Unveiling the Function of Oxygen Vacancy on Facet-Dependent CeO2 for the Catalytic Destruction of Monochloromethane: Guidance for Industrial Catalyst Design.

Secondary pollution remains a critical challenge for the catalytic destruction of chlorinated volatile organic compounds (CVOCs). By employing experimental studies and theoretical calculations, we provide valuable insights into the catalytic behaviors exhibited by ceria rods, cubes, and octahedra for monochloromethane (MCM) destruction, shedding light on the elementary reactions over facet-dependent CeO2. Our findings demonstrate that CeO2 nanorods with the (110) facet exhibit the best performance in MCM destruction, and the role of vacancies is mainly to form a longer distance (4.63 Å) of frustrated Lewis pairs (FLPs) compared to the stoichiometric surface, thereby enhancing the activation of MCM molecules. Subsequent molecular orbital analysis showed that the adsorption of MCM mainly transferred electrons from the 3σ and 4π* orbitals to the Ce 4f orbitals, and the activation was mainly caused by weakening of the 3σ bonding orbitals. Furthermore, isotopic experiments and theoretical calculations demonstrated that the hydrogen chloride generated is mainly derived from methyl in MCM rather than from water, and the primary function of water is to form excess saturated H on the surface, facilitating the desorption of generated hydrogen chloride.

Soluble carbon source recovery using preconditioning coagulants for applicable short-term fermentation of waste activated sludge in WWTPs.

A huge production of waste activated sludge (WAS) has been a burden for wastewater treatment plants (WWTPs) with high disposal cost and little benefit back to wastewater purification. The short-chain fatty acids (SCFAs) produced by a short-term acidogenic fermentation of WAS before methane production have been proven to be a high-quality carbon source available for microbial denitrification process. The dual purpose of full recovery of fermentation liquid products and facilitating disposal of residual solid waste necessitate an efficient solid-liquid separation process of short-term fermentation liquid. The transformation and loss of various soluble carbon sources between solid and liquid are very important issues for carbon recovery efficiency when combining short-term fermentation and sludge dewatering in WWTPs. Here we testified the three conventional preconditioning coagulants, Polyferric Sulfate (PFS), Poly Aluminum Chloride (PAC) and Polyacrylamide (PAM), to improve the efficiency of subsequent solid-liquid separation. The results show that conversion yield of SCFAs in the liquid phase of sludge after short-term fermentation was 195 mg COD/g VSS, when using the coagulants PFS, PAC, and PAM for recovery, the recovery ratio was 79.5%, 82.0%, and 85.9%, respectively, while the dewaterability could be improved after preconditioning short-term fermentation sludge. The complexation of Al3+/Fe3+ in metal coagulants with carboxyl groups of SCFA demonstrated by Density Functional Theory calculation led to small part of soluble carbons co-migration to the solid phase, mainly a loss of high molecular weight organic compounds (carbohydrate, proteins, humic acids), while the application of PAM had little impact on carbon recovery. Economic calculations further showed PAM preconditioning short-term fermentation liquid of WAS could achieve higher recovery benefits.

Activated phosphoinositide 3-kinase δ syndrome caused by PIK3CD mutations: expanding the phenotype.

BACKGROUND: Germline heterozygous gain-of-function (GOF) mutations in the PIK3CD gene lead to a rare primary immunodeficiency disease known as activated phosphoinositide 3-kinase (PI3K) δ syndrome type 1(APDS1). Affected patients present a spectrum of clinical manifestations, particularly recurrent respiratory infections and lymphoproliferation, increased levels of serum immunoglobulin (Ig) M, Epstein-Barr virus (EBV) and cytomegalovirus (CMV) viremia. Due to highly heterogeneous phenotypes of APDS1, it is very likely that suspected cases may be misdiagnosed. METHODS: Herein we reported three patients with different clinical presentations but harboring pathogenic variants in PIK3CD gene detected by trio whole-exome sequencing (trio-WES) and confirmed by subsequent Sanger sequencing. RESULTS: Two heterozygous mutations (c.3061G > A, p.E1021K and c.1574 A > G, p.E525G) in PIK3CD (NM_005026.3) were identified by whole exome sequencing (WES) in the three patients. One of two patients with the mutation (c.3061G > A) presented with abdominal pain and diarrhea as the first symptoms, which was due to intussusception caused by multiple polyps of colon. The patient with mutation (c.1574 A > G) had an anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV)-like clinical manifestations, including multisystemic inflammation, acute nephritic syndrome, and positive perinuclear ANCA (p-ANCA), thus the diagnosis of ANCA-AAV was considered. CONCLUSIONS: Our study expands the spectrums of clinical phenotype and genotype of APDS, and demonstrates that WES has a high molecular diagnostic yield for patients with immunodeficiency related symptoms, such as respiratory infections, multiple ecchymosis, ANCA-associated vasculitis, multiple ileocecal polyps, hepatosplenomegaly, and lymphoid hyperplasia. TRIAL REGISTRATION: Retrospectively registered.

Surface-Phosphorylated Ceria for Chlorine-Tolerance Catalysis.

An improved fundamental understanding of active site structures can unlock opportunities for catalysis from conceptual design to industrial practice. Herein, we present the computational discovery and experimental demonstration of a highly active surface-phosphorylated ceria catalyst that exhibits robust chlorine tolerance for catalysis. Ab initio molecular dynamics (AIMD) calculations and in situ near-ambient pressure X-ray photoelectron spectroscopy (in situ NAP-XPS) identified a predominantly HPO4 active structure on CeO2(110) and CeO2(111) facets at room temperature. Importantly, further elevating the temperature led to a unique hydrogen (H) atom hopping between coordinatively unsaturated oxygen and the adjacent P═O group of HPO4. Such a mobile H on the catalyst surface can effectively quench the chlorine radicals (Cl•) via an orientated reaction analogous to hydrogen atom transfer (HAT), enabling the surface-phosphorylated CeO2-supported monolithic catalyst to exhibit both expected activity and stability for over 68 days during a pilot test, catalyzing the destruction of a complex chlorinated volatile organic compound industrial off-gas.

DeepMesh: Mesh-Based Cardiac Motion Tracking Using Deep Learning.

3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and the diagnosis of cardiovascular diseases. Current state-of-the art methods focus on estimating dense pixel-/voxel-wise motion fields in image space, which ignores the fact that motion estimation is only relevant and useful within the anatomical objects of interest, e.g., the heart. In this work, we model the heart as a 3D mesh consisting of epi- and endocardial surfaces. We propose a novel learning framework, DeepMesh, which propagates a template heart mesh to a subject space and estimates the 3D motion of the heart mesh from CMR images for individual subjects. In DeepMesh, the heart mesh of the end-diastolic frame of an individual subject is first reconstructed from the template mesh. Mesh-based 3D motion fields with respect to the end-diastolic frame are then estimated from 2D short- and long-axis CMR images. By developing a differentiable mesh-to-image rasterizer, DeepMesh is able to leverage 2D shape information from multiple anatomical views for 3D mesh reconstruction and mesh motion estimation. The proposed method estimates vertex-wise displacement and thus maintains vertex correspondences between time frames, which is important for the quantitative assessment of cardiac function across different subjects and populations. We evaluate DeepMesh on CMR images acquired from the UK Biobank. We focus on 3D motion estimation of the left ventricle in this work. Experimental results show that the proposed method quantitatively and qualitatively outperforms other image-based and mesh-based cardiac motion tracking methods.

Palladium Encapsulated by an Oxygen-Saturated TiO2 Overlayer for Low-Temperature SO2 -Tolerant Catalysis during CO Oxidation.

The development of oxidation catalysts that are resistant to sulfur poisoning is crucial for extending the lifespan of catalysts in real-working conditions. Herein, we describe the design and synthesis of oxide-metal interaction (OMI) catalyst under oxidative atmospheres. By using organic coated TiO2 , an oxide/metal inverse catalyst with non-classical oxygen-saturated TiO2 overlayers were obtained at relatively low temperature. These catalysts were found to incorporate ultra-small Pd metal and support particles with exceptional reactivity and stability for CO oxidation (under 21 vol % O2 and 10 vol % H2 O). In particular, the core (Pd)-shell (TiO2 ) structured OMI catalyst exhibited excellent resistance to SO2 poisoning, yielding robust CO oxidation performance at 120 °C for 240 h (at 100 ppm SO2 and 10 vol % H2 O). The stability of this new OMI catalyst was explained through density functional theory (DFT) calculations that interfacial oxygen atoms at Pd-O-Ti sites (of oxygen-saturated overlayers) serve as non-metal active sites for low-temperature CO oxidation, and change the SO2 adsorption from metal(d)-to-SO2 (π*) back-bonding to much weaker σ(Ti-S) bonding.

A bibliometric analysis of metastatic breast cancer: two-decade report (2002-2022).

Background: MBC is a lethal form of breast cancer that arises when cancer cells invade other organs or tissues. The treatment of MBC needs personalized approaches based on the tumor and patient characteristics. The purpose of this paper is to analyze MBC studies from 2002 to 2022 using bibliometrics and to investigate its current situation, main contributors, core journals, highly cited papers, and topic evolution. Materials and methods: We retrieved data from Web of Science Core Collection (WOSCC). Bibliometric analysis of the included literatures mainly used the following tools: the function of "analyze results" and "citation report" in WoS, Microsoft excel 2021, CiteSpace v.6.1. R6, VOSviewer v.1.6.18, BICOMB v.2.04 and gCLUTO v.1.0. Results: We found 12,653 articles on MBC research published in 1, 802 journals by 69, 753 authors from 118 countries. The annual output and citation of MBC articles showed a rising trend over time. The United States was the most influential country in MBC research. The most cited journal in this field was The Journal of Clinical Oncology. And the most cited article was by Slamon DJ. The co-word analysis of keywords divides MBC into six research clusters. The hormone receptor-positive MBC and liquid biopsy of MBC are the frontiers research trends. "CDK4/6 inhibitor" had the highest burst strength. Conclusion: Our bibliometric analysis offers a comprehensive overview of MBC research in the past two decades. It shows the current situation, main contributors, core journals, highly cited papers, and topic evolution of this field. Our study can assist researchers and practitioners to comprehend the development and trends of MBC research and to discover potential directions for future research.

Defect Engineering in 0D/2D S-Scheme Heterojunction Photocatalysts for Water Activation: Synergistic Roles of Nickel Doping and Oxygen Vacancy.

Photocatalytic hydrodechlorination (HDC) is a promising method for eliminating chlorinated organic compounds (COCs) from water, but it requires catalysts with excellent water activation ability. Defect engineering is a feasible way to enhance the catalytic performance of photocatalysts by improving light adsorption, charge carrier dynamics, and surface reactions. Herein, a well-designed 0D/2D S-scheme heterojunction with favorable band structures and defective interfaces was constructed via defect tailoring on TiO2 quantum dots (QDs) and the interface structure. The optimized catalyst Ni-TiO2-x/g-C3N4 with 1% Ni doping after thermal treatment at 300 °C under nitrogen resulted in superior visible-light-driven activity in trichloroethylene (TCE) photocatalytic HDC, approximately an 18.2-fold increase as compared with g-C3N4. Ni doping and thermal-induced oxygen vacancies were verified to synergistically endow the catalyst with improved visible-light absorption efficiency, ameliorated charge separation and migration, and enhanced redox potential. Experimental and theoretical results showed that the synergy of multifold defects in promoting visible-light harvesting was mainly due to the characteristic multiple midgap states, in terms of different intermediate energy levels and narrowed bandgap. Furthermore, the contradicting effects of midgap states on photogenerated charge carrier dynamics were mediated by the defective S-scheme heterojunction, where the detrimental charge recombination relating to excessive defects was considerably inhibited via superior spatial charge separation and promoted surface redox reactions. The design of defect-engineered heterojunctions and the role of controlled defects in adjusting band structures provide valuable insights for creating highly efficient artificial photosystems in the visible region.

A Fluorinated Polyimide Based Nano Silver Paste with High Thermal Resistance and Outstanding Thixotropic Performance.

Because of high conductivity, acceptable cost and good screen-printing process performance, silver pastes have been extensively used for making flexible electronics. However, there are few reported articles focusing on high heat resistance solidified silver pastes and their rheological properties. In this paper, a fluorinated polyamic acids (FPAA) is synthesized by polymerization of the 4,4'-(hexafluoroisopropylidene) diphthalic anhydride and 3,4'-diaminodiphenylether as monomers in the diethylene glycol monobutyl. The nano silver pastes are prepared by mixing the obtained FPAA resin with nano silver powder. The agglomerated particles caused by nano silver powder are divided and the dispersion of nano silver pastes are improved by three-roll grinding process with low roll gaps. The obtained nano silver pastes possess excellent thermal resistance with 5% weight loss temperature higher than 500 °C. The volume resistivity of cured nano silver paste achieves 4.52 × 10-7 Ω·m, when the silver content is 83% and the curing temperature is 300 °C. Additionally, the nano silver pastes have high thixotropic performance, which contributes to fabricate the fine pattern with high resolution. Finally, the conductive pattern with high resolution is prepared by printing silver nano pastes onto PI (Kapton-H) film. The excellent comprehensive properties, including good electrical conductivity, outstanding heat resistance and high thixotropy, make it a potential application in flexible electronics manufacturing, especially in high-temperature fields.

Icariin Induces Triple-Negative Breast Cancer Cell Apoptosis and Suppresses Invasion by Inhibiting the JNK/c-Jun Signaling Pathway.

Background: Breast cancer is a common cancer worldwide. Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer characterized by a poor prognosis. Icariin (ICA) is a flavonoid glycoside purified from the natural product Epimedium, which is reported to exert an inhibitory effect on a variety of cancers. However, molecular mechanisms behind ICA suppressed TNBC remain elusive. Methods: The curative effects of ICA on TNBC cells and potential targets were predicted by network pharmacology and molecular biology methods screening, and the mechanism of inhibition was explained through in vitro experiments such as cell function determination, Western blot analysis, molecular docking verification, etc. Results: This study showed that ICA inhibits TNBC cell functions such as proliferation, migration, and invasion in a dose-dependent manner. ICA could induce redox-induced apoptosis in TNBC cell, as shown by ROS upregulation. As a result of network pharmacology, ICA was predicted to be able to inhibit the MAPK signaling pathway. ICA treatment inhibited the expression of JNK and c-Jun and downregulated the antiapoptotic gene cIAP-2. Our results suggested that ICA could induce apoptosis by inducing an excessive accumulation of ROS in cells and suppress TNBC cell invasion via the JNK/c-Jun signaling pathway. Conclusion: We demonstrated that ICA can effectively inhibit cell proliferation and induced apoptosis of TNBC cells. In addition, ICA could inhibit TNBC cell invasion through the JNK/c-Jun signaling pathway. The above suggests that ICA may become a potential drug for TNBC.

Clinical features of CNOT3-associated neurodevelopmental disorder in three Chinese patients.

CNOT3 is the central component of the CCR4-NOT protein complex, which is a global regulator of RNA polymerase II transcription. Loss of function mutations in CNOT3 lead to intellectual developmental disorder with speech delay, autism, and dysmorphic facies (IDDSADF), which is very rare. Herein, we reported two novel heterozygous frameshift mutations (c.1058_1059insT and c.724delT) and one novel splice site variant (c.387 + 2 T > C) in CNOT3 (NM_014516.3) gene in three Chinese patients with dysmorphic features, developmental delay, and behavior anomalies. The functional study showed that the CNOT3 mRNA levels were significantly decreased in the peripheral blood of two patients with c.1058_1059insT and c.387 + 2 T > C variants, respectively, and minigene assay demonstrated that the splice variant (c.387 + 2 T > C) resulted in exon skipping. We also found that CNOT3 deficiency was linked to alterations of expression levels of other CCR4-NOT complex subunits in mRNA level in the peripheral blood. By analyzing the clinical manifestations of all these patients with CNOT3 variants, including our three cases and 22 patients previously reported, we did not observe a correlation between genotypes and phenotypes. In summary, this is the first time to report cases with IDDSADF in the Chinese population, and three novel CNOT3 variants in these patients expand its mutational spectrum.

Ultrafine aluminum sulfide nanocrystals anchored on two-dimensional carbon sheets for high-performance lithium-ion batteries.

Aluminum sulfide is a novel light metal sulfide, which possesses multiple advantages for lithium storage, including high theoretical capacity, proper discharge potential and good conductivity. However, much research has not been done in areas related to light metal sulfide materials. Herein, we synthesized Al2S3/C nanocomposite by a facile one-step ball milling method. This simple method not only effectively achieves the uniform composite of Al2S3 nanoparticles and carbon sheets, but also controls Al2S3 into ultrafine nanocrystals. Al2S3/C electrode demonstrates very outstanding lithium storage performance with large reversible specific capacity (1249 mAh g-1 at 100 mA g-1), remarkable rate capability (670 mAh g-1 at 5000 mA g-1) and superior long-cycling stability (retaining 850 mAh g-1 even after 1000 cycles at 1000 mA g-1). Moreover, the reversible lithium storage behavior and excellent diffusion kinetics of Al2S3/C are unveiled deeply. This work provides an inspiration to develop new light metal sulfide materials for the next-generation high-performance lithium ion battery.

Deep learning-based prediction of effluent quality of a constructed wetland.

Data-driven approaches that make timely predictions about pollutant concentrations in the effluent of constructed wetlands are essential for improving the treatment performance of constructed wetlands. However, the effect of the meteorological condition and flow changes in a real scenario are generally neglected in water quality prediction. To address this problem, in this study, we propose an approach based on multi-source data fusion that considers the following indicators: water quality indicators, water quantity indicators, and meteorological indicators. In this study, we establish four representative methods to simultaneously predict the concentrations of three representative pollutants in the effluent of a practical large-scale constructed wetland: (1) multiple linear regression; (2) backpropagation neural network (BPNN); (3) genetic algorithm combined with the BPNN to solve the local minima problem; and (4) long short-term memory (LSTM) neural network to consider the influence of past results on the present. The results suggest that the LSTM-predicting model performed considerably better than the other deep neural network-based model or linear method, with a satisfactory R2. Additionally, given the huge fluctuation of different pollutant concentrations in the effluent, we used a moving average method to smooth the original data, which successfully improved the accuracy of traditional neural networks and hybrid neural networks. The results of this study indicate that the hybrid modeling concept that combines intelligent and scientific data preprocessing methods with deep learning algorithms is a feasible approach for forecasting water quality in the effluent of actual engineering.

A novel CARD11 germline mutation in a Chinese patient of B cell expansion with NF-κB and T cell anergy (BENTA) and literature review.

Germline gain-of-function (GOF) mutations in the CARD11 gene lead to a rare primary immunodeficiency disease known as B cell expansion with NF-κB and T cell anergy (BENTA). Affected patients present with a polyclonal expansion of B cells, lymphadenopathy, and splenomegaly. Herein, we report a novel germline in-frame three base-pair deletion (c.1030_1032del, p.K344del) in the CARD11 gene in a patient with atypical BENTA, presenting with a recurrent fever and B cell lymphocytosis. This mutation was inherited from his mother, who is clinically asymptomatic and had a recurrent respiratory tract infection in her childhood. In vitro functional analysis demonstrated that this variant decreased the expression level of the CARD11 protein and activated the NF-κB signal pathway, leading to a higher expression of several NF-κB target gene transcripts in HCT116 cells transfected with mutant CARD11 (K344del-CARD11) as revealed by RNA sequencing analysis. To our knowledge, only 23 BENTA patients have been identified and carried seven distinct GOF mutations in CARD11. The clinical manifestations of patients are highly heterogeneous and there was no significant correlation between genotype and phenotype. In summary, we identified a novel in-frame three base-pair deletion that may be responsible for the pathogenesis of atypical BENTA in a Chinese family. Our study expands the mutational spectrum of the CARD11 gene and may be helpful in the understanding of diseases caused by CARD11 mutations and the clinical management of BENTA.

Selective Ru Adsorption on SnO2/CeO2 Mixed Oxides for Efficient Destruction of Multicomponent Volatile Organic Compounds: From Laboratory to Practical Possibility.

Ru-based catalysts have been extensively employed for the catalytic destruction of chlorinated volatile organic compounds (VOCs), but their versatility for other routine VOCs' destruction has been less explored. Herein, we show that Ru-decorated SnO2/CeO2 mixed oxides can sustain H2O and HCl poisonings and are endowed with extraordinary versatility for a wide range of VOCs' destruction. Selective adsorption of Ru on the cassiterite SnO2 and CeO2 nanorods through a Coulomb force can rationally tune the oxidation and dechlorination centers on decorated catalysts, where the epitaxial growth of RuOx on top of SnO2 is endowed with excellent dechlorination ability and that on CeO2 is functional as an oxidation center; the latter could also activate H2O to provide sufficient H protons for HCl formation. Our developed Ru/SnO2/CeO2 catalyst can steadily destruct mono-chlorobenzene, ortho-dichlorobenzene, trichloroethylene, dichloromethane, epichlorohydrin, N-hexane, ethyl acetate, toluene, and their mixtures at an optimum temperature of 300 °C, and its monolithic form is also functional at this temperature with few dioxins being detected in the off-gas. Our results imply that the Ru-decorated SnO2/CeO2 catalyst can meet the demands of regenerative catalytic oxidation for the treatment of a wide range of VOCs from industrial exhausts.

Achieving Partial Nitritation by Treating Sludge With Free Nitrous Acid: The Potential Role of Quorum Sensing.

Partial nitritation is increasingly regarded as a promising biological nitrogen removal process owing to lower energy consumption and better nitrogen removal performance compared to the traditional nitrification process, especially for the treatment of low carbon wastewater. Regulating microbial community structure and function in sewage treatment systems, which are mainly determined by quorum sensing (QS), by free nitrous acid (FNA) to establish a partial nitritation process is an efficient and stable method. Plenty of research papers reported that QS systems ubiquitously existed in ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB), and various novel nitrogen removal processes based on partial nitritation were successfully established using FNA. Although the probability that partial nitritation process might be achieved by the regulation of FNA on microbial community structure and function through the QS system was widely recognized and discussed, the potential role of QS in partial nitritation achievement by FNA and the regulation mechanism of FNA on QS system have not been reviewed. This article systematically reviewed the potential role of QS in the establishment of partial nitritation using FNA to regulate activated sludge flora based on the summary and analysis of the published literature for the first time, and future research directions were also proposed.

MulViMotion: Shape-Aware 3D Myocardial Motion Tracking From Multi-View Cardiac MRI.

Recovering the 3D motion of the heart from cine cardiac magnetic resonance (CMR) imaging enables the assessment of regional myocardial function and is important for understanding and analyzing cardiovascular disease. However, 3D cardiac motion estimation is challenging because the acquired cine CMR images are usually 2D slices which limit the accurate estimation of through-plane motion. To address this problem, we propose a novel multi-view motion estimation network (MulViMotion), which integrates 2D cine CMR images acquired in short-axis and long-axis planes to learn a consistent 3D motion field of the heart. In the proposed method, a hybrid 2D/3D network is built to generate dense 3D motion fields by learning fused representations from multi-view images. To ensure that the motion estimation is consistent in 3D, a shape regularization module is introduced during training, where shape information from multi-view images is exploited to provide weak supervision to 3D motion estimation. We extensively evaluate the proposed method on 2D cine CMR images from 580 subjects of the UK Biobank study for 3D motion tracking of the left ventricular myocardium. Experimental results show that the proposed method quantitatively and qualitatively outperforms competing methods.

Video Summarization Through Reinforcement Learning With a 3D Spatio-Temporal U-Net.

Intelligent video summarization algorithms allow to quickly convey the most relevant information in videos through the identification of the most essential and explanatory content while removing redundant video frames. In this paper, we introduce the 3DST-UNet-RL framework for video summarization. A 3D spatio-temporal U-Net is used to efficiently encode spatio-temporal information of the input videos for downstream reinforcement learning (RL). An RL agent learns from spatio-temporal latent scores and predicts actions for keeping or rejecting a video frame in a video summary. We investigate if real/inflated 3D spatio-temporal CNN features are better suited to learn representations from videos than commonly used 2D image features. Our framework can operate in both, a fully unsupervised mode and a supervised training mode. We analyse the impact of prescribed summary lengths and show experimental evidence for the effectiveness of 3DST-UNet-RL on two commonly used general video summarization benchmarks. We also applied our method on a medical video summarization task. The proposed video summarization method has the potential to save storage costs of ultrasound screening videos as well as to increase efficiency when browsing patient video data during retrospective analysis or audit without loosing essential information.

Idiopathic Granulomatous Mastitis: Etiology, Clinical Manifestation, Diagnosis and Treatment.

Idiopathic granulomatous mastitis (IGM) is a rare form of chronic inflammatory breast disease. Although it is a benign breast lesion, it may be sometimes difficult to distinguish from breast cancer. The cause of IGM is unknown, but may be associated with autoimmunity, abnormal hormone levels and infection. While the clinical manifestations of IGM involve various manifestations of inflammation, the diagnosis is principally established by histopathology, characterized by non-caseating granulomas and microabscess formation centered on the breast lobules. Therapeutic options for IGM range from observation to various medical treatments, such as steroids, immunosuppressants, and antibiotics, to surgical intervention, particularly if secondarily infected. Given that the controversy on etiology and treatment choices, we accomplished the present review through reviewing IGM-related literature published in 'Pubmed' and 'Web of science' databases during 1997 to 2020, aiming to provide the basis for rational clinical diagnosis and treatment.

Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time.

OBJECTIVE: Advances in artificial intelligence (AI) have demonstrated potential to improve medical diagnosis. We piloted the end-to-end automation of the mid-trimester screening ultrasound scan using AI-enabled tools. METHODS: A prospective method comparison study was conducted. Participants had both standard and AI-assisted US scans performed. The AI tools automated image acquisition, biometric measurement, and report production. A feedback survey captured the sonographers' perceptions of scanning. RESULTS: Twenty-three subjects were studied. The average time saving per scan was 7.62 min (34.7%) with the AI-assisted method (p < 0.0001). There was no difference in reporting time. There were no clinically significant differences in biometric measurements between the two methods. The AI tools saved a satisfactory view in 93% of the cases (four core views only), and 73% for the full 13 views, compared to 98% for both using the manual scan. Survey responses suggest that the AI tools helped sonographers to concentrate on image interpretation by removing disruptive tasks. CONCLUSION: Separating freehand scanning from image capture and measurement resulted in a faster scan and altered workflow. Removing repetitive tasks may allow more attention to be directed identifying fetal malformation. Further work is required to improve the image plane detection algorithm for use in real time.