Outbreak of Streptococcus pyogenes emm89 ST646 in a head and neck surgical oncology ward

Streptococcus pyogenes causes a variety of human infections, and hospital outbreaks with this pathogen have also been reported. The purpose of this study is to describe the clinical characteristics of an outbreak of S. pyogenes involving 15 patients and four healthcare workers (HCWs), as well as the molecular characteristics of the causative isolates. The course and response to the outbreak were reviewed, and information on the characteristics of the patients was extracted retrospectively from the medical records. Whole-genome sequencing of the 16 causative isolates (14 from patients and two from HCWs) was also performed. All 15 patients were postoperative of head and neck cancer with tracheotomy, and 12 had invasive infections, primarily surgical site infections, all of which resolved without causing serious illness. All but the first case was detected more than 7 days after admission. S. pyogenes was detected in two patients after empiric antimicrobial administration was performed on all inpatients and HCWs, and the outbreak was finally contained in approximately 2 months. All isolates detected in patients and HCWs belonged to emm89/clade 3, a hypervirulent clone that has emerged worldwide and was classified as sequence type 646. These isolates had single nucleotide polymorphism (SNP) differences of zero to one, indicating clonal transmission. This study demonstrated an outbreak of S. pyogenes emm89/clade 3 in a ward of patients with head and neck cancer. The global emergence of hypervirulent isolates may increase the risk of outbreaks among high-risk patients.

IMPORTANCE

This study describes an outbreak of Streptococcus pyogenes that occurred in a ward caring for patients with head and neck cancer and tracheostomies. Many cases of invasive infections occurred in a short period, and extensive empiric antimicrobial administration on patients and healthcare workers was performed to control the outbreak. Whole-genome sequencing analysis of the causative strains confirmed that it was a monoclonal transmission of strains belonging to emm89/clade 3. The epidemiology and clinical characteristics of S. pyogenes infections have changed with the replacement of the prevalent clones worldwide. In the 1980s, there was a reemergence of S. pyogenes infections in high-income countries due to the spread of hypervirulent emm1 strains. emm89/clade 3 has recently been spreading worldwide and shares common features with emm1, including increased production of two toxins, NADase, and streptolysin O. The outbreak reported here may reflect the high spreading potential and virulence of emm89/clade 3.

Strong plastic responses in aerenchyma formation in F1 hybrids of Imperata cylindrica under different soil moisture conditions

Hybrids can express traits plastically, enabling them to occupy environments that differ from parental environments. However, there is insufficient evidence demonstrating how phenotypic plasticity in specific traits mediates hybrid performance. Two parental ecotypes of Imperata cylindrica produce F1 hybrids. The E-type in wet habitats has larger internal aerenchyma than the C-type in dry habitats. This study evaluated relationships between habitat utilisation, aerenchyma plasticity, and growth of I. cylindrica accessions. We hypothesize that plasticity in expressing parental traits explains hybrid establishment in habitats with various soil moisture conditions. Aerenchyma formation was examined in the leaf midribs, rhizomes and roots of two parental ecotypes and their F1 hybrids in their natural habitats. In common garden experiments, we examined plastic aerenchyma formation in leaf midribs, rhizomes and roots of natural and artificial F1 hybrids and parental ecotypes and quantified vegetative growth performance. In the natural habitats where soil moisture content varied widely, the F1 hybrids showed larger variation in aerenchyma formation in rhizomes than their parental ecotypes. In the common garden experiments, F1 hybrids showed high plasticity of aerenchyma formation in rhizomes, and their growth was similar to that of C-type and E-type under drained and flooded conditions, respectively. The results demonstrate that F1 hybrids of I. cylindrica exhibit plasticity in aerenchyma development in response to varying local soil moisture content. This characteristic allows the hybrids to thrive in diverse soil moisture conditions.

Kluyvera georgiana Bacteremia Due to Acute Cholangitis: A Report of the First Known Case and a Literature Review

We herein present the first known case of bacteremia caused by Kluyvera georgiana in a 67-year-old female undergoing chemotherapy for recurrent pancreatic cancer. The patient underwent choledochojejunotomy and thereafter developed ascending cholangitis. The diagnosis of K. georgiana was confirmed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. A literature review of Kluyvera spp. infections indicated potential risk factors including an underlying malignancy and immunosuppression. Although Kluyvera spp. infections are typically sensitive to antibiotics, multidrug resistance is possible. This case highlights the importance of the early diagnosis and treatment of K. georgiana and its associated risk factors.

Proof of concept testing of a positive reference material for in vivo and in vitro sensitization testing of medical devices

In vivo skin sensitization tests are required to evaluate the biological safety of medical devices in contact with living organisms to provide safe medical care to patients. Negative and positive reference materials have been developed for biological tests of cytotoxicity, implantation, hemolysis, and in vitro skin irritation. However, skin sensitization tests are lacking. In this study, polyurethane sheets containing 1 wt/wt % 2,4-dinitrochlorobenzene (DNCB-PU) were developed and evaluated as a positive reference material for skin sensitization tests. DNCB-PU sheet extracts prepared with sesame oil elicited positive sensitization responses for in vivo sensitization potential in the guinea pig maximization test and the local lymph node assay. Furthermore, DNCB-PU sheet extracts prepared with water and acetonitrile, 10% fetal bovine serum-containing medium, or sesame oil elicited positive sensitization responses as alternatives to animal testing based on the amino acid derivative reactivity assay, human cell line activation test, and epidermal sensitization assay, respectively. These data suggest that the DNCB-PU sheet is an effective extractable positive reference material for in vivo and in vitro skin sensitization testing in medical devices. The formulation of this reference material will lead to the development of safer medical devices that contribute to patient safety.

A case of hypervirulent K1-ST23 Klebsiella pneumoniae endocarditis and papillary muscle rupture secondary to multiple site abscesses

Hypervirulent Klebsiella pneumoniae (hvKP) causes multisite infections and abscesses. However, endocarditis is a rare presentation of hvKP infection. Herein, we report a case of K. pneumoniae native valve infective endocarditis secondary to community-acquired liver and prostate abscesses. The patient developed papillary muscle rupture, leading to mitral regurgitation, and underwent emergent mitral valve replacement. The diagnosis of endocarditis was confirmed microbiologically and histologically. The causative strain belonged to the hypermucoid K1 capsular genotype and possessed the rmpA gene. The genome sequence was deposited in GenBank under the accession number JAQZBZ000000000.

Comparative Analysis of Maternal Colostrum and Colostrum Replacer Effects on Immunity, Growth, and Health of Japanese Black Calves

Maternal colostrum (MC) is an important source of nutrients and immune factors for newborn calves. However, when colostrum is unavailable or of poor quality, a colostrum replacer (CR) may be a suitable alternative to MC. As stock-raising farmers must make informed decisions about colostrum feeding management, this study was conducted to determine the effect of feeding MC versus CR on the promotion of immunological status, growth, and health in pre-weaned Japanese black (JB) calves. Sixteen newborn JB calves were fed MC after birth, and 16 JB calves were fed CR. For the MC group, the numbers of γδ T cells, CD4+ cells, CD8+ cells, CD4+CD8+ cells, B cells, and MHC class II+ cells were significantly higher compared with the CR group. Furthermore, the expression levels of interleukin (IL)-1β-, IL-2-, and interferon-γ (IFN-γ)-encoding mRNAs were significantly higher in the MC group compared with the CR group. A lower incidence of disease in 1-month-old calves and higher carcass weight in the MC group were observed compared with the CR group. These results suggest that CR activates the immune system delayed in calves compared with MC. MC increases populations of various immunocompetent cells, which can reduce infection rates and improve body weight gain.

Boltzmann machines and quantum many-body problems

Analyzing quantum many-body problems and elucidating the entangled structure of quantum states is a significant challenge common to a wide range of fields. Recently, a novel approach using machine learning was introduced to address this challenge. The idea is to 'embed' nontrivial quantum correlations (quantum entanglement) into artificial neural networks. Through intensive developments, artificial neural network methods are becoming new powerful tools for analyzing quantum many-body problems. Among various artificial neural networks, this topical review focuses on Boltzmann machines and provides an overview of recent developments and applications.

Deep Learning-Based Single-View Fluorescence Dose Reconstruction for 3D Dosimetry

PURPOSE/OBJECTIVE(S)

3D dose distribution measurement is crucial for precise radiotherapy. Radiation-excited fluorescence imaging has potential for the 3D dosimetry with high spatial resolution, but multiple fluorescence images from different view-angles are required for analytical reconstruction techniques. Furthermore, the imaging data are contaminated by anisotropic Cherenkov light emission and statistical noise. This project aims to establish a novel deep learning-based model to predict 3D dose distributions from a single-view 2D fluorescence image while simultaneously removing the adverse effects of Cherenkov signals and other noises.

MATERIALS/METHODS

A total of 124 single-aperture static photon beams were delivered to an acrylic tank containing 1 g/L quinine hemisulfate water solution with varying aperture shapes and collimator angle. The emitted optical signals were detected by a low-cost CMOS camera for 20 seconds, and image pre-processing was performed to obtain input 2D fluorescence images with 0.3 × 0.3 mm spatial resolution. 3D back-projected dose distribution images were also calculated from the input fluorescence images. Ground-truth of 3D dose distributions and 2D field map images were obtained from a clinical treatment planning system with 1.4 × 1.4 × 1.4 mm spatial resolution. The proposed deep learning-based dose reconstruction method involved 3 steps. First, 2D fluence map images at the bottom plane of the tank were predicted from the fluorescence images by using a customized convolutional neural network (CNN). Second, the predicted fluence map images were transformed into the 2D field map images on the isocenter plane by applying perspective transformation. Finally, 2D dose distributions at a given radiological depth were calculated by using the predicted field map images, the back-projected dose distribution images, and the radiological depth value as inputs of a shallow CNN. Both CNN models were trained separately, and the 3D dose distributions were predicted by concatenating the output 2D dose distributions at various radiological depths.

RESULTS

The proposed CNN model yielded accurate 2D field map images. Averaged Dice similarity coefficient and mean absolute error of the field maps in the test data was 92.0% ± 4.6% and 0.0132 ± 0.0113, respectively. Moreover, our deep learning-based approach was able to predict accurate 3D dose distributions from the 2D fluorescence images. Mean squared error and averaged 3D gamma passing ratio (3%/3mm) were 9.55 mGy ± 6.8 mGy and 86.3% ± 9.86%, respectively.

CONCLUSION

Theproposed deep learning-based method calculated accurate 3D dose distributions from a single-view 2D fluorescence image. Since this technique require only a single CMOS camera image and fluorescent material, it can be readily used for any external radiotherapy modalities, including SRS/SBRT with small fields. This method is useful for acquiring 3D dose distribution data for precise dose verification within a few seconds.

Deep learning-based fluorescence image correction for high spatial resolution precise dosimetry

Objective.While radiation-excited fluorescence imaging has great potential to measure absolute 2D dose distributions with high spatial resolution, the fluorescence images are contaminated by noise or artifacts due to Cherenkov light, scattered light or background noise. This study developed a novel deep learning-based model to correct the fluorescence images for accurate dosimetric application.Approach.181 single-aperture static photon beams were delivered to an acrylic tank containing quinine hemisulfate water solution. The emitted radiation-exited optical signals were detected by a complementary metal-oxide semiconductor camera to acquire fluorescence images with 0.3 × 0.3 mm2pixel size. 2D labels of projected dose distributions were obtained by applying forward projection calculation of the 3D dose distributions calculated by a clinical treatment planning system. To calibrate the projected dose distributions for Cherenkov angular dependency, a novel empirical Cherenkov emission calibration method was performed. Total 400-epoch supervised learning was applied to a convolutional neural network (CNN) model to predict the projected dose distributions from fluorescence images, gantry, and collimator angles. Accuracy of the calculated projected dose distributions was evaluated with that of uncorrected or conventional methods by using a few quantitative evaluation metrics.Main results.The projected dose distributions corrected by the empirical Cherenkov emission calibration represented more accurate noise-free images than the uncalibrated distributions. The proposed CNN model provided accurate projected dose distributions. The mean absolute error of the projected dose distributions was improved from 2.02 to 0.766 mm·Gy by the CNN model correction. Moreover, the CNN correction provided higher gamma index passing rates for three different threshold criteria than the conventional methods.Significance.The deep learning-based method improves the accuracy of dose distribution measurements. This technique will also be applied to optical signal denoising or Cherenkov light discrimination in other imaging modalities. This method will provide an accurate dose verification tool with high spatial resolution.

Learning image representations for content-based image retrieval of radiotherapy treatment plans

Objective.In this work, we propose a content-based image retrieval (CBIR) method for retrieving dose distributions of previously planned patients based on anatomical similarity. Retrieved dose distributions from this method can be incorporated into automated treatment planning workflows in order to streamline the iterative planning process. As CBIR has not yet been applied to treatment planning, our work seeks to understand which current machine learning models are most viable in this context.Approach.Our proposed CBIR method trains a representation model that produces latent space embeddings of a patient's anatomical information. The latent space embeddings of new patients are then compared against those of previous patients in a database for image retrieval of dose distributions. All source code for this project is available on github.Main results.The retrieval performance of various CBIR methods is evaluated on a dataset consisting of both publicly available image sets and clinical image sets from our institution. This study compares various encoding methods, ranging from simple autoencoders to more recent Siamese networks like SimSiam, and the best performance was observed for the multitask Siamese network.Significance.Our current results demonstrate that excellent image retrieval performance can be obtained through slight changes to previously developed Siamese networks. We hope to integrate CBIR into automated planning workflow in future works.

A probabilistic deep learning model of inter-fraction anatomical variations in radiotherapy

Objective. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. To assess the need for adaptation, motion models can be used to simulate dominant motion patterns and assess anatomical robustness before delivery. Traditionally, such models are based on principal component analysis (PCA) and are either patient-specific (requiring several scans per patient) or population-based, applying the same set of deformations to all patients. We present a hybrid approach which, based on population data, allows to predict patient-specific inter-fraction variations for an individual patient.Approach. We propose a deep learning probabilistic framework that generates deformation vector fields warping a patient's planning computed tomography (CT) into possible patient-specific anatomies. This daily anatomy model (DAM) uses few random variables capturing groups of correlated movements. Given a new planning CT, DAM estimates the joint distribution over the variables, with each sample from the distribution corresponding to a different deformation. We train our model using dataset of 312 CT pairs with prostate, bladder, and rectum delineations from 38 prostate cancer patients. For 2 additional patients (22 CTs), we compute the contour overlap between real and generated images, and compare the sampled and 'ground truth' distributions of volume and center of mass changes.Results. With a DICE score of 0.86 ± 0.05 and a distance between prostate contours of 1.09 ± 0.93 mm, DAM matches and improves upon previously published PCA-based models, using as few as 8 latent variables. The overlap between distributions further indicates that DAM's sampled movements match the range and frequency of clinically observed daily changes on repeat CTs.Significance. Conditioned only on planning CT values and organ contours of a new patient without any pre-processing, DAM can accurately deformations seen during following treatment sessions, enabling anatomically robust treatment planning and robustness evaluation against inter-fraction anatomical changes.

Increased risk of biliary infection after biliary stent placement in users of proton pump inhibitors

OBJECTIVES

Proton pump inhibitors (PPIs) are widely prescribed medications for gastric acid-induced diseases. Despite the effectiveness of PPIs, recent evidence suggested an increased risk of various bacterial infections in PPI users. The current study was conducted to evaluate the risk of biliary infection after endoscopic biliary stent placement in regular users of PPIs.

METHODS

Consecutive patients with a native papilla who underwent endoscopic retrograde cholangiopancreatography and stent placement for biliary stricture between January 2010 and August 2019 were included in this retrospective study. The cumulative incidences of biliary infection were compared between regular and non-regular PPI users.

RESULTS

During the study period, 270 regular PPI users and 146 non-regular PPI users were included in the analyses. Age, gender, and indication of endoscopic retrograde cholangiopancreatography were not different between the two groups. The incidences of biliary infection were 43% in regular PPI users and 36% in non-regular PPI users but the time to biliary infection was significantly shorter in regular PPI users than in non-regular users (28 vs. 87 days, p = 0.01). The cumulative incidence of biliary infection was significantly higher in regular PPI users compared with non-regular users (p = 0.008). The multivariable Cox regression analysis also showed a significantly higher hazard ratio of biliary infection in regular PPI users (1.62 [95% confidence interval 1.16-2.26; p = 0.005]).

CONCLUSIONS

Regular PPI use was associated with a higher risk of biliary infection after endoscopic biliary drainage. Inappropriate PPI use should be avoided.

Fully automated segmentally boosted VMAT

PURPOSE

Treatment planning for volumetric modulated arc therapy (VMAT) typically involves the use of multiple arcs to achieve sufficient intensity modulation. Alternatively, we can perform segment boosting to achieve similar intensity modulation while also reducing the number of control points used. Here, we propose the MetaPlanner Boosted VMAT (MPBV) approach, which generates boosted VMAT plans through a fully automated framework.

METHODS

The proposed MPBV approach is an open-source framework that consists of three main stages: meta-optimization of treatment plan hyperparameters, fast beam angle optimization on a coarse dose grid to select desirable segments for boosting, and final plan generation (i.e., constructing the boosted VMAT arc and performing optimization).

RESULTS

Performance for the MPBV approach is evaluated on 21 prostate cases and 6 head and neck cases using clinically relevant plan quality metrics (i.e., target coverage, dose conformity, dose homogeneity, and OAR sparing). As compared to two baseline methods with multiple arcs, MPBV maintains or improves dosimetric performance for the evaluated metrics while substantially reducing average estimated delivery times (from 2.6 to 2.1 min).

CONCLUSION

Our proposed MPBV approach provides an automated framework for producing high-quality VMAT plans that uses fewer control points and reduces delivery time as compared to traditional approaches with multiple arcs. MPBV applies automated treatment planning to segmentally boosted VMAT to address the beam utilization inefficiencies of traditional VMAT approaches that use multiple full arcs.

Ovarian high-grade serous carcinoma cells with low SMARCA4 expression and high SMARCA2 expression contribute to platinum resistance

Platinum resistance is a major obstacle to the treatment of ovarian cancer and is correlated with poor clinical outcomes. Intratumor heterogeneity plays a key role in chemoresistance. Recent studies have emphasized the contributions of genetic and epigenetic factors to the development of intratumor heterogeneity. Although the clinical significance of multi-subunit chromatin remodeler, switch/sucrose nonfermenting (SWI/SNF) complexes in cancers has been reported, the impacts of SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily A, member 4/subfamily A, member 2 (SMARCA4/A2) expression patterns in human cancer tissues have not been fully elucidated. Here, we show that low expression of SMARCA4 and high expression of SMARCA2 are associated with platinum resistance in ovarian high-grade serous carcinoma (HGSC) cells. We used fluorescence multiplex immunohistochemistry (fmIHC) to study resected specimens; we examined heterogeneity in human HGSC tissues at the single-cell level, which revealed that the proportion of cells with the SMARCA4^low /SMARCA2^high phenotype was positively correlated with clinical platinum-resistant recurrence. We used stable transfection of SMARCA2 and siRNA knockdown of SMARCA4 to generate HGSC cells with the SMARCA4^low /SMARCA2^high phenotype; these cells had the greatest resistance to carboplatin. Bioinformatics analyses revealed that the underlying mechanism involved in substantial alterations to chromatin accessibility and resultant fibroblast growth factor (FGF) signaling activation, MAPK pathway activation, BCL2 overexpression, and reduced carboplatin-induced apoptosis; these were confirmed by in vitro functional experiments. Furthermore, in vivo experiments in an animal model demonstrated that combination therapy with carboplatin and a fibroblast growth factor receptor (FGFR) inhibitor promoted cell death in HGSC xenografts. Taken together, these observations reveal a specific subpopulation of HGSC cells that is associated with clinical chemoresistance, which may lead to the establishment of a histopathological prediction system for carboplatin response. Our findings may facilitate the development of novel therapeutic strategies for platinum-resistant HGSC cells. © 2023 The Pathological Society of Great Britain and Ireland.

[A case of biliary panperitonitis due to intrahepatic bile duct rupture with intrahepatic bile duct tumor]

An 87-year-old man visited his previous doctor because of jaundice, abdominal pain, and disturbance of consciousness. He was diagnosed with cholangitis and panperitonitis and was referred to our hospital. Emergency laparotomy revealed biliary peritonitis. However, the bile leak point was unclear. Two days after surgery, endoscopic retrograde cholangiopancreatography was performed and revealed hilar bile duct stenosis, slight dilation of the intrahepatic bile duct, and bile leakage from the peripheral left intrahepatic bile duct to the abdominal free space. Endoscopic nasobiliary drainage was performed, and bile leakage decreased. He was discharged from our hospital with improvement from jaundice and peritonitis. Intrahepatic bile duct rupture with neoplastic obstruction of the bile duct is extremely rare. To date, only two cases of intrahepatic bile duct rupture with intrahepatic cholangiocarcinoma have been published.

Doping Asymmetry and Layer-Selective Metal-Insulator Transition in Trilayer K_{3+x}C_{60}

Thin films provide a versatile platform to tune electron correlations and explore new physics in strongly correlated materials. Epitaxially grown thin films of the alkali-doped fulleride K_{3+x}C_{60}, for example, exhibit intriguing phenomena, including Mott transitions and superconductivity, depending on dimensionality and doping. Surprisingly, in the trilayer case, a strong electron-hole doping asymmetry has been observed in the superconducting phase, which is absent in the three-dimensional bulk limit. Using density-functional theory plus dynamical mean-field theory, we show that this doping asymmetry results from a substantial charge reshuffling from the top layer to the middle layer. While the nominal filling per fullerene is close to n=3, the top layer rapidly switches to an n=2 insulating state upon hole doping, which implies a doping asymmetry of the superconducting gap. The interlayer charge transfer and layer-selective metal-insulator transition result from the interplay between crystal field splittings, strong Coulomb interactions, and an effectively negative Hund coupling. This peculiar charge reshuffling is absent in the monolayer system, which is an n=3 Mott insulator, as expected from the nominal filling.

[Investigation of Foreign Particles in Moderna COVID-19 Vaccine]

Particular batches of Moderna mRNA Coronavirus Disease 2019 (COVID-19) vaccine were recalled after foreign particles were found in some vaccine vials at the vaccination site in Japan in August 2021. We investigated the foreign particles at the request of the Ministry of Health, Labour and Welfare. Energy dispersive X-ray spectroscopy analysis suggested that the foreign particles found in the vials recalled from the vaccination sites were from stainless steel SUS 316L, which was in line with the findings of the root cause investigation by the manufacturer. The sizes of the observed particles ranged from <50 μm to 548 μm in the major axis. Similar foreign particles were also detected in 2 of the 5 vaccine vials of the same lot stored by the manufacturer, indicating that the foreign particles have already been administered to some people via vaccine. Observation of the vials of the same lot by digital microscope found smaller particles those were not detected by visual inspection, suggesting that more vials were affected. Contrarily, visual inspection and subvisible particulate matter test indicated no foreign particles in the vials of normal lots. Possible root cause and strategies to prevent such a deviation were discussed from technical and regulatory aspects.

Fermi Surface Expansion above Critical Temperature in a Hund Ferromagnet

Using a cluster extension of the dynamical mean-field theory, we show that strongly correlated metals subject to Hund's physics exhibit significant electronic structure modulations above magnetic transition temperatures. In particular, in a ferromagnet having a large local moment due to Hund's coupling (Hund's ferromagnet), the Fermi surface expands even above the Curie temperature (T_{C}) as if a spin polarization occurred. Behind this phenomenon, effective "Hund's physics" works in momentum space, originating from ferromagnetic fluctuations in the strong-coupling regime. The resulting significantly momentum-dependent (spatially nonlocal) electron correlations induce an electronic structure reconstruction involving a Fermi surface volume change and a redistribution of the momentum-space occupation. Our finding will give a deeper insight into the physics of Hund's ferromagnets above T_{C}.

Superconductivity in infinite-layer nickelates

The recent discovery of the superconductivity in the doped infinite layer nickelatesRNiO₂(R= La, Pr, Nd) is of great interest since the nickelates are isostructural to doped (Ca, Sr)CuO₂having superconducting transition temperature (T_c) of about 110 K. Verifying the commonalities and differences between these oxides will certainly give a new insight into the mechanism of highT_csuperconductivity in correlated electron systems. In this paper, we review experimental and theoretical works on this new superconductor and discuss the future perspectives for the 'nickel age' of superconductivity.

Magnetic structures and electronic properties of cubic-pyrochlore ruthenates from first principles

The magnetic ground states ofR₂Ru₂O₇andA₂Ru₂O₇withR= Pr, Gd, Ho, and Er, as well asA= Ca, Cd are predicted devising a combination of the cluster-multipole (CMP) theory and spin-density-functional theory (SDFT). The strong electronic correlation effects are estimated by the constrained-random-phase approximation (cRPA) and taken into account within the dynamical-mean-field theory (DMFT). The target compounds feature d-orbital magnetism on Ru⁴⁺and Ru⁵⁺ions forRandA, respectively, as well as f-orbital magnetism on theRsite, which leads to an intriguing interplay of magnetic interactions in a strongly correlated system. We find CMP + SDFT is capable of describing the magnetic ground states in these compounds. The cRPA captures a difference in the screening strength betweenR₂Ru₂O₇andA₂Ru₂O₇compounds, which leads to a qualitative and quantitative understanding of the electronic properties within DMFT.

Meta-optimization for fully automated radiation therapy treatment planning

Objective. Radiation therapy treatment planning is a time-consuming process involving iterative adjustments of hyperparameters. To automate the treatment planning process, we propose a meta-optimization framework, called MetaPlanner (MP).Approach. Our MP algorithm automates planning by performing meta-optimization of treatment planning hyperparameters. The algorithm uses a derivative-free method (i.e. parallel Nelder-Mead simplex search) to search for weight configurations that minimize a meta-scoring function. Meta-scoring is performed by constructing a tier list of the relevant considerations (e.g. dose homogeneity, conformity, spillage, and OAR sparing) to mimic the clinical decision-making process. Additionally, we have made our source code publicly available via github.Main results. The proposed MP method is evaluated on two datasets (21 prostate cases and 6 head and neck cases) collected as part of clinical workflow. MP is applied to both IMRT and VMAT planning and compared to a baseline of manual VMAT plans. MP in both IMRT and VMAT scenarios has comparable or better performance than manual VMAT planning for all evaluated metrics.Significance. Our proposed MP provides a general framework for fully automated treatment planning that produces high quality treatment plans. Our MP method promises to substantially reduce the workload of treatment planners while maintaining or improving plan quality.

Discovery of an F-actin-binding small molecule serving as a fluorescent probe and a scaffold for functional probes

Actin is a ubiquitous cytoskeletal protein, forming a dynamic network that generates mechanical forces in the cell. There is a growing demand for practical and accessible tools for dissecting the role of the actin cytoskeleton in cellular function, and the discovery of a new actin-binding small molecule is an important advance in the field, offering the opportunity to design and synthesize of new class of functional molecules. Here, we found an F-actin–binding small molecule and introduced two powerful tools based on a new class of actin-binding small molecule: One enables visualization of the actin cytoskeleton, including super-resolution imaging, and the other enables highly specific green light–controlled fragmentation of actin filaments, affording unprecedented control of the actin cytoskeleton and its force network in living cells.

Orbital Isotropy of Magnetic Fluctuations in Correlated Electron Materials Induced by Hund's Exchange Coupling

Characterizing nonlocal magnetic fluctuations in materials with strong electronic Coulomb interactions remains one of the major outstanding challenges of modern condensed matter theory. In this Letter, we address the spatial symmetry and orbital structure of magnetic fluctuations in perovskite materials. To this aim, we develop a consistent multiorbital diagrammatic extension of dynamical mean-field theory, which we apply to an anisotropic three-orbital model of cubic t_{2g} symmetry. We find that the form of spatial spin fluctuations is governed by the local Hund's coupling. For small values of the coupling, magnetic fluctuations are anisotropic in orbital space, which reflects the symmetry of the considered t_{2g} model. Large Hund's coupling enhances collective spin excitations, which mixes orbital and spatial degrees of freedom, and magnetic fluctuations become orbitally isotropic. Remarkably, this effect can be seen only in two-particle quantities; single-particle observables remain anisotropic for any value of the Hund's coupling. Importantly, we find that the orbital isotropy can be induced both at half filling and for the case of four electrons per lattice site, where the magnetic instability is associated with different, antiferromagnetic and ferromagnetic, modes, respectively.

Tenosynovitis caused by Mycobacterium marseillense, initially identified as Mycobacterium avium complex using AccuProbe and COBAS TaqMan

Background

Mycobacterium marseillense is a new species of the Mycobacterium avium complex. There has been only a few human infections caused by M. marseillense worldwide.

Case presentation

We report a case of tenosynovitis caused by M. marseillense in an immunocompetent adult in Japan. The isolate was initially identified as M. intracellulare using commercial real time polymerase chain reaction assays and later identified as M. marseillense with sequencing of the the rpoB and hsp65 regions, and matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS).

Conclusions

This is the first case reporting on M. marseillense generating a positive result with commercial real time PCR assays targeting MAC. Human infections associated by M. marseillense might be underreported due to similarities with Mycobacterium intracellulare. To accurately identify M. marseillese, MALDI-TOF MS might provide a rapid and reliable method.

Use of proton pump inhibitors and cholangitis complicated with multi-drug resistant bacteria

BACKGROUND

Multidrug-resistant bacteria (MDRB) has rapidly spread worldwide and become a serious problem. Proton pump inhibitors (PPIs) are a class of commonly prescribed medications, but recent studies have suggested the increased risk of infection with MDRB in PPI users. We evaluated the association between PPI use and incidence of cholangitis with MDRB.

METHODS

Consecutive patients who underwent endoscopic retrograde cholangiopancreatography (ERCP) between January 2010 and August 2019 were included in this retrospective study. The incidence of cholangitis with MDRB was compared between regular and non-regular PPI users.

RESULTS

A total of 1224 regular PPI users and 1528 non-regular PPI users were identified. There was no clinically significant difference in age and sex between the groups. Indication of ERCP was different between the groups. The number of ERCP sessions during the study periods was higher in regular PPI users. The incidence of cholangitis with MDRB was significantly higher in regular PPI users (3.0% vs 1.1%; P < .001). Multivariable-adjusted odds ratio for cholangitis with MDRB comparing regular PPI users to non-regular users was 2.19 (95% confidence interval 1.20-4.00; P = .01).

CONCLUSIONS

Regular PPI use was associated with a higher risk of cholangitis with MDRB.

Purifying Deep Boltzmann Machines for Thermal Quantum States

We develop two cutting-edge approaches to construct deep neural networks representing the purified finite-temperature states of quantum many-body systems. Both methods commonly aim to represent the Gibbs state by a highly expressive neural-network wave function, exemplifying the idea of purification. The first method is an entirely deterministic approach to generate deep Boltzmann machines representing the purified Gibbs state exactly. This strongly assures the remarkable flexibility of the ansatz which can fully exploit the quantum-to-classical mapping. The second method employs stochastic sampling to optimize the network parameters such that the imaginary time evolution is well approximated within the expressibility of neural networks. Numerical demonstrations for transverse-field Ising models and Heisenberg models show that our methods are powerful enough to investigate the finite-temperature properties of strongly correlated quantum many-body systems, even when the problematic effect of frustration is present.

Trial protocol: a randomised controlled trial to verify the non-inferiority of a partially covered self-expandable metal stent to an uncovered self-expandable metal stent for biliary drainage during neoadjuvant therapy in patients with pancreatic cancer with obstructive jaundice (PUN-NAC trial)

INTRODUCTION

Neoadjuvant chemotherapy or neoadjuvant chemoradiotherapy (NAC/NACRT) for resectable/borderline resectable pancreatic cancers was recently performed to improve clinical outcomes and led to good results, although it remains controversial whether NAC/NACRT is beneficial for resectable pancreatic cancer. A few recent studies revealed longer patency and lower cost related to the stent occlusion of a metal stent than those of a plastic stent during NAC/NACRT. It also remains controversial which type of self-expandable metal stent (SEMS) is the most suitable for patients with resectable/borderline resectable pancreatic cancer during NAC/NACRT: an uncovered SEMS (USEMS), a fully covered SEMS (FCSEMS) or a partially covered SEMS (PCSEMS). So far, two randomised controlled trials indicated that a USEMS and an FCSEMS were similar in preoperative stent dysfunction and adverse event rate. Thus, we aimed to verify the non-inferiority of a PCSEMS to a USEMS in this multicentre randomised controlled trial.

METHODS AND ANALYSIS

We designed a multicentre randomised controlled trial, for which we will recruit 100 patients with resectable/borderline resectable pancreatic cancer and distal biliary obstruction scheduled for NAC/NACRT from 13 high-volume institutions. Patients will be randomly allocated to the PCSEMS group or USEMS group. The primary outcome measure is the preoperative biliary event rate. Data will be analysed after completion of the study. We will calculate the 95% CIs of the incidence of preoperative biliary events in each group and analyse whether the difference between them is within the non-inferiority margin (10%).

ETHICS AND DISSEMINATION

This study has been approved by the institutional review board of Hokkaido University Hospital. The results will be submitted for presentation at an international medical conference and published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

UMIN000041737; jRCT1012200002.

Helping restricted Boltzmann machines with quantum-state representation by restoring symmetry

The variational wave functions based on neural networks have recently started to be recognized as a powerful ansatz to represent quantum many-body states accurately. In order to show the usefulness of the method among all available numerical methods, it is imperative to investigate the performance in challenging many-body problems for which the exact solutions are not available. Here, we construct a variational wave function with one of the simplest neural networks, the restricted Boltzmann machine (RBM), and apply it to a fundamental but unsolved quantum spin Hamiltonian, the two-dimensionalJ₁-J₂Heisenberg model on the square lattice. We supplement the RBM wave function with quantum-number projections, which restores the symmetry of the wave function and makes it possible to calculate excited states. Then, we perform a systematic investigation of the performance of the RBM. We show that, with the help of the symmetry, the RBM wave function achieves state-of-the-art accuracy both in ground-state and excited-state calculations. The study shows a practical guideline on how we achieve accuracy in a controlled manner.

Performance evaluation of bactericidal effect and endotoxin inactivation by low-temperature ozone/hydrogen peroxide mixed gas exposure

This study evaluated the performance of a new O₃ /H₂ O₂ mixed gas sterilization instrument for killing microorganisms and inactivating bacterial endotoxin at low temperatures. Sterility assurance level was achieved by an over 6-log reduction of Geobacillus stearothermophilus ATCC 12980, and the decimal reduction value was 0.77 min in sterilization mode. A reduction of over 3 logs in Limulus amebocyte lysate coagulation activity of purified endotoxin from Escherichia coli was observed after treatment in endotoxin-inactivation mode. The same inactivation ability was observed when treating dried bacterial cells. Biomaterials made of polymer or metal did not exhibit cytotoxicity after gas exposure at O₃ concentrations below 200 ppm. As the results of human cell-based pyrogen testing, significant amounts of endotoxin that were over the limit for medical devices contacting cerebrospinal fluid (2.15 EU/device) were detected on scissors washed with a washer-disinfector and sterilized with ethylene oxide or autoclaving. In contrast, endotoxin decreased to 0.29 ± 0.05 EU/device after O₃ /H₂ O₂ mixed gas sterilization in endotoxin-inactivation mode. Compared to conventional gas sterilization methods, O₃ /H₂ O₂ mixed gas has high sterilization ability and a strong capacity to inactivate endotoxin. It is expected that this sterilization technology will improve the safety of reusable medical devices and utensils for regenerative medicine.

Calibrated uncertainty estimation for interpretable proton computed tomography image correction using Bayesian deep learning

Integrated-type proton computed tomography (pCT) measures proton stopping power ratio (SPR) images for proton therapy treatment planning, but its image quality is degraded due to noise and scatter. Although several correction methods have been proposed, techniques that include estimation of uncertainty are limited. This study proposes a novel uncertainty-aware pCT image correction method using a Bayesian convolutional neural network (BCNN). A DenseNet-based BCNN was constructed to predict both a corrected SPR image and its uncertainty from a noisy SPR image. A total 432 noisy SPR images of 6 non-anthropomorphic and 3 head phantoms were collected with Monte Carlo simulations, while true noise-free images were calculated with known geometric and chemical components. Heteroscedastic loss and deep ensemble techniques were performed to estimate aleatoric and epistemic uncertainties by training 25 unique BCNN models. 200-epoch end-to-end training was performed for each model independently. Feasibility of the predicted uncertainty was demonstrated after applying two post-hoc calibrations and calculating spot-specific path length uncertainty distribution. For evaluation, accuracy of head SPR images and water-equivalent thickness (WET) corrected by the trained BCNN models was compared with a conventional method and non-Bayesian CNN model. BCNN-corrected SPR images represent noise-free images with high accuracy. Mean absolute error in test data was improved from 0.263 for uncorrected images to 0.0538 for BCNN-corrected images. Moreover, the calibrated uncertainty represents accurate confidence levels, and the BCNN-corrected calibrated WET was more accurate than non-Bayesian CNN with high statistical significance. Computation time for calculating one image and its uncertainties with 25 BCNN models is 0.7 s with a consumer grade GPU. Our model is able to predict accurate pCT images as well as two types of uncertainty. These uncertainties will be useful to identify potential cause of SPR errors and develop a spot-specific range margin criterion, toward elaboration of uncertainty-guided proton therapy.

Caprylic acid enhances hydroxyhexylitaconic acid production in Aspergillus niger S17-5

AIM

Aspergillus niger S17-5 produces two alkylitaconic acids, 9-hydroxyhexylitaconic acid (9-HHIA) and 10-hydroxyhexylitaconic acid (10-HHIA), which have cytotoxic and polymer building block properties. In this study, we characterized the production of 9-HHIA and 10-HHIA by addition of their expected precursor, caprylic acid, to a culture of A. niger S17-5, and demonstrated batch fermentation of 9-HHIA and 10-HHIA in a jar fermenter with DO-stat.

METHODS AND RESULTS

Production titres of 9-HHIA and 10-HHIA from 3% glucose in a flask after 25 days cultivation were 0·35 and 1·01 g l^-1 respectively. Addition of 0·22 g l^-1 of caprylic acid to a suspension of resting cells of A. niger S17-5 led to 32% enhancement of total 9-HHIA and 10-HHIA production compared to no addition. No enhancement of the production of 9-HHIA or 10-HHIA by the addition of oxaloacetic acid was observed. Addition of caprylic acid to the culture at mid-growth phase was more suitable for 9-HHIA and 10-HHIA production due to less cell growth inhibition by caprylic acid. DO-stat batch fermentation with 3% glucose and 14·4 g l^-1 of caprylic acid in a 1·5 l jar fermenter resulted in the production titres of 9-HHIA and 10-HHIA being 0·48 and 1·54 g l^-1 respectively after 10 days of cultivation.

CONCLUSIONS

Addition of caprylic acid to the culture of A. niger S17-5 enhances 9-HHIA and 10-HHIA production.

SIGNIFICANCE AND IMPACT OF THE STUDY

These results suggest that 9-HHIA and 10-HHIA are synthesized with octanoyl-CoA derived from caprylic acid, and that the supply of octanoyl-CoA is a rate-limiting step in 9-HHIA and 10-HHIA production. To the best of our knowledge, this is the first report regarding the fermentation of naturally occurring itaconic acid derivatives in a jar fermenter.

Factors associated with silent cerebral events during catheter ablation for atrial fibrillation in the era of uninterrupted oral anticoagulation therapy

Background

A silent cerebral event (SCE), detected by brain magnetic resonance imaging (MRI), is defined as an acute new brain lesion without clinically apparent neurological deficit, and is frequently observed after catheter ablation in atrial fibrillation (AF) patients. Although the small number of SCEs does not cause neurocognitive dysfunction, the greater volume and/or larger number of SCE lesions are reportedly related to neuropsychological decline; SCE incidence may be a surrogate marker for the potential thromboembolic risk. Thus, strategies to reduce SCEs would be beneficial. Uninterrupted oral anticoagulation strategy for peri-procedural period reportedly reduced the risk of SCEs, but the incidence hovers at 10% to 30%. We sought factors associated with SCEs during catheter ablation for AF in patients with peri-procedural uninterrupted oral anticoagulation (OAC) therapy.

Methods

AF patients undergoing catheter ablation were eligible (n=255). All patients took non-vitamin K antagonist oral anticoagulants (NOACs) or vitamin K antagonist (VKA) for peri-procedural OAC (&gt;4 weeks) without interruption during the procedure. Brain MRI was performed within 2 days after the procedure to detect SCEs. Clinical characteristics and procedure-related parameters were compared between patients with and without SCEs.

Results

SCEs were detected in 59 patients (23%, SCE[+]) but not in 196 patients (77%, SCE[-]). Average age was higher in SCE[+] than SCE[-] (66±10 years vs. 62±12 years, p&lt;0.05). Persistent AF prevalence, CHADS2/CHA2DS2-VASc scores, and serum NT-ProBNP levels increased in SCE[+] vs. SCE[-]. In transthoracic/transesophageal echocardiography, left-atrial dimension (LAD) was larger and AF rhythm/spontaneous echo contrast were more frequently observed in SCE[+] than SCE[-]. SCE[+] had lower initial activated clotting time (ACT) before unfractionated heparin (UFH) injection and longer time to reach optimal ACT (&gt;300 sec) before trans-septal puncture than SCE [-]. In multivariate analysis, LAD, initial ACT before UFH injection, and time to reach optimal ACT were predictors for SCEs.

Conclusions

LAD and intra-procedural ACT kinetics affect SCEs during the procedure in patients with uninterrupted OAC for AF ablation. Shortening time to achieve optimal ACT during the procedure may reduce the risk of SCEs.

Funding Acknowledgement

Type of funding source: None

Fast spot-scanning proton dose calculation method with uncertainty quantification using a three-dimensional convolutional neural network

This study proposes a near-real-time spot-scanning proton dose calculation method with probabilistic uncertainty estimation using a three-dimensional convolutional neural network (3D-CNN). CT images and clinical target volume contours of 215 head and neck cancer patients were collected from a public database. 1484 and 488 plans were extracted for training and testing the 3D-CNN model, respectively. Spot beam data and single-field uniform dose (SFUD) labels were calculated for each plan using an open-source dose calculation toolkit. Variable spot data were converted into a fixed-size volume hereby called a 'peak map' (PM). 300 epochs of end-to-end training was implemented using sets of stopping power ratio and PM as input. Moreover, transfer learning techniques were used to adjust the trained model to SFUD doses calculated with different beam parameters and calculation algorithm using only 7.95% of training data used for the base model. Finally, accuracy of the 3D-CNN-calculated doses and model uncertainty was reviewed with several evaluation metrics. The 3D-CNN model calculates 3D proton dose distributions accurately with a mean absolute error of 0.778 cGyE. The predicted uncertainty is correlated with dose errors at high contrast edges. Averaged Sørensen-Dice similarity coefficients between binarized outputs and ground truths are mostly above 80%. Once the 3D-CNN model was well-trained, it can be efficiently fine-tuned for different proton doses by transfer learning techniques. Inference time for calculating one dose distribution is around 0.8 s for a plan using 1500 spot beams with a consumer grade GPU. A novel spot-scanning proton dose calculation method using 3D-CNN was developed. The 3D-CNN model is able to calculate 3D doses and uncertainty with any SFUD spot data and beam irradiation angles. Our proposed method should be readily extendable to other setups and plans and be useful for dose verification, image-guided proton therapy, or other applications.

A G-quadruplex-forming RNA aptamer binds to the MTG8 TAFH domain and dissociates the leukemic AML1-MTG8 fusion protein from DNA

MTG8 (RUNX1T1) is a fusion partner of AML1 (RUNX1) in the leukemic chromosome translocation t(8;21). The AML1-MTG8 fusion gene encodes a chimeric transcription factor. One of the highly conserved domains of MTG8 is TAFH which possesses homology with human TAF4 [TATA-box binding protein-associated factor]. To obtain specific inhibitors of the AML1-MTG8 fusion protein, we isolated RNA aptamers against the MTG8 TAFH domain using systematic evolution of ligands by exponential enrichment. All TAF aptamers contained guanine-rich sequences. Analyses of a TAF aptamer by NMR, CD, and mutagenesis revealed that it forms a parallel G-quadruplex structure in the presence of K⁺ . Furthermore, the aptamer could bind to the AML1-MTG8 fusion protein and dissociate the AML1-MTG8/DNA complex, suggesting that it can inhibit the dominant negative effects of AML1-MTG8 against normal AML1 function and serve as a potential therapeutic agent for leukemia.

Detection of MEAF6-PHF1 translocation in an endometrial stromal nodule

Endometrial stromal nodule (ESN) and low-grade endometrial stromal sarcoma (LG-ESS) are rare uterine tumors known as endometrial stromal tumors (ESTs). In addition to their similarity in morphological features, recent studies have shown that these two tumors share common genetic alterations. In particular, JAZF1-SUZ12 fusion is found with high frequency in both ESN and LG-ESS. In LG-ESS, some minor fusions have also been described, which include rearrangements involving PHF1 and its partner genes, such as JAZF1, EPC1, MEAF6, BRD8, EPC2, and MBTD1. Because of the rarity of ESN, genetic alterations other than JAZF1 fusion have not been investigated in detail. In this study, we performed a next-generation sequencing-based analysis in a case of ESN with peripheral metaplastic bone formation and detected MEAF6-PHF1 fusion, which has been reported in a small subset of uterine LG-ESSs and soft tissue ossifying fibromyxoid tumors. The finding that MEAF6-PHF1 fusion is a background genetic abnormality detected both in ESN and LG-ESS, along with JAZF1-SUZ12, provides further support for the similarity and continuum between these two types of ESTs. Furthermore, the association between metaplastic bone formation and MEAF6-PHF1 fusion may not be limited to soft tissue tumors.

Microbial Screening Based on the Mizoroki-Heck Reaction Permits Exploration of Hydroxyhexylitaconic-Acid-Producing Fungi in Soils

Recently, we developed a unique microbial screening method based on the Mizoroki–Heck reaction for itaconic acid (IA)-producing fungi. This method revealed that 37 out of 240 fungal strains isolated from soils produce vinyl compounds, including IA. In this study, we further characterized these compounds in order to verify that the screening method permits the isolation of fungi that produce other vinyl compounds, excluding IA. HPLC analysis showed that 11 out of 37 isolated strains produced IA, similar to Aspergillus terreus S12-1. Surprisingly, the other 8 isolated strains produced two vinyl compounds with HPLC retention times different from that of IA. From these strains, the vinyl compounds of Aspergillus niger S17-5 were characterized. Mass spectrometric and NMR analyses showed that they were identical to 8-hydroxyhexylitaconic acid (8-HHIA) and 9-HHIA. This finding showed that 8-HHIA- and 9-HHIA-producing fungi, as well as IA-producing fungi, are ubiquitously found in soils. Neither 8-HHIA nor 9-HHIA showed antibacterial or anti-inflammatory activities. Interestingly, 8-HHIA and 9-HHIA showed cytotoxicity against the human cervical cancer cell line (HeLa) and human diploid cell line (MRC-5), and MRC-5 only, respectively, compared to IA at the same concentration. This study indicates that the screening method could easily discover fungi producing 8-HHIA and 9-HHIA in soils.

Wannier90 as a community code: new features and applications

Wannier90 is an open-source computer program for calculating maximally-localised Wannier functions (MLWFs) from a set of Bloch states. It is interfaced to many widely used electronic-structure codes thanks to its independence from the basis sets representing these Bloch states. In the past few years the development of Wannier90 has transitioned to a community-driven model; this has resulted in a number of new developments that have been recently released in Wannier90 v3.0. In this article we describe these new functionalities, that include the implementation of new features for wannierisation and disentanglement (symmetry-adapted Wannier functions, selectively-localised Wannier functions, selected columns of the density matrix) and the ability to calculate new properties (shift currents and Berry-curvature dipole, and a new interface to many-body perturbation theory); performance improvements, including parallelisation of the core code; enhancements in functionality (support for spinor-valued Wannier functions, more accurate methods to interpolate quantities in the Brillouin zone); improved usability (improved plotting routines, integration with high-throughput automation frameworks), as well as the implementation of modern software engineering practices (unit testing, continuous integration, and automatic source-code documentation). These new features, capabilities, and code development model aim to further sustain and expand the community uptake and range of applicability, that nowadays spans complex and accurate dielectric, electronic, magnetic, optical, topological and transport properties of materials.

Placental Gene Expression and Offspring Temperament Trajectories: Predicting Negative Affect in Early Childhood

Exposure to prenatal stress increases offspring risk for long-term neurobehavioral impairments and psychopathology, such as Attention Deficit Hyperactivity Disorder (ADHD). Epigenetic regulation of glucocorticoid pathway genes may be a potential underlying mechanism by which maternal conditions 'program' the fetal brain for downstream vulnerabilities. The present study aims to investigate whether mRNA expression of glucocorticoid pathway genes in the placenta predict offspring negative affect during early childhood (between 6 and 24 months). Participants include 318 mother-child dyads participating in a longitudinal birth cohort study. Placental mRNA expression of glucocorticoid pathway genes (HSD11B1, HSD11B2, NR3C1, NCOR2) were profiled and negative affect traits of the offspring were measured at 6, 12, 18, and 24 months. HSD11B1 mRNA expression significantly predicted negative affect (β = -.09, SE = .04; p = .036), and Distress to Limitations trajectories (β = -.13, SE = .06; p = .016). NCOR2 mRNA expression significantly predicted Distress to Limitations (β = .43, SE = .21; p = .047), and marginally predicted Sadness trajectories (β = .39, SE = .21; p = .068). HSD11B2 and NR3C1 did not predict trajectories of Negative Affect or subscale scores. Infant negative affect traits were assessed via maternal self-report, and deviated from linearity across follow-up. mRNA expression of glucocorticoid pathway genes in the placenta may be a potentially novel tool for early identification of infants at greater risk for elevated negative affect. Further study is needed to validate the utility of mRNA expression of glucocorticoid pathway genes in the placenta.

Prenatal Exposure to Famine and Risk for Development of Psychopathology in Adulthood: A Meta-Analysis

Prenatal famine, resulting in intrauterine malnutrition, impacts offspring psychopathology later in adulthood. In addition, the specific impact of intrauterine malnutrition of different psychopathology differs by the timing of the exposure. Using a meta-analysis, the current study assessed the specific risk of developing affective, psychotic, and personality disorders. Studies were identified using PubMed and PsycINFO. Studies met the following criteria for inclusion in the analysis: availability in peer-reviewed English journals, use of human subjects, prenatal exposure to famine, and psychopathology in adulthood defined by diagnostic criteria as an outcome. Fixed effect relative risks (RRs) were calculated for affective, psychotic, and personality domains. Furthermore, timing of exposure was assessed as an effect modifier in our analysis, defined by the index trimester at the height of famine. Our meta-analysis found that adults exposed in utero during the 1^st trimester were at a significant increased risk of psychotic disorders (RR=1.46, 95% CI=1.08, 1.97, p=0.014), and personality disorders (RR=2.31, 95% CI=1.36, 3.92, p=0.002). Those exposed during the 2^nd trimester were at a significant increased risk of affective disorders (RR=1.45, 95% CI=1.22, 1.72, p<0.0001), and psychotic disorders (RR=1.46, 95% CI=1.13, 1.89, p=0.004). Similarly, those exposed in the 3^rd trimester were at a significant increased risk of affective disorders (RR=1.33, 95% CI=1.13, 1.57, p=0.0001), and psychotic disorders RR=1.47, 95% CI=1.10, 1.97, p=0.010). Our findings suggest that there is differential risk across the different domains of psychopathology by trimester of exposures. This meta-analysis underscores the need for further investigation into the mechanisms underlying prenatal maternal nutrition and offspring psychopathology where magnitude of elevated risk differs by the exposure timing during pregnancy.

P1901Use of direct thrombin inhibitor on the day of atrial fibrillation ablation decreases incidence of silent cerebral ischemia detected by magnetic resonance imaging

Background

There is increasing evidence to use direct oral anticoagulants (DOACs) in atrial fibrillation (AF) ablation. Uninterrupted use of DOACs is recommended for peri-procedural anticoagulation; the ways of choosing and/or using DOACs depend on physicians' decisions and preferences. Uninterrupted dabigatran (DAB), a direct thrombin inhibitor, reportedly decreased the risk of major bleeding (MB) in AF ablation, compared to uninterrupted warfarin (NEJM 2017; 376:1627). Among DOACs, only regular-dose of DAB (150 mg b.i.d.), showed superiority to warfarin for preventing ischemic thromboembolism (TE) in patients with non-valvular AF, implicating the powerful anti-thrombotic agent. DAB may decrease the potential risk of procedure-related TE.

Purpose

To evaluate whether use of DAB on the day of AF ablation decreases the prevalence of silent cerebral ischemia (SCI) detected by magnetic resonance imaging (MRI).

Methods

414 AF patients on DOACs were enrolled and admitted on the day before AF ablation. Among 354 patients on factor Xa inhibitors (rivaroxaban, apixaban, and edoxaban), the original DOACs were switched to DAB (150 mg b.i.d.) on the day of the procedure in 172 patients (Group D); the treatment remained unchanged in 182 patients (Group non-D). In both groups, DOACs were continuously used throughout the procedure. After propensity-score matching, procedure-related parameters/events and the incidence of MRI-detected SCI were compared between Group D (n=134) and Group non-D (n=134). These parameters in patients originally taking DAB, used without interruption during the procedure (uninterrupted DAB, n=55), were also compared to Group D (n=55) after propensity-score matching.

Results

Baseline activated clotting time (ACT) before initial heparin injection was increased in Group D vs. Group-non-D (179±25* vs. 146±23 sec, *p<0.05 vs. Group non-D). The time to achieve optimal ACT (>300 sec) was shorter in Group D (34±29* vs. 43±32 min). The amounts of heparin needed to achieve optimal ACT and the total amount of heparin used during the procedure were unchanged between Group D and Group non-D. The incidence of SCI decreased in Group D (13.1%* vs. 21.9%), suggesting the potential anti-thrombotic efficacy of DAB. No MB or symptomatic TE events were observed in either group. Baseline ACT, the time to achieve ACT >300 sec, and the incidence of SCI in Group D were comparable to those in uninterrupted DAB (183±38 vs. 181±32 sec, 39±31 vs. 42±28 min, and 14.5% vs. 16.4%, respectively). No MB or symptomatic TE events were observed either in Group D or uninterrupted DAB.

Conclusions

Temporarily switching to DAB from the other DOACs and using it on the day of procedure enable us to achieve optimal ACT quickly and decrease the incidence of SCI, showing similar potential anti-thrombotic efficacy to uninterrupted DAB. Use of DAB on the day of AF ablation also benefits from the availability of its antidote in the case of MB during the procedure.

The children of Superstorm Sandy: Maternal prenatal depression blunts offspring electrodermal activity

We set out to examine the relations between prenatal exposure to the natural disaster Superstorm Sandy, maternal depression, and offspring electrodermal activity (EDA). EDA was measured via skin conductance response (SCR) magnitude in 198 children (M = 42.54 months, SD = 12.76) during a startle paradigm. In keeping with prior research, we expected prenatal depression to be associated with hyporeactive EDA and prenatal stress to be associated with hyperreactive EDA. SCR magnitude was lower in children prenatally exposed to depression alone, when compared to Superstorm Sandy, and controls. SCR magnitude of children prenatally exposed to both maternal depression and the storm was lower than that of all other groups. Our results emphasize the influence of maternal prenatal mental health, support targeted risk assessment for children who experienced an adverse prenatal environment, and highlight the need for a deeper understanding of the interactions between maternal mood and stress on the developing child.

Projection-domain scatter correction for cone beam computed tomography using a residual convolutional neural network

PURPOSE

Scatter is a major factor degrading the image quality of cone beam computed tomography (CBCT). Conventional scatter correction strategies require handcrafted analytical models with ad hoc assumptions, which often leads to less accurate scatter removal. This study aims to develop an effective scatter correction method using a residual convolutional neural network (CNN).

METHODS

A U-net based 25-layer CNN was constructed for CBCT scatter correction. The establishment of the model consists of three steps: model training, validation, and testing. For model training, a total of 1800 pairs of x-ray projection and the corresponding scatter-only distribution in nonanthropomorphic phantoms taken in full-fan scan were generated using Monte Carlo simulation of a CBCT scanner installed with a proton therapy system. An end-to-end CNN training was implemented with two major loss functions for 100 epochs with a mini-batch size of 10. Image rotations and flips were randomly applied to augment the training datasets during training. For validation, 200 projections of a digital head phantom were collected. The proposed CNN-based method was compared to a conventional projection-domain scatter correction method named fast adaptive scatter kernel superposition (fASKS) method using 360 projections of an anthropomorphic head phantom. Two different loss functions were applied for the same CNN to evaluate the impact of loss functions on the final results. Furthermore, the CNN model trained with full-fan projections was fine-tuned for scatter correction in half-fan scan by using transfer learning with additional 360 half-fan projection pairs of nonanthropomorphic phantoms. The tuned-CNN model for half-fan scan was compared with the fASKS method as well as the CNN-based method without the fine-tuning using additional lung phantom projections.

RESULTS

The CNN-based method provides projections with significantly reduced scatter and CBCT images with more accurate Hounsfield Units (HUs) than that of the fASKS-based method. Root mean squared error of the CNN-corrected projections was improved to 0.0862 compared to 0.278 for uncorrected projections or 0.117 for the fASKS-corrected projections. The CNN-corrected reconstruction provided better HU quantification, especially in regions near the air or bone interfaces. All four image quality measures, which include mean absolute error (MAE), mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM), indicated that the CNN-corrected images were significantly better than that of the fASKS-corrected images. Moreover, the proposed transfer learning technique made it possible for the CNN model trained with full-fan projections to be applicable to remove scatters in half-fan projections after fine-tuning with only a small number of additional half-fan training datasets. SSIM value of the tuned-CNN-corrected images was 0.9993 compared to 0.9984 for the non-tuned-CNN-corrected images or 0.9990 for the fASKS-corrected images. Finally, the CNN-based method is computationally efficient - the correction time for the 360 projections only took less than 5 s in the reported experiments on a PC (4.20 GHz Intel Core-i7 CPU) with a single NVIDIA GTX 1070 GPU.

CONCLUSIONS

The proposed deep learning-based method provides an effective tool for CBCT scatter correction and holds significant value for quantitative imaging and image-guided radiation therapy.