Dysregulation of CHD1 at genetic, epigenetic, and post-translational levels is common in malignancies and other human diseases. Through interacting with different genetic alterations, CHD1 possesses the capabilities to exert oncogenic or tumor-suppressive functions in context-dependent manners. In this Review, we summarize the biochemical properties and dysregulation of CHD1 in cancer cells, and then discuss CHD1's roles in different contexts of prostate cancer, with an emphasis on its crosstalk with diverse signaling pathways. Furthermore, we highlight the potential therapeutic strategies for cancers with dysregulated CHD1. At last, we discuss current research gaps in understanding CHD1's biological functions and molecular basis during disease progression, as well as the modeling systems for biology study and therapeutic development.

CHD1 Promotes Sensitivity to Aurora Kinase Inhibitors by Suppressing Interaction of AURKA with Its Coactivator TPX2.

Clinical studies have shown that subsets of patients with cancer achieve a significant benefit from Aurora kinase inhibitors, suggesting an urgent need to identify biomarkers for predicting drug response. Chromodomain helicase DNA binding protein 1 (CHD1) is involved in chromatin remodeling, DNA repair, and transcriptional plasticity. Prior studies have demonstrated that CHD1 has distinct expression patterns in cancers with different molecular features, but its impact on drug responsiveness remains understudied. Here, we show that CHD1 promotes the susceptibility of prostate cancer cells to inhibitors targeting Aurora kinases, while depletion of CHD1 impairs their efficacy in vitro and in vivo. Pan-cancer drug sensitivity analyses revealed that high expression of CHD1 was associated with increased sensitivity to Aurora kinase A (AURKA) inhibitors. Mechanistically, KPNA2 served as a direct target of CHD1 and suppressed the interaction of AURKA with the coactivator TPX2, thereby rendering cancer cells more vulnerable to AURKA inhibitors. Consistent with previous research reporting that loss of PTEN elevates CHD1 levels, studies in a genetically engineered mouse model, patient-derived organoids, and patient samples showed that PTEN defects are associated with a better response to AURKA inhibition in advanced prostate cancer. These observations demonstrate that CHD1 plays an important role in modulating Aurora kinases and drug sensitivities, providing new insights into biomarker-driven therapies targeting Aurora kinases for future clinical studies. SIGNIFICANCE: CHD1 plays a critical role in controlling AURKA activation and promoting Aurora kinase inhibitor sensitivity, providing a potential clinical biomarker to guide cancer treatment.

Influence of normal forces on the frictional behavior in tribological systems made of different bracket types and wire dimensions.

The aim of the present work was measuring the effect of varying normal forces on frictional forces applied to different bracket types in combination with archwires made of NiTi and stainless steel of variable cross section. The measurements were carried out in artificial saliva. Three-way ANOVA and Bonferroni post-hoc tests (α=0.05) were applied. Except for one subgroup the combination of normal force, bracket system and wire dimension had significant effect on friction (p<0.001) as friction increased with increasing normal forces. Only moderately tied ligatures or passive self-ligating brackets generate low friction forces. There was a statistically significant order (0.016"×0.022"<0.018"×0.025"<0.019"×0.025") for stainless steel wire material. Finite element modeling simulation showed the increasing effect of active clip force on friction especially for 0.025" wire profiles. If compared to NiTi wires, stainless steel archwires delivered higher friction. Combinations between wire-type and ligation should be chosen carefully for the intended treatment step.

Transcriptome analysis of thymic tissues from Chinese Partridge Shank chickens with or without Newcastle disease virus LaSota vaccine injection via high-throughput RNA sequencing.

The LaSota strain of Newcastle disease virus (NDV) is a commonly used vaccine to control Newcastle disease. However, improper immunization is a common reason for vaccine failure. Hence, it is imperative to thoroughly explore innate immunity-related molecular regulatory responses to the LaSota vaccine. In this text, 140 long non-coding RNAs (lncRNAs), 8 microRNAs (miRNAs), and 1514 mRNAs were identified to be differentially expressed by RNA sequencing analysis in the thymic tissues of Chinese Partridge Shank chickens after LaSota vaccine inoculation. Moreover, 70 dysregulated genes related to innate immunity were identified based on GO, Reactome pathway, and InnateDB annotations and differential expression analysis. Additionally, dysregulated lncRNAs and innate immunity-related mRNAs that could interact with dysregulated miRNAs were identified based on bioinformatics prediction analysis via the miRanda software and differential expression analysis. Among these transcripts, expression patterns of five lncRNAs, seven miRNAs, and six mRNAs were further examined by RT-qPCR assay. Both RNA-seq and RT-qPCR outcomes showed that 10 transcripts (MSTRG.22689.1, ENSGALT00000065826, ENSGALT00000059336, ENSGALT00000060887, gga-miR-6575-5p, gga-miR-6631-5p, gga-miR-1727, paraoxonase 2 (PON2), mitogen-activated protein kinase 10, and cystic fibrosis transmembrane conductance regulator (CFTR) were highly expressed, and 4 transcripts (MSTRG.188121.10, gga-miR-6655-5p, gga-miR-6548-3p, and matrix metallopeptidase 9 (MMP9) were low expressed after NDV infection. Additionally, two potential competing endogenous RNA networks (ENSGALT00000060887/gga-miR-6575-5p/PON2 or MSTRG.188121.10/gga-miR-6631-5p/MMP9) and some co-expression axes (ENSGALT00000065826/gga-miR-6631-5p, MSTRG.188121.10/gga-miR-6575-5p, MSTRG.188121.10/CFTR, ENSGALT00000060887/MMP9) were identified based on RT-qPCR and co-expression analyses. In conclusion, we identified multiple dysregulated lncRNAs, miRNAs, and mRNAs after LaSota infection and some potential regulatory networks for these dysregulated transcripts.

Application of deep learning image reconstruction algorithm to improve image quality in CT angiography of children with Takayasu arteritis.

BACKGROUND: The inflammatory indexes of children with Takayasu arteritis (TAK) usually tend to be normal immediately after treatment, therefore, CT angiography (CTA) has become an important method to evaluate the status of TAK and sometime is even more sensitive than laboratory test results. OBJECTIVE: To evaluate image quality improvement in CTA of children diagnosed with TAK using a deep learning image reconstruction (DLIR) in comparison to other image reconstruction algorithms. METHODS: hirty-two TAK patients (9.14±4.51 years old) underwent neck, chest and abdominal CTA using 100 kVp were enrolled. Images were reconstructed at 0.625 mm slice thickness using Filtered Back-Projection (FBP), 50%adaptive statistical iterative reconstruction-V (ASIR-V), 100%ASIR-V and DLIR with high setting (DLIR-H). CT number and standard deviation (SD) of the descending aorta and back muscle were measured and contrast-to-noise ratio (CNR) for aorta was calculated. The vessel visualization, overall image noise and diagnostic confidence were evaluated using a 5-point scale (5, excellent; 3, acceptable) by 2 observers. RESULTS: There was no significant difference in CT number across images reconstructed using different algorithms. Image noise values (in HU) were 31.36±6.01, 24.96±4.69, 18.46±3.91 and 15.58±3.65, and CNR values for aorta were 11.93±2.12, 15.66±2.37, 22.54±3.34 and 24.02±4.55 using FBP, 50%ASIR-V, 100%ASIR-V and DLIR-H, respectively. The 100%ASIR-V and DLIR-H images had similar noise and CNR (all P > 0.05), and both had lower noise and higher CNR than FBP and 50%ASIR-V images (all P < 0.05). The subjective evaluation suggested that all images were diagnostic for large arteries, however, only 50%ASIR-V and DLIR-H met the diagnostic requirement for small arteries (3.03±0.18 and 3.53±0.51). CONCLUSION: DLIR-H improves CTA image quality and diagnostic confidence for TAK patients compared with 50%ASIR-V, and best balances image noise and spatial resolution compared with 100%ASIR-V.

Performance evaluation of using shorter contrast injection and 70 kVp with deep learning image reconstruction for reduced contrast medium dose and radiation dose in coronary CT angiography for children: a pilot study.

BACKGROUND: Iterative reconstruction algorithms are often used to reduce image noise in low-dose coronary computed tomography angiography (CCTA) but encounter limitations. The newly introduced deep learning image reconstruction (DLIR) algorithm may provide new opportunities. We assessed the image quality and diagnostic performance of DLIR in low radiation dose and contrast medium dose CCTA of pediatric patients with 70 kVp and a shortened injection protocol. METHODS: This was a prospective study. A total of 27 consecutive arrhythmic pediatric patients were enrolled in the study group and underwent CCTA using a prospective ECG-triggered single-beat protocol: tube voltage 70 kVp, automatic tube current modulation for a noise index (NI) of 22, and contrast dose of 0.4-0.6 mL/kg. Images were reconstructed with DLIR. They were compared with 27 matched patients in the control group scanned with 80 kVp, a lower NI setting (NI =19), and a higher contrast dose (0.8-1.2 mL/kg). The images in the control group were reconstructed using the adaptive statistical iterative reconstruction (ASIR-V) algorithm. The image contrast, image quality, and diagnostic confidence were assessed by 2 experienced radiologists using a 5-point scale (1: nondiagnostic and 5: excellent). The CT value and standard deviation of the aorta and perivascular tissue were measured, and the contrast-to-noise ratio (CNR) for the aorta was calculated. The contrast medium and radiation doses were compared. RESULTS: The study and control groups had similar image contrast scores (4.75±0.57 vs. 4.78±0.42), image quality scores (3.67±0.47 vs. 3.44±0.51), and diagnostic confidence (4.74±0.44 vs. 4.74±0.45) (all P>0.05). There was an adequate enhancement in the aorta (614.74±127.73 vs. 705.89±111.20 HU) and similar CNR (20.34±4.64 vs. 20.99±4.14) in both groups. The image noise of the study group was lower in the aorta (30.61±3.88 vs. 34.77±3.49) and similar in perivascular tissue (27.66±6.24 vs. 27.55±3.33) compared with the control group. The study group reduced the total contrast medium dose by 53% to 15.07±3.68 mL and radiation dose by 36% to 0.57±0.31 mSv. CONCLUSIONS: The DLIR algorithm in CCTA for children using 70 kVp tube voltage with a shortened contrast medium injection protocol maintains image quality and diagnostic confidence while significantly reducing contrast medium dose and radiation dose compared with the use of the conventional CCTA protocol.

Effect of different media on frictional forces between tribological systems made from self-ligating brackets in combination with different stainless steel wire dimensions.

The purpose was to determine the effect of different environments (artificial saliva, human saliva, distilled water, dry storage) on frictional forces between various tribological systems made from self-ligating brackets in combination with stainless-steel wires (dimensions: 0.016″×0.022″, 0.018″×0.025″ and 0.019″×0.025″). An universal testing-machine applied a normal force of 1 N. Two-way ANOVA and Tukey post-hoc tests (α=5%) were used. Saliva had significantly higher frictional forces (p<0.001). Yet, the influence of the media depends on the wire dimensions. The results were not as straightforward as in 0.018″×0.025″, which had a clear order (dry storage

Application of a deep learning image reconstruction (DLIR) algorithm in head CT imaging for children to improve image quality and lesion detection.

BACKGROUND: To evaluate the performance of a Deep Learning Image Reconstruction (DLIR) algorithm in pediatric head CT for improving image quality and lesion detection with 0.625 mm thin-slice images. METHODS: Low-dose axial head CT scans of 50 children with 120 kV, 0.8 s rotation and age-dependent 150-220 mA tube current were selected. Images were reconstructed at 5 mm and 0.625 mm slice thickness using Filtered back projection (FBP), Adaptive statistical iterative reconstruction-v at 50% strength (50%ASIR-V) (as reference standard), 100%ASIR-V and DLIR-high (DL-H). The CT attenuation and standard deviation values of the gray and white matters in the basal ganglia were measured. The clarity of sulci/cisterns, boundary between white and gray matters, and overall image quality was subjectively evaluated. The number of lesions in each reconstruction group was counted. RESULTS: The 5 mm FBP, 50%ASIR-V, 100%ASIR-V and DL-H images had a subjective score of 2.25 ± 0.44, 3.05 ± 0.23, 2.87 ± 0.39 and 3.64 ± 0.49 in a 5-point scale, respectively with DL-H having the lowest image noise of white matter at 2.00 ± 0.34 HU; For the 0.625 mm images, only DL-H images met the diagnostic requirement. The 0.625 mm DL-H images had similar image noise (3.11 ± 0.58 HU) of the white matter and overall image quality score (3.04 ± 0.33) as the 5 mm 50% ASIR-V images (3.16 ± 0.60 HU and 3.05 ± 0.23). Sixty-five lesions were recognized in 5 mm 50%ASIR-V images and 69 were detected in 0.625 mm DL-H images. CONCLUSION: DL-H improves the head CT image quality for children compared with ASIR-V images. The 0.625 mm DL-H images improve lesion detection and produce similar image noise as the 5 mm 50%ASIR-V images, indicating a potential 85% dose reduction if current image quality and slice thickness are desired.

Improving the image quality of pediatric chest CT angiography with low radiation dose and contrast volume using deep learning image reconstruction.

BACKGROUND: Chest CT angiography (CTA) is a common clinical examination technique for children. Iterative reconstruction algorithms are often used to reduce image noise but encounter limitations under low dose conditions. Deep learning-based image reconstruction algorithms have been developed to overcome these limitations. We assessed the quantitative and qualitative image quality of thin-slice chest CTA in children acquired with low radiation dose and contrast volume by using a deep learning image reconstruction (DLIR) algorithm. METHODS: A total of 33 children underwent chest CTA with 70 kVp and automatic tube current modulation for noise indices of 11-15 based on their age and contrast volume of 0.8-1.2 mL/kg. Images were reconstructed with 50% and 100% adaptive statistical iterative reconstruction-V (ASIR-V) and high-setting DLIR (DLIR-H) at 0.625 mm slice thickness. Two radiologists evaluated images in consensus for overall image noise, artery margin, and artery contrast separately on a 5-point scale (5, excellent; 4, good; 3, acceptable; 2, sub-acceptable, and 1, not acceptable). The CT value and image noise of the descending aorta and back muscle were measured. Radiation dose and contrast volume was recorded. RESULTS: The volume CT dose index, dose length product, and contrast volume were 1.37±0.29 mGy, 35.43±10.59 mGy·cm, and 25.43±13.32 mL, respectively. The image noises (in HU) of the aorta with DLIR-H (19.24±5.77) and 100% ASIR-V (20.45±6.93) were not significantly different (P>0.05) and were substantially lower than 50% ASIR-V (29.45±7.59) (P<0.001). The 100% ASIR-V images had over-smoothed artery margins, but only the DLIR-H images provided acceptable scores on all 3 aspects of the qualitative image quality evaluation. CONCLUSIONS: It is feasible to improve the image quality of a low radiation dose and contrast volume chest CTA in children using the high-setting DLIR algorithm.

Performance evaluation of a deep learning image reconstruction (DLIR) algorithm in "double low" chest CTA in children: a feasibility study.

BACKGROUND: Chest CT angiography (CTA) is a convenient clinical examination for children with an increasing need to reduce both radiation and contrast medium doses. Iterative Reconstruction algorithms are often used to reduce image noise but encounter limitations under low radiation dose and conventional 100 kVp tube voltage may not provide adequate enhancement under low contrast dose. PURPOSE: To evaluate the performance of a deep learning image reconstruction (DLIR) algorithm in conjunction with lower tube voltage in chest CTA in children under reduced radiation and contrast medium (CM) dose. MATERIALS AND METHODS: 46 Children (age 5.9 ± 4.2 years) in the study group underwent chest CTA with 70 kVp and CM dose of 0.8-1.2 ml/kg. Images were reconstructed at 0.625 mm using a high setting DLIR (DLIR-H). The control group consisted of 46 age-matching children scanned with 100 kVp, CM dose of 1.3-1.8 ml/kg and images reconstructed with 50% and 100% adaptive statistical iterative reconstruction-V. Two radiologists evaluated images subjectively for overall image noise, vessel contrast and vessel margin clarity separately on a 5-point scale (5, excellent and 1, not acceptable). CT value and image noise of aorta and erector spinae muscle were measured. RESULTS: Compared to the control group, the study group reduced the dose-length-product by 11.2% (p = 0.01) and CM dose by 24% (p < 0.001), improved the enhancement in aorta (416.5 ± 113.1HU vs. 342.0 ± 57.6HU, p < 0.001) and reduced noise (15.1 ± 3.5HU vs. 18.6 ± 4.4HU, p < 0.001). The DLIR-H images provided acceptable scores on all 3 aspects of the qualitative evaluation. CONCLUSION: "Double low" chest CTA in children using 70 kVp and DLIR provides high image quality with reduced noise and improved vessel enhancement for diagnosis while further reduces radiation and CM dose.

Application of 70 kVp in abdominal CT angiography to reduce both radiation and contrast dosage and improve patient comfort for children.

BACKGROUND: Low-tube voltage scanning improves CT attenuation value of contrast medium (CM). Thus, we hypothesized that 70 kVp in pediatric abdominal CT angiography (CTA) could be used to reduce both radiation and CM dose and improve patient comfort at the same time. OBJECTIVE: To evaluate the feasibility of using 70 kVp in pediatric abdominal CTA to reduce radiation dose and CM dose and improve patient care for children. MATERIALS AND METHODS: Forty-six children needing abdominal CTA were enrolled in the study group using low-dose scanning protocol with 70 kVp and 0.7-1.1 ml/kg contrast dose, and reconstructed with 50%ASIR-V. They were compared with other 46 children in control group with matching body weight and underwent conventional CT scans with 100 kVp, 1.2-1.8 ml/kg contrast dose and reconstructed using 50%ASIR. Image quality of large vessels was evaluated using a 5-point scale. CT value and standard deviation of descending aorta (Ao) was measured, and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Radiation dose, contrast dose, the maximum injection pressure between the two groups were also compared. RESULTS: Score for displaying large vessels by 70 kVp images was 3.91±0.28, lower than that (4.17±0.38) of the control group (p < 0.05), but fully met the diagnostic requirements. CT value of Ao was 390.87±86.79HU in study group, which is higher than 343.93±49.94HU in control group, while there was no difference in SNR and CNR between two groups; the radiation dose, contrast dosage and injection pressure of the study group were 1.23±0.39mGy, 12.67±7.27 ml and 43.83±17.16psi, respectively, which are significantly lower than the 1.95±0.37mGy, 22.67±7.39 ml, and 77.59±19.68psi of control group. CONCLUSION: Use of 70 kVp in pediatric abdominal CTA provides diagnostic quality images while significantly reduce radiation and contrast dose, as well as injection pressure to improve patient comfort for children.