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BackgroundDuring the COVID-19 pandemic, decreased volumes of stroke admissions and mechanical thrombectomy were reported. The study's objective was to examine whether subarachnoid haemorrhage (SAH) hospitalisations and ruptured aneurysm coiling interventions demonstrated similar declines.MethodsWe conducted a cross-sectional, retrospective, observational study across 6 continents, 37 countries and 140 comprehensive stroke centres. Patients with the diagnosis of SAH, aneurysmal SAH, ruptured aneurysm coiling interventions and COVID-19 were identified by prospective aneurysm databases or by International Classification of Diseases, 10th Revision, codes. The 3-month cumulative volume, monthly volumes for SAH hospitalisations and ruptured aneurysm coiling procedures were compared for the period before (1 year and immediately before) and during the pandemic, defined as 1 March-31 May 2020. The prior 1-year control period (1 March-31 May 2019) was obtained to account for seasonal variation.FindingsThere was a significant decline in SAH hospitalisations, with 2044 admissions in the 3 months immediately before and 1585 admissions during the pandemic, representing a relative decline of 22.5% (95% CI -24.3% to -20.7%, p

Saccharomyces cerevisiae sake yeast strain Kyokai no. 7 (K7) and its relatives carry a homozygous loss-of-function mutation in the RIM15 gene, which encodes a Greatwall family protein kinase. Disruption of RIM15 in nonsake yeast strains leads to improved alcoholic fermentation, indicating that the defect in Rim15p is associated with the enhanced fermentation performance of sake yeast cells. In order to understand how Rim15p mediates fermentation control, we here focused on target-of-rapamycin protein kinase complex 1 (TORC1) and protein phosphatase 2A with the B55δ regulatory subunit (PP2AB55δ), complexes that are known to act upstream and downstream of Rim15p, respectively. Several lines of evidence, including our previous transcriptomic analysis data, suggested enhanced TORC1 signaling in sake yeast cells during sake fermentation. Fermentation tests of the TORC1-related mutants using a laboratory strain revealed that TORC1 signaling positively regulates the initial fermentation rate in a Rim15p-dependent manner. Deletion of the CDC55 gene, encoding B55δ, abolished the high fermentation performance of Rim15p-deficient laboratory yeast and sake yeast cells, indicating that PP2AB55δ mediates the fermentation control by TORC1 and Rim15p. The TORC1-Greatwall-PP2AB55δ pathway similarly affected the fermentation rate in the fission yeast Schizosaccharomyces pombe, strongly suggesting that the evolutionarily conserved pathway governs alcoholic fermentation in yeasts. It is likely that elevated PP2AB55δ activity accounts for the high fermentation performance of sake yeast cells. Heterozygous loss-of-function mutations in CDC55 found in K7-related sake strains may indicate that the Rim15p-deficient phenotypes are disadvantageous to cell survival.IMPORTANCE The biochemical processes and enzymes responsible for glycolysis and alcoholic fermentation by the yeast S. cerevisiae have long been the subject of scientific research. Nevertheless, the factors determining fermentation performance in vivo are not fully understood. As a result, the industrial breeding of yeast strains has required empirical characterization of fermentation by screening numerous mutants through laborious fermentation tests. To establish a rational and efficient breeding strategy, key regulators of alcoholic fermentation need to be identified. In the present study, we focused on how sake yeast strains of S. cerevisiae have acquired high alcoholic fermentation performance. Our findings provide a rational molecular basis to design yeast strains with optimal fermentation performance for production of alcoholic beverages and bioethanol. In addition, as the evolutionarily conserved TORC1-Greatwall-PP2AB55δ pathway plays a major role in the glycolytic control, our work may contribute to research on carbohydrate metabolism in higher eukaryotes.

Objectives: The objectives were to investigate the clinical characteristics and course of long COVID, defined as the persistence of symptoms at least one month after the onset of COVID-19, in outpatients and to clarify differences in symptoms between SARS CoV-2 mutant strains. Methods: Our observational study in a primary care institution in Japan included 1053 patients with long COVID who visited our outpatient clinic between April 2021 and March 2023. Symptom distribution, performance status, and patient background at the time of the first outpatient visit were compared between infectious strains (Delta and before group and Omicron group). Background factors and symptoms related to time to remission were also analyzed. Results: The severity of COVID-19 in the acute phase was mild, moderate, and severe in 82.2%, 14.9%, and 2.9% in the Delta and before group; and in 97.6%, 1.7%, and 0.4% in the Omicron group, respectively. Vaccination coverage was significantly different between the Delta and before (37.1%) and Omicron groups (73.1%) (p < 0.001), probably due to the period of vaccine unavailability in the former group. Symptoms of fatigue and headache occurred most frequently, irrespective of infectious strain. The mean number of symptoms per patient was significantly higher in the Delta and before group than the Omicron group (3.4 vs. 2.7, p < 0.0001). The median time overall to remission of long COVID was 169 days. Cox hazard model analysis identified female sex, high body mass index, and dyspnea (but not infectious strain) as significant factors prolonging the time to remission (p < 0.05). Conclusions: Differences in the number of symptoms between infectious strains may be related to differences in viral virulence and/or vaccination coverage. However, the clinical course was found to be minimally influenced by the infectious strain. The present results should improve the understanding of prognosis in patients with long COVID from both the clinical and social perspectives. [ABSTRACT FROM AUTHOR]

A 67‐year‐old man had taken the janus kinase (JAK) inhibitor, tofacitinib, for ulcerative colitis. He was referred to our department for a refractory ulcer on his lower leg. We suspected vasculitis and performed skin biopsy. Histopathological examination showed multinucleated giant cells in the epidermis and fibrinoid degeneration of small vessels in the upper dermis. Varicella zoster virus (VZV) DNA was detected by polymerase chain reaction and we diagnosed the patient with atypical vasculitis‐like herpes zoster. The patient was treated with oral valacyclovir, but the rash persisted and took 2 months to heal. Immunostaining using anti‐VZV antibody was positive mainly in epidermal keratinocytes, but was also observed to be positive in cells in the dermis. We further performed RNA in situ hybridization using a VZV ORF9 mRNA probe and clearly showed that the distribution of VZV mRNA extended into the dermis, including the dermal vessel walls and the eccrine sweat glands as well as the epidermis. The internal administration of JAK inhibitors may induce regional widespread VZV infection including vessels and involved in the formation of prolonged vasculitis‐like manifestation. RNA in situ hybridization can be a potent tool for detecting the spread of VZV infection in the skin. [ABSTRACT FROM AUTHOR]

There is considerable interest in expanding B cell-targeted therapies in human autoimmune diseases. However, clinical trials in human primary biliary cholangitis (PBC) using a chimeric antibody against human CD20 (hCD20) have showed limited efficacy. Two potential explanations for these disappointing results are the appearance of anti-drug antibodies (ADAs) and the high frequency of patients with moderate PBC or patients who had failed ursodeoxycholic acid treatment. Here, we studied a novel humanized IgG1 antibody against hCD20 and explored its efficacy in early stage PBC using a well-defined murine model. We developed a unique murine model consisting of dnTGF-βRII mice expressing hCD20 and human Fcγ receptors (hFcγRs). Beginning at 4-6 weeks of age, equivalent to stage I/II human PBC, female mice were given weekly injections of an anti-hCD20 antibody (TKM-011) or vehicle control, and monitored for liver histology as well as a broad panel of immunological readouts. After 16 weeks' treatment, we observed a significant reduction in portal inflammation, a decrease in liver-infiltrating mononuclear cells as well as a reduction in liver CD8+ T cells. Importantly, direct correlations between numbers of liver non-B cells and B cells (r = 0.7426, p = 0.0006) and between numbers of liver memory CD8+ T cells and B cells (r = 0.6423, p = 0.0054) were apparent. Accompanying these changes was a dramatic reduction in anti-mitochondrial antibodies (AMAs), interleukin (IL)-12p40 and IL-5, and elevated levels of the anti-inflammatory chemokine CXCL1/KC. In mice that developed ADAs, clinical improvements were less pronounced. Sustained treatment with B cell-targeted therapies may broadly inhibit effector pathways in PBC, but may need to be administered early in the natural history of PBC.

Background: This paper examines scientific papers in the field of digital twins to explore the different areas of application in supply chains. Methods: Using a machine learning-based topic modeling approach, this study aims to provide insights into the key areas of supply chain management that benefit from digital twin capabilities. Results: The research findings highlight key priorities in the areas of infrastructure, construction, business, technology, manufacturing, blockchain, and agriculture, providing a comprehensive perspective. Conclusions: Our research findings confirm several recommendations. First, the machine learning-based model identifies new areas that are not addressed in the human review results. Second, while the human review results put more emphasis on practicality, such as management activities, processes, and methods, the machine learning results pay more attention to macro perspectives, such as infrastructure, technology, and business. Third, the machine learning-based model is able to extract more granular information; for example, it identifies core technologies beyond digital twins, including AI/reinforcement learning, picking robots, cybersecurity, 5G networks, the physical internet, additive manufacturing, and cloud manufacturing. [ABSTRACT FROM AUTHOR]