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Cyclic adenosine monophosphate (cAMP) controls differentiation in several types of cells during brain development. However, the molecular mechanism of cAMP-controlled differentiation is not fully understood. We investigated the role of protein kinase A (PKA) and exchange protein directly activated by cAMP (Epac) on cAMP-induced glial fibrillary acidic protein (GFAP), an astrocyte marker, in cultured glial cells. B92 glial cells were treated with cAMP-elevating drugs, an activator of adenylate cyclase, phosphodiesterase inhibitor and a ß adrenal receptor agonist. These cAMP-elevating agents induced dramatic morphological changes and expression of GFAP. A cAMP analog, 8-Br-cAMP, which activates Epac as well as PKA, induced GFAP expression and morphological changes, while another cAMP analog, 8-CPT-cAMP, which activates Epac with greater efficacy when compared to PKA, induced GFAP expression but very weak morphological changes. Most importantly, the treatment with a PKA inhibitor partially reduced cAMP-induced GFAP expression. Taken together, these results indicate that cAMP-elevating drugs lead to the induction of GFAP via PKA and/or Epac activation in B92 glial cells.

Abstract Manufacturing regenerative medicine requires continuous monitoring of pluripotent cell culture and quality assessment while eliminating cell destruction and contaminants. In this study, we employed a novel method to monitor the pluripotency of stem cells through image analysis, avoiding the traditionally used invasive procedures. This approach employs machine learning algorithms to analyze stem cell images to predict the expression of pluripotency markers, such as OCT4 and NANOG, without physically interacting with or harming cells. We cultured induced pluripotent stem cells under various conditions to induce different pluripotent states and imaged the cells using bright-field microscopy. Pluripotency states of induced pluripotent stem cells were assessed using invasive methods, including qPCR, immunostaining, flow cytometry, and RNA sequencing. Unsupervised and semi-supervised learning models were applied to evaluate the results and accurately predict the pluripotency of the cells using only image analysis. Our approach directly links images to invasive assessment results, making the analysis of cell labeling and annotation of cells in images by experts dispensable. This core achievement not only contributes for safer and more reliable stem cell research but also opens new avenues for real-time monitoring and quality control in regenerative medicine manufacturing. Our research fills an important gap in the field by providing a viable, noninvasive alternative to traditional invasive methods for assessing pluripotency. This innovation is expected to make a significant contribution to improving regenerative medicine manufacturing because it will enable a more detailed and feasible understanding of cellular status during the manufacturing process.

Abstract The RNA-guided DNA endonuclease Cas9 cleaves double-stranded DNA targets complementary to an RNA guide, and is widely used as a powerful genome-editing tool. Here, we report the crystal structure of Brevibacillus laterosporus Cas9 (BlCas9, also known as BlatCas9), in complex with a guide RNA and its target DNA at 2.4-Å resolution. The structure reveals that the BlCas9 guide RNA adopts an unexpected architecture containing a triple-helix, which is specifically recognized by BlCas9, and that BlCas9 recognizes a unique N4CNDN protospacer adjacent motif through base-specific interactions on both the target and non-target DNA strands. Based on the structure, we rationally engineered a BlCas9 variant that exhibits enhanced genome- and base-editing activities with an expanded target scope in human cells. This approach may further improve the performance of the enhanced BlCas9 variant to generate useful genome-editing tools that require only a single C PAM nucleotide and can be packaged into a single AAV vector for in vivo gene therapy.

Hemophagocytic lymphohistiocytosis (HLH) has been recognized as a rare adverse event following the coronavirus disease 2019 (COVID-19) vaccination. We report a case of neuropsychiatric symptoms and refractory HLH in a woman with systemic lupus erythematosus (SLE) after receiving her COVID-19 vaccine treated with belimumab, later found to have intravascular large B-cell lymphoma (IVLBCL) at autopsy. A 61-year-old woman with SLE was referred to our hospital because of impaired consciousness and fever. One month prior to consulting, she received her second COVID-19 vaccine dose. Afterward, her consciousness level decreased, and she developed a high fever. She tested negative for SARS-CoV-2. Neuropsychiatric SLE was suspected; therefore, glucocorticoid pulse therapy was initiated on day 1 and 8. She had thrombocytopenia, increased serum ferritin levels and hemophagocytosis. The patient was diagnosed with HLH and treated with etoposide, dexamethasone and cyclosporine. Despite treatment, the patient died on day 75; autopsy report findings suggested IVLBCL as the underlying cause of HLH. Differentiating comorbid conditions remains difficult; however, in the case of an atypical clinical presentation, other causes should be considered. Therefore, we speculate that the COVID-19 vaccination and her autoimmune condition may have expedited IVLBCL development.

Kentaro Iwata1, Tomoko Toma2, Akihiro Yachie21Department of Infectious Diseases, Kobe University Hospital, Kobe, Japan; 2Department of Pediatrics, Graduate School of Medical Science and School of Medicine, Kanazawa University, Kanazawa, JapanAbstract: A 38-year-old woman presented with 2 days history of left-flank pain. She had similar episodes of abdominal pain as well as chest pain several times, but symptoms disappeared spontaneously. Each time she developed pain, there was no fever. After ruling out common causes of recurrent abdominal pain, familial Mediterranean fever (FMF) was considered as a potential diagnosis. Genetic tests revealed multiple heterozygote mutations, which may be associated with FMF. Patients with Mediterranean fever mutations may present with atypical presentations without fever, like in this case. Astute clinical suspicion is required to make an accurate diagnosis.Keywords: familial Mediterranean fever, MEFV mutation, afebrile

Protocol standardization and sharing are crucial for reproducibility in life sciences. In spite of numerous efforts for standardized protocol description, adherence to these standards in literature remains largely inconsistent. Curation of protocols are especially challenging due to the labor intensive process, requiring expert domain knowledge of each experimental procedure. Recent advancements in Large Language Models (LLMs) offer a promising solution to interpret and curate knowledge from complex scientific literature. In this work, we develop ProtoCode, a tool leveraging fine-tune LLMs to curate protocols into intermediate representation formats which can be interpretable by both human and machine interfaces. Our proof-of-concept, focused on polymerase chain reaction (PCR) protocols, retrieves information from PCR protocols at an accuracy ranging 69–100 % depending on the information content. In all tested protocols, we demonstrate that ProtoCode successfully converts literature-based protocols into correct operational files for multiple thermal cycler systems. In conclusion, ProtoCode can alleviate labor intensive curation and standardization of life science protocols to enhance research reproducibility by providing a reliable, automated means to process and standardize protocols. ProtoCode is freely available as a web server at https://curation.taxila.io/ProtoCode/.

Phylogeny estimation (the reconstruction of evolutionary trees) has recently been applied to CRISPR-based cell lineage tracing, allowing the developmental history of an individual tissue or organism to be inferred from a large number of mutated sequences in somatic cells. However, current computational methods are not able to construct phylogenetic trees from extremely large numbers of input sequences. Here, we present a deep distributed computing framework to comprehensively trace accurate large lineages (FRACTAL) that substantially enhances the scalability of current lineage estimation software tools. FRACTAL first reconstructs only an upstream lineage of the input sequences and recursively iterates the same produce for its downstream lineages using independent computing nodes. We demonstrate the utility of FRACTAL by reconstructing lineages from >235 million simulated sequences and from >16 million cells from a simulated experiment with a CRISPR system that accumulates mutations during cell proliferation. We also successfully applied FRACTAL to evolutionary tree reconstructions and to an experiment using error-prone PCR (EP-PCR) for large-scale sequence diversification.

Abstract NMN is the direct precursor of nicotinamide adenine dinucleotide (NAD+) and is considered as a key factor for increasing NAD+ levels and mitochondrial activity in cells. In this study, based on transcriptome analysis, we showed that NMN alleviates the poly(I:C)-induced inflammatory response in cultures of two types of human primary cells, human pulmonary microvascular endothelial cells (HPMECs) and human coronary artery endothelial cells (HCAECs). Major inflammatory mediators, including IL6 and PARP family members, were grouped into coexpressed gene modules and significantly downregulated under NMN exposure in poly(I:C)-activated conditions in both cell types. The Bayesian network analysis of module hub genes predicted common genes, including eukaryotic translation initiation factor 4B (EIF4B), and distinct genes, such as platelet-derived growth factor binding molecules, in HCAECs, which potentially regulate the identified inflammation modules. These results suggest a robust regulatory mechanism by which NMN alleviates inflammatory pathway activation, which may open up the possibility of a new role for NMN replenishment in the treatment of chronic or acute inflammation.

Abstract Introduction A wide variety of skin manifestations are associated with Mycoplasma pneumoniae infection. However, the precise mechanisms by which M. pneumoniae infection is able to produce a variety of cutaneous manifestations are poorly understood. Case presentation An 8-year-old Japanese girl presented with sequential skin manifestations, including erythema nodosum, erythema multiforme and Henoch-Schönlein purpura. Although a chest radiograph showed no significant lung abnormalities, serological examinations revealed that these skin manifestations were associated with M. pneumoniae infection. Conclusion It has been reported that the variations in cutaneous manifestations of M. pneumoniae infection can be attributed to the immaturity of the adaptive immunity of a host. However, the case presented herein indicates that skin manifestations might not be specific for each individual. An awareness of the varied patterns of cutaneous disease is essential for the early diagnosis and treatment of patients with manifestations of M. pneumoniae infection.

Abstract Glycine receptors (GlyRs) are ligand-gated chloride channels comprising alpha (α1–4) and β subunits. The GlyR subunits play major roles in the mammalian central nervous system, ranging from regulating simple sensory information to modulating higher-order brain function. Unlike the other GlyR subunits, GlyR α4 receives relatively little attention because the human ortholog lacks a transmembrane domain and is thus considered a pseudogene. A recent genetic study reported that the GLRA4 pseudogene locus on the X chromosome is potentially involved in cognitive impairment, motor delay and craniofacial anomalies in humans. The physiologic roles of GlyR α4 in mammal behavior and its involvement in disease, however, are not known. Here we examined the temporal and spatial expression profile of GlyR α4 in the mouse brain and subjected Glra4 mutant mice to a comprehensive behavioral analysis to elucidate the role of GlyR α4 in behavior. The GlyR α4 subunit was mainly enriched in the hindbrain and midbrain, and had relatively lower expression in the thalamus, cerebellum, hypothalamus, and olfactory bulb. In addition, expression of the GlyR α4 subunit gradually increased during brain development. Glra4 mutant mice exhibited a decreased amplitude and delayed onset of the startle response compared with wild-type littermates, and increased social interaction in the home cage during the dark period. Glra4 mutants also had a low percentage of entries into open arms in the elevated plus-maze test. Although mice with GlyR α4 deficiency did not show motor and learning abnormalities reported to be associated in human genomics studies, they exhibited behavioral changes in startle response and social and anxiety-like behavior. Our data clarify the spatiotemporal expression pattern of the GlyR α4 subunit and suggest that glycinergic signaling modulates social, startle, and anxiety-like behaviors in mice.

Abstract Among the different etiologies for fever of unknown origin in children, infectious diseases are the most frequent final diagnosis, followed by autoimmune diseases and malignancies. Autoinflammatory diseases are relatively rare among children and are frequently overlooked as differential diagnoses for fever of unknown origin. Once the possibility of a particular autoimmune disease is considered by physicians, the diagnosis might be easily made by a genetic approach because many of autoinflammatory diseases are of monogenic origin. To reach the diagnosis, detailed history-taking, precise physical examinations, and cytokine profiling as well as extensive mutation analysis of candidate genes should be undertaken for febrile children. Such the approach will protect the patients, and their family to undergo “diagnostic odyssey” in which unnecessary and sometimes risky diagnostic and therapeutic interventions are taken. This short review discusses the clinical and laboratory features of familial Mediterranean fever and systemic juvenile idiopathic arthritis, as representative illnesses of monogenic and polygenic autoinflammatory diseases, respectively. Cytokine profiling and mutation analyses both help to understand and decipher the heterogeneous pathologies in both disease categories.

DNA constructs and their annotated sequence maps have been rapidly accumulating with the advancement of DNA cloning, synthesis, and assembly methods. Here the authors introduce QUEEN, a framework to describe and share DNA materials and construction protocols.

Hemophagocytic lymphohistiocytosis (HLH) has been recognized as a rare adverse event following the coronavirus disease 2019 (COVID-19) vaccination. We report a case of neuropsychiatric symptoms and refractory HLH in a woman with systemic lupus erythematosus (SLE) after receiving her COVID-19 vaccine treated with belimumab, later found to have intravascular large B-cell lymphoma (IVLBCL) at autopsy. A 61-year-old woman with SLE was referred to our hospital because of impaired consciousness and fever. One month prior to consulting, she received her second COVID-19 vaccine dose. Afterward, her consciousness level decreased, and she developed a high fever. She tested negative for SARS-CoV-2. Neuropsychiatric SLE was suspected; therefore, glucocorticoid pulse therapy was initiated on day 1 and 8. She had thrombocytopenia, increased serum ferritin levels and hemophagocytosis. The patient was diagnosed with HLH and treated with etoposide, dexamethasone and cyclosporine. Despite treatment, the patient died on day 75; autopsy report findings suggested IVLBCL as the underlying cause of HLH. Differentiating comorbid conditions remains difficult; however, in the case of an atypical clinical presentation, other causes should be considered. Therefore, we speculate that the COVID-19 vaccination and her autoimmune condition may have expedited IVLBCL development. [ABSTRACT FROM AUTHOR]

Abstract Objective To identify potential biomarkers to distinguish familial Mediterranean fever (FMF) from sepsis. Method We recruited 28 patients diagnosed with typical FMF (according to the Tel Hashomer criteria), 22 patients with sepsis, and 118 age-matched controls. Serum levels of 40 cytokines were analyzed using multi-suspension cytokine array. We performed a cluster analysis of each cytokine in the FMF and sepsis groups in order to identify specific molecular networks. Multivariate classification (random forest analysis) and logistic regression analysis were used to rank the cytokines by importance and determine specific biomarkers for distinguishing FMF from sepsis. Results Fifteen of the 40 cytokines were found to be suitable for further analysis. Levels of serum granulocyte-macrophage colony-stimulating factor (GM-CSF), fibroblast growth factor 2, vascular endothelial growth factor, macrophage inflammatory protein-1b, and interleukin-17 were significantly elevated, whereas tumor necrosis factor-α (TNF-α) was significantly lower in patients with FMF compared with those with sepsis. Cytokine clustering patterns differed between the two groups. Multivariate classification followed by logistic regression analysis revealed that measurement of both GM-CSF and TNF-α could distinguish FMF from sepsis with high accuracy (cut-off values for GM-CSF = 8.3 pg/mL; TNF-α = 16.3 pg/mL; sensitivity, 92.9%; specificity, 94.4%; accuracy, 93.4%). Conclusion Determination of GM-CSF and TNF-α levels in combination may represent a biomarker for the differential diagnosis of FMF from sepsis, based on measurement of multiple cytokines.

Interleukin (IL)-18 is a pleiotropic, pro-inflammatory cytokine involved in the regulation of innate and adaptive immune responses. IL-18 has attracted increasing attention as a key mediator in autoinflammatory diseases associated with the development of macrophage activation syndrome (MAS) including systemic juvenile idiopathic arthritis and adult-onset Still’s disease. In these diseases, dysregulation of inflammasome activity and overproduction of IL-18 might be associated with the development of MAS by inducing natural killer cell dysfunction. Serum IL-18 levels are high in patients with these diseases and therefore are useful for the diagnosis and monitoring of disease activity. In contrast, a recent study revealed the overproduction of IL-18 was present in cases of autoinflammation without susceptibility to MAS such as pyogenic sterile arthritis, pyoderma gangrenosum, and acne (PAPA) syndrome. The pathogenic and causative roles of IL-18 remain unclear in these autoinflammatory diseases. Further investigations are necessary to clarify the role of IL-18 and its importance as a therapeutic target in the pathogenesis of autoinflammatory diseases.

BackgroundIt is expected that personal health information collected through mobile information terminals will be used to develop health strategies that benefit the public. Against this background, several countries have actively attempted to use mobile phones to control infectious diseases. These collected data, such as activity logs and contact history, are countermeasures against diseases such as COVID-19. In Japan, the Ministry of Health, Labor, and Welfare has developed and disseminated a contact-confirming app (COVID-19 Contact-Confirming Application [COCOA]) to the public, which detects and notifies individuals whether they have been near someone who had subsequently tested positive for COVID-19. However, there are concerns about leakage and misuse of the personal information collected by such information terminals. ObjectiveThis study aimed to investigate the possible trade-off between effectiveness in preventing infectious diseases and infringement of personal privacy in COCOA. In addition, we analyzed whether resistance to COCOA would reduce if the app contributed to public health or if a discount was provided on mobile phone charges. MethodsA cross-sectional, quantitative survey of Japanese citizens was conducted using Survey Monkey, a general-purpose web-based survey platform. When developing the questions for the questionnaire, we included the installation status of COCOA and recorded the anxiety stemming from the potential leakage or misuse of personal information collected for COVID-19 infection control. The respondents were asked to rate various factors to determine their perceptions on a 5-point scale. ResultsIn total, 1058 participants were included in the final analysis. In response to the question of whether the spread of the disease was being controlled by the infection control measures taken by the government, 25.71% (272/1058) of the respondents answered that they strongly agreed or agreed. One-quarter of the respondents indicated that they had already installed COCOA. This study found that the sense of resistance to government intervention was not alleviated by the benefits provided to individuals when using the app. The only factors that were positively associated with the response absolutely opposed to use of the app, even with a discount on mobile phone use charges, were those regarding leaks and misuse of personal information, which was true for all functions (function A: odds ratio [OR] 1.8, 95% CI 1.3-2.4; function B: OR 1.9, 95% CI 1.5-2.6; function C: OR 1.8, 95% CI 1.4-2.4). ConclusionsPublic organizations need to emphasize the general benefits of allowing them to manage personal information and assure users that this information is being managed safely rather than offering incentives to individuals to provide such personal information. When collecting and using citizens’ health information, it is essential that governments and other entities focus on contributing to the public good and ensuring safety rather than returning benefits to individual citizens.

Abstract Background Identifying novel therapeutic targets is crucial for the successful development of drugs. However, the cost to experimentally identify therapeutic targets is huge and only approximately 400 genes are targets for FDA-approved drugs. As a result, it is inevitable to develop powerful computational tools that can identify potential novel therapeutic targets. Fortunately, the human protein-protein interaction network (PIN) could be a useful resource to achieve this objective. Methods In this study, we developed a deep learning-based computational framework that extracts low-dimensional representations of high-dimensional PIN data. Our computational framework uses latent features and state-of-the-art machine learning techniques to infer potential drug target genes. Results We applied our computational framework to prioritize novel putative target genes for Alzheimer’s disease and successfully identified key genes that may serve as novel therapeutic targets (e.g., DLG4, EGFR, RAC1, SYK, PTK2B, SOCS1). Furthermore, based on these putative targets, we could infer repositionable candidate-compounds for the disease (e.g., tamoxifen, bosutinib, and dasatinib). Conclusions Our deep learning-based computational framework could be a powerful tool to efficiently prioritize new therapeutic targets and enhance the drug repositioning strategy.

Abstract Background Exotoxins secreted from Staphylococcus aureus or Streptococcus pyogenes act as superantigens that induce systemic release of inflammatory cytokines and are a common cause of toxic shock syndrome (TSS). However, little is known about TSS caused by coagulase-negative staphylococci (CoNS) and the underlying mechanisms. Here, we present a rare case of TSS caused by Staphylococcus simulans (S. simulans). Case presentation We report the case of a 75-year-old woman who developed pneumococcal pneumonia and bacteremia from S. simulans following an influenza infection. The patient met the clinical criteria for probable TSS, and her symptoms included fever of 39.5 °C, diffuse macular erythroderma, conjunctival congestion, vomiting, diarrhea, liver dysfunction, and disorientation. Therefore, the following treatment was initiated for bacterial pneumonia complicating influenza A with suspected TSS: meropenem (1 g every 8 h), vancomycin (1 g every 12 h), and clindamycin (600 mg every 8 h). Blood cultures taken on the day after admission were positive for CoNS, whereas sputum and pharyngeal cultures grew Streptococcus pneumoniae (Geckler group 4) and methicillin-sensitive S. aureus, respectively. However, exotoxins thought to cause TSS, such as TSS toxin-1 and various enterotoxins, were not detected. The patient’s therapy was switched to cefazolin (2 g every 8 h) and clindamycin (600 mg every 8 h) for 14 days based on microbiologic test results. She developed desquamation of the fingers on hospital day 8 and was diagnosed with TSS. Conventional exotoxins, such as TSST-1, and S. aureus enterotoxins were not detected in culture samples. The serum levels of inflammatory cytokines, such as neopterin and IL-6, were high. CD8+ T cells were activated in peripheral blood. Vβ2+ population activation, which is characteristic for TSST-1, was not observed in the Vβ usage of CD8+ T cells in T cell receptor Vβ repertoire distribution analysis. Conclusions We present a case of S. simulans-induced TSS. Taken together, we speculate that no specific exotoxins are involved in the induction of TSS in this patient. A likely mechanism is uncontrolled cytokine release (i.e., cytokine storm) induced by non-specific immune reactions against CoNS proliferation.

Pathological examination of formalin-fixed paraffin-embedded (FFPE) needle-biopsied samples by certified pathologists represents the gold standard for differential diagnosis between ductal carcinoma in situ (DCIS) and invasive breast cancers (IBC), while information of marker metabolites in the samples is lost in the samples. Infrared laser-scanning large-area surface-enhanced Raman spectroscopy (SERS) equipped with gold-nanoparticle-based SERS substrate enables us to visualize metabolites in fresh-frozen needle-biopsied samples with spatial matching between SERS and HE staining images with pathological annotations. DCIS (n = 14) and IBC (n = 32) samples generated many different SERS peaks in finger-print regions of SERS spectra among pathologically annotated lesions including cancer cell nests and the surrounding stroma. The results showed that SERS peaks in IBC stroma exhibit significantly increased polysulfide that coincides with decreased hypotaurine as compared with DCIS, suggesting that alterations of these redox metabolites account for fingerprints of desmoplastic reactions to distinguish IBC from DCIS. Furthermore, the application of supervised machine learning to the stroma-specific multiple SERS signals enables us to support automated differential diagnosis with high accuracy. The results suggest that SERS-derived biochemical fingerprints derived from redox metabolites account for a hallmark of desmoplastic reaction of IBC that is absent in DCIS, and thus, they serve as a useful method for precision diagnosis in breast cancer.