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.

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.

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.

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)-1ß-, 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.

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.

A microscopic Kondo lattice model for the heavy fermion antiferromagnet CeIn3.

Electrons at the border of localization generate exotic states of matter across all classes of strongly correlated electron materials and many other quantum materials with emergent functionality. Heavy electron metals are a model example, in which magnetic interactions arise from the opposing limits of localized and itinerant electrons. This remarkable duality is intimately related to the emergence of a plethora of novel quantum matter states such as unconventional superconductivity, electronic-nematic states, hidden order and most recently topological states of matter such as topological Kondo insulators and Kondo semimetals and putative chiral superconductors. The outstanding challenge is that the archetypal Kondo lattice model that captures the underlying electronic dichotomy is notoriously difficult to solve for real materials. Here we show, using the prototypical strongly-correlated antiferromagnet CeIn3, that a multi-orbital periodic Anderson model embedded with input from ab initio bandstructure calculations can be reduced to a simple Kondo-Heisenberg model, which captures the magnetic interactions quantitatively. We validate this tractable Hamiltonian via high-resolution neutron spectroscopy that reproduces accurately the magnetic soft modes in CeIn3, which are believed to mediate unconventional superconductivity. Our study paves the way for a quantitative understanding of metallic quantum states such as unconventional superconductivity.

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 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.

[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.

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.

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 SMARCA4low /SMARCA2high 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 SMARCA4low /SMARCA2high 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.

Prostatic urinary tract visualization with super-resolution deep learning models.

In urethra-sparing radiation therapy, prostatic urinary tract visualization is important in decreasing the urinary side effect. A methodology has been developed to visualize the prostatic urinary tract using post-urination magnetic resonance imaging (PU-MRI) without a urethral catheter. This study investigated whether the combination of PU-MRI and super-resolution (SR) deep learning models improves the visibility of the prostatic urinary tract. We enrolled 30 patients who had previously undergone real-time-image-gated spot scanning proton therapy by insertion of fiducial markers. PU-MRI was performed using a non-contrast high-resolution two-dimensional T2-weighted turbo spin-echo imaging sequence. Four different SR deep learning models were used: the enhanced deep SR network (EDSR), widely activated SR network (WDSR), SR generative adversarial network (SRGAN), and residual dense network (RDN). The complex wavelet structural similarity index measure (CW-SSIM) was used to quantitatively assess the performance of the proposed SR images compared to PU-MRI. Two radiation oncologists used a 1-to-5 scale to subjectively evaluate the visibility of the prostatic urinary tract. Cohen's weighted kappa (k) was used as a measure of agreement of inter-operator reliability. The mean CW-SSIM in EDSR, WDSR, SRGAN, and RDN was 99.86%, 99.89%, 99.30%, and 99.67%, respectively. The mean prostatic urinary tract visibility scores of the radiation oncologists were 3.70 and 3.53 for PU-MRI (k = 0.93), 3.67 and 2.70 for EDSR (k = 0.89), 3.70 and 2.73 for WDSR (k = 0.88), 3.67 and 2.73 for SRGAN (k = 0.88), and 4.37 and 3.73 for RDN (k = 0.93), respectively. The results suggest that SR images using RDN are similar to the original images, and the SR deep learning models subjectively improve the visibility of the prostatic urinary tract.

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.

Japanese Regulatory Considerations for Interoperability of Medical Devices.

With the rapid technological innovations of the Internet of Things (IoT), the situation surrounding medical devices and medical systems has been changing. Interoperable medical devices-medical devices capable of interoperating in a clinically significant way with other medical devices-have been developed, and interoperable medical systems consisting of two or more interconnected interoperable medical devices are being used in clinical settings. However, general points that need to be considered to ensure safe and effective interoperability have yet to be fully established in Japan. A research project (FY2019-FY2021) to discuss issues associated with ensuring safe and effective interoperability was commissioned by the Japan Agency for Medical Research and Development. A pivotal aspect identified in that project is how to manage the sharing of data and information among interoperable medical devices from different manufacturers. Characteristics and timestamps of data and information need to be exchanged between interoperable medical devices. Risks associated with interoperable devices should be managed in a manner appropriate to the characteristics and the intended use of the interoperable medical devices. In this review, we summarize the aspects of data and information that this study group judged were important to consider for ensuring safety and effective interoperability.

Accurate Identification of Klebsiella variicola by MALDI-TOF Mass Spectrometry in Clinical Microbiology Laboratories.

Klebsiella variicola is a pathogen that is increasingly recognized as being associated with human infections, but the methods available to clinical microbiology laboratories for accurate identification are limited. In this study, we assessed the accuracy of identification of K. variicola by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry using genetic identification with multiplex PCR as the reference method. Antimicrobial susceptibilities and virulence of K. variicola strains were also investigated. Fifty-five Klebsiella pneumoniae, 26 K. variicola, and 2 Klebsiella quasipneumoniae clinical strains were used for evaluation. Both MALDI Biotyper with library version 9 and Klebsiella MALDI TypeR, a web-based species identification tool using MALDI-TOF data, accurately identified all K. variicola strains. In addition, two strains of K. quasipneumoniae were accurately identified with Klebsiella MALDI TypeR. Whole-genome sequencing confirmed the accurate identification to the subspecies level by Klebsiella MALDI TypeR for four strains (two strains each of K. variicola subsp. variicola and K. quasipneumoniae subsp. similipneumoniae). While 13 strains, 3 strains, and 1 strain of K. pneumoniae showed nonsusceptibility to ampicillin-sulbactam, ceftriaxone, and meropenem, respectively, all strains of K. variicola were susceptible to all tested antimicrobial agents. Although two K. variicola strains were positive for the string test, no K. variicola strains harbored any of the genes associated with hypervirulence of K. pneumoniae. Accurate identification of the K. pneumoniae complex, including K. variicola, by MALDI-TOF in clinical microbiology laboratories is expected to clarify the clinical characteristics of each species in the future. IMPORTANCE Recent widespread use of bacterial whole-genome sequencing analysis has resulted in the proposal of novel bacterial species and reclassification of taxonomy. Accurate methods for identification of bacterial species in clinical microbiology laboratories are essential to accumulate information on the clinical characteristics of each bacterial species. Klebsiella variicola is a member of the Klebsiella pneumoniae complex, and its association with human infections has been increasingly recognized, but accurate identification methods approved for use in clinical microbiology laboratories have been limited thus far. The findings of the present study suggest that K. variicola can be accurately identified by matrix-assisted laser desorption ionization-time of flight mass spectrometry using updated library or web-based identification tools. Accurate identification will promote exploration of clinical characteristics of K. variicola.

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}.