Mammography is the current standard for breast cancer screening. This study aimed to develop an artificial intelligence (AI) algorithm for diagnosis of breast cancer in mammography, and explore ...whether it could benefit radiologists by improving accuracy of diagnosis.
In this retrospective study, an AI algorithm was developed and validated with 170 230 mammography examinations collected from five institutions in South Korea, the USA, and the UK, including 36 468 cancer positive confirmed by biopsy, 59 544 benign confirmed by biopsy (8827 mammograms) or follow-up imaging (50 717 mammograms), and 74 218 normal. For the multicentre, observer-blinded, reader study, 320 mammograms (160 cancer positive, 64 benign, 96 normal) were independently obtained from two institutions. 14 radiologists participated as readers and assessed each mammogram in terms of likelihood of malignancy (LOM), location of malignancy, and necessity to recall the patient, first without and then with assistance of the AI algorithm. The performance of AI and radiologists was evaluated in terms of LOM-based area under the receiver operating characteristic curve (AUROC) and recall-based sensitivity and specificity.
The AI standalone performance was AUROC 0·959 (95% CI 0·952–0·966) overall, and 0·970 (0·963–0·978) in the South Korea dataset, 0·953 (0·938–0·968) in the USA dataset, and 0·938 (0·918–0·958) in the UK dataset. In the reader study, the performance level of AI was 0·940 (0·915–0·965), significantly higher than that of the radiologists without AI assistance (0·810, 95% CI 0·770–0·850; p<0·0001). With the assistance of AI, radiologists' performance was improved to 0·881 (0·850–0·911; p<0·0001). AI was more sensitive to detect cancers with mass (53 90% vs 46 78% of 59 cancers detected; p=0·044) or distortion or asymmetry (18 90% vs ten 50% of 20 cancers detected; p=0·023) than radiologists. AI was better in detection of T1 cancers (73 91% vs 59 74% of 80; p=0·0039) or node-negative cancers (104 87% vs 88 74% of 119; p=0·0025) than radiologists.
The AI algorithm developed with large-scale mammography data showed better diagnostic performance in breast cancer detection compared with radiologists. The significant improvement in radiologists' performance when aided by AI supports application of AI to mammograms as a diagnostic support tool.
Lunit.
In South Korea, a November 2021 outbreak caused by severe acute respiratory syndrome coronavirus 2 Omicron variant originated from 1 person with an imported case and spread to households, ...kindergartens, workplaces, restaurants, and hospitals, resulting in 11 clusters within 3 weeks. An epidemiologic curve indicated rapid community transmission of the Omicron variant.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China and rapidly spread worldwide. To prevent SARS-CoV-2 ...dissemination, understanding the in vivo characteristics of SARS-CoV-2 is a high priority. We report a ferret model of SARS-CoV-2 infection and transmission that recapitulates aspects of human disease. SARS-CoV-2-infected ferrets exhibit elevated body temperatures and virus replication. Although fatalities were not observed, SARS-CoV-2-infected ferrets shed virus in nasal washes, saliva, urine, and feces up to 8 days post-infection. At 2 days post-contact, SARS-CoV-2 was detected in all naive direct contact ferrets. Furthermore, a few naive indirect contact ferrets were positive for viral RNA, suggesting airborne transmission. Viral antigens were detected in nasal turbinate, trachea, lungs, and intestine with acute bronchiolitis present in infected lungs. Thus, ferrets represent an infection and transmission animal model of COVID-19 that may facilitate development of SARS-CoV-2 therapeutics and vaccines.
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•SARS-CoV-2-infected ferrets exhibit elevated body temperature and virus replication•SARS-CoV-2 is shed in nasal washes, saliva, urine and feces•SARS-CoV-2 is effectively transmitted to naive ferrets by direct contact•SARS-CoV-2 infection leads acute bronchiolitis in infected ferrets
The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rapidly spreads, leading to a pandemic infection. Kim et al. show that ferrets are highly susceptible to SARS-CoV-2 infection and effectively transmit the virus by direct or indirect contact, recapitulating human infection and transmission.
Parkin dysfunction associated with the progression of parkinsonism contributes to a progressive systemic skeletal disease characterized by low bone mineral density. However, the role of parkin in ...bone remodeling has not yet been elucidated in detail.
We observed that decreased parkin in monocytes is linked to osteoclastic bone-resorbing activity. siRNA-mediated knockdown of parkin significantly enhanced the bone-resorbing activity of osteoclasts (OCs) on dentin without any changes in osteoblast differentiation. Moreover, Parkin-deficient mice exhibited an osteoporotic phenotype with a lower bone volume accompanied by increased OC-mediated bone-resorbing capacity displaying increased acetylation of α-tubulin compared to wild-type (WT) mice. Notably, compared to WT mice, the Parkin-deficient mice displayed increased susceptibility to inflammatory arthritis, reflected by a higher arthritis score and a marked bone loss after arthritis induction using K/BxN serum transfer, but not ovariectomy-induced bone loss. Intriguingly, parkin colocalized with microtubules and parkin-depleted-osteoclast precursor cells (Parkin
OCPs) displayed augmented ERK-dependent acetylation of α-tubulin due to failure of interaction with histone deacetylase 6 (HDAC6), which was promoted by IL-1β signaling. The ectopic expression of parkin in Parkin
OCPs limited the increase in dentin resorption induced by IL-1β, accompanied by the reduced acetylation of α-tubulin and diminished cathepsin K activity.
These results indicate that a deficiency in the function of parkin caused by a decrease in parkin expression in OCPs under the inflammatory condition may enhance inflammatory bone erosion by altering microtubule dynamics to maintain OC activity.
In November 2021, 14 international travel-related severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) B.1.1.529 (omicron) variant of concern (VOC) patients were detected in South Korea. ...Epidemiologic investigation revealed community transmission of the omicron VOC. A total of 80 SARS-CoV-2 omicron VOC-positive patients were identified until December 10, 2021 and 66 of them reported no relation to the international travel. There may be more transmissions with this VOC in Korea than reported.
The blood-brain barrier (BBB) maintains homeostasis of the brain environment by tightly regulating the entry of substances from systemic circulation. A breach in the BBB results in increased ...permeability to potentially toxic substances and is an important contributor to amplification of ischemic brain damage. The precise molecular pathways that result in impairment of BBB integrity remain to be elucidated. Autophagy is a degradation pathway that clears damaged or unnecessary proteins from cells. However, excessive autophagy can lead to cellular dysfunction and death under pathological conditions.
In this study, we investigated whether autophagy is involved in BBB disruption in ischemia, using in vitro cells and in vivo rat models. We used brain endothelial bEnd.3 cells and oxygen glucose deprivation (OGD) to simulate ischemia in culture, along with a rat ischemic stroke model to evaluate the role of autophagy in BBB disruption during cerebral ischemia.
OGD 18 h induced cellular dysfunction, and increased permeability with degradation of occludin and activation of autophagy pathways in brain endothelial cells. Immunostaining revealed that occludin degradation is co-localized with ischemic autophagosomes. OGD-induced occludin degradation and permeability changes were significantly decreased by inhibition of autophagy using 3-methyladenine (3-MA). Enhanced autophagic activity and loss of occludin were also observed in brain capillaries isolated from rats with middle cerebral artery occlusion (MCAO). Intravenous administration of 3-MA inhibited these molecular changes in brain capillaries, and recovered the increased permeability as determined using Evans blue.
Our findings provide evidence that autophagy plays an important role in ischemia-induced occludin degradation and loss of BBB integrity.
Low serum progranulin (PGRN) is known to be associated with granulin (GRN) gene mutation and T alleles of GRN rs5848 polymorphism. However, there have been only a few Asian studies exploring these. ...We investigated the serum PGRN levels, rs5848 genotypes, and their relations with cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers in the Korean population. Serum PGRN levels, GRN rs5848 polymorphism, and GRN mutations were evaluated in 239 participants (22 cognitively unimpaired participants and 217 patients with neurodegenerative diseases). CSF AD biomarkers were also evaluated in 214 participants. There was no significant difference in the serum PGRN levels among the diagnostic groups. We could not find any GRN mutation carrier in our sample. The differences in the frequencies of the rs5848 genotypes among the clinical groups or the effects of the rs5848 genotypes on serum PGRN were not observed. There was no correlation between the serum PGRN level or rs5848 genotype and CSF AD biomarkers. Neither the T allele nor the TT genotype had an effect on the development of AD. Our results showed that serum PGRN levels were not associated with rs5848 genotypes, indicating that multiple single nucleotide polymorphisms might affect PGRN concentrations in an ethnicity-specific manner.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Coupling is the process that links bone resorption to bone formation in a temporally and spatially coordinated manner within the remodeling cycle. Several lines of evidence point to the critical ...roles of osteoclast-derived coupling factors in the regulation of osteoblast performance. Here, we used a fractionated secretomic approach and identified the axon-guidance molecule SLIT3 as a clastokine that stimulated osteoblast migration and proliferation by activating β-catenin. SLIT3 also inhibited bone resorption by suppressing osteoclast differentiation in an autocrine manner. Mice deficient in Slit3 or its receptor, Robo1, exhibited osteopenic phenotypes due to a decrease in bone formation and increase in bone resorption. Mice lacking Slit3 specifically in osteoclasts had low bone mass, whereas mice with either neuron-specific Slit3 deletion or osteoblast-specific Slit3 deletion had normal bone mass, thereby indicating the importance of SLIT3 as a local determinant of bone metabolism. In postmenopausal women, higher circulating SLIT3 levels were associated with increased bone mass. Notably, injection of a truncated recombinant SLIT3 markedly rescued bone loss after an ovariectomy. Thus, these results indicate that SLIT3 plays an osteoprotective role by synchronously stimulating bone formation and inhibiting bone resorption, making it a potential therapeutic target for metabolic bone diseases.
Single‐atom catalysts (SACs), in which metal atoms are dispersed on the support without forming nanoparticles, have been used for various heterogeneous reactions and most recently for electrochemical ...reactions. In this Minireview, recent examples of single‐atom electrocatalysts used for the oxygen reduction reaction (ORR), hydrogen oxidation reaction (HOR), hydrogen evolution reaction (HER), formic acid oxidation reaction (FAOR), and methanol oxidation reaction (MOR) are introduced. Many density functional theory (DFT) simulations have predicted that SACs may be effective for CO2 reduction to methane or methanol production while suppressing H2 evolution, and those cases are introduced here as well. Single atoms, mainly Pt single atoms, have been deposited on TiN or TiC nanoparticles, defective graphene nanosheets, N‐doped covalent triazine frameworks, graphitic carbon nitride, S‐doped zeolite‐templated carbon, and Sb‐doped SnO2 surfaces. Scanning transmission electron microscopy, extended X‐ray absorption fine structure measurement, and in situ infrared spectroscopy have been used to detect the single‐atom structure and confirm the absence of nanoparticles. SACs have shown high mass activity, minimizing the use of precious metal, and unique selectivity distinct from nanoparticle catalysts owing to the absence of ensemble sites. Additional features that SACs should possess for effective electrochemical applications were also suggested.
Down to the atom: Single‐atom catalysts, in which metal atoms are dispersed on the support without forming nanoparticles, have recently been used for electrochemical reactions. In this Minireview, recent examples of single‐atom electrocatalysts for reactions including oxygen reduction, hydrogen oxidation, hydrogen evolution, formic acid oxidation, and methanol oxidation are introduced.
Despite rapidly growing interest in harnessing machine learning in the study of quantum many-body systems, training neural networks to identify quantum phases is a nontrivial challenge. The key ...challenge is in efficiently extracting essential information from the many-body Hamiltonian or wave function and turning the information into an image that can be fed into a neural network. When targeting topological phases, this task becomes particularly challenging as topological phases are defined in terms of nonlocal properties. Here, we introduce quantum loop topography (QLT): a procedure of constructing a multidimensional image from the "sample" Hamiltonian or wave function by evaluating two-point operators that form loops at independent Monte Carlo steps. The loop configuration is guided by the characteristic response for defining the phase, which is Hall conductivity for the cases at hand. Feeding QLT to a fully connected neural network with a single hidden layer, we demonstrate that the architecture can be effectively trained to distinguish the Chern insulator and the fractional Chern insulator from trivial insulators with high fidelity. In addition to establishing the first case of obtaining a phase diagram with a topological quantum phase transition with machine learning, the perspective of bridging traditional condensed matter theory with machine learning will be broadly valuable.
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