AXL+SIGLEC6+ dendritic cells in cerebrospinal fluid and brain tissues of patients with autoimmune inflammatory demyelinating disease of CNS.

Inflammatory demyelinating disease of the CNS (IDD) is a heterogeneous group of autoimmune diseases, and multiple sclerosis is the most common type. Dendritic cells (DCs), major antigen-presenting cells, have been proposed to play a central role in the pathogenesis of IDD. The AXL+SIGLEC6+ DC (ASDC) has been only recently identified in humans and has a high capability of T cell activation. Nevertheless, its contribution to CNS autoimmunity remains still obscure. Here, we aimed to identify the ASDC in diverse sample types from IDD patients and experimental autoimmune encephalomyelitis (EAE). A detailed analysis of DC subpopulations using single-cell transcriptomics for the paired cerebrospinal fluid (CSF) and blood samples of IDD patients (total n = 9) revealed that three subtypes of DCs (ASDCs, ACY3+ DCs, and LAMP3+ DCs) were overrepresented in CSF compared with their paired blood. Among these DCs, ASDCs were also more abundant in CSF of IDD patients than in controls, manifesting poly-adhesional and stimulatory characteristics. In the brain biopsied tissues of IDD patients, obtained at the acute attack of disease, ASDC were also frequently found in close contact with T cells. Lastly, the frequency of ASDC was found to be temporally more abundant in acute attack of disease both in CSF samples of IDD patients and in tissues of EAE, an animal model for CNS autoimmunity. Our analysis suggests that the ASDC might be involved in the pathogenesis of CNS autoimmunity.

Single-cell RNA sequencing reveals rebalancing of immunological response in patients with periodontitis after non-surgical periodontal therapy.

BACKGROUND: Periodontitis is a major inflammatory disease of the oral mucosa that is not limited to the oral cavity but also has systemic consequences. Although the importance of chronic periodontitis has been emphasized, the systemic immune response induced by periodontitis and its therapeutic effects remain elusive. Here, we report the transcriptomes of peripheral blood mononuclear cells (PBMCs) from patients with periodontitis. METHODS: Using single-cell RNA sequencing, we profiled PBMCs from healthy controls and paired pre- and post-treatment patients with periodontitis. We extracted differentially expressed genes and biological pathways for each cell type and calculated activity scores reflecting cellular characteristics. Intercellular crosstalk was classified into therapy-responsive and -nonresponsive pathways. RESULTS: We analyzed pan-cellular differentially expressed genes caused by periodontitis and found that most cell types showed a significant increase in CRIP1, which was further supported by the increased levels of plasma CRIP1 observed in patients with periodontitis. In addition, activated cell type-specific ligand-receptor interactions, including the BTLA, IFN-γ, and RESISTIN pathways, were prominent in patients with periodontitis. Both the BTLA and IFN-γ pathways returned to similar levels in healthy controls after periodontal therapy, whereas the RESISTIN pathway was still activated even after therapy. CONCLUSION: These data collectively provide insights into the transcriptome changes and molecular interactions that are responsive to periodontal treatment. We identified periodontitis-specific systemic inflammatory indicators and suggest unresolved signals of non-surgical therapy as future therapeutic targets.

Proton Pump Inhibitor Use and the Efficacy of Chemotherapy in Metastatic Colorectal Cancer: A Post Hoc Analysis of a Randomized Phase III Trial (AXEPT).

BACKGROUND: Concomitant use of proton pump inhibitors (PPIs) with capecitabine was suggested to be associated with poor outcomes in gastrointestinal cancers. We analyzed the differential impact of PPI use on capecitabine and fluorouracil using the data set from the AXEPT trial, a phase III randomized trial that demonstrated the noninferiority of mXELIRI (modified XELIRI: capecitabine plus irinotecan) to FOLFIRI (leucovorin, fluorouracil, and irinotecan), either with or without bevacizumab in patients with metastatic colorectal cancer. PATIENTS AND METHODS: Out of the per-protocol set (n = 620), patients with information on concomitant medications (n = 482) were included in this post hoc analysis. PPI use was defined as concomitant exposure of capecitabine and the use of any PPI for 20% or more of the study period. The treatment-by-PPI-use interaction was examined after adjusting for stratification factors. RESULTS: Of the 482 patients, 49 (10.1%) used PPI. Among the PPI users, the mXELIRI group tended to have poorer overall survival compared with the FOLFIRI group. In contrast, among the nonusers, the overall survival of the mXELIRI group was significantly better than that of the FOLFIRI group. Similarly, a trend of worse progression-free survival with mXELIRI compared with FOLFIRI was observed in PPI users but not in nonusers. Treatment-by-PPI-use interaction was significant for overall survival and progression-free survival. CONCLUSION: The significant interaction between PPI use and the type of fluoropyrimidine in terms of overall and progression-free survival suggests that fluorouracil could be a more favorable option than capecitabine for patients with metastatic colorectal cancer using PPIs. IMPLICATIONS FOR PRACTICE: This study showed a significant interaction between the use of proton pump inhibitors (PPIs) and the type of fluoropyrimidines. This interaction mainly comes from the positive impact of PPIs in the survival outcomes in the fluorouracil arm rather than a negative impact of PPIs in the capecitabine arm. The possible drug-drug interaction shown in this study suggests that fluorouracil, rather than capecitabine, could be a more appropriate choice of fluoropyrimidine for patients who are taking PPIs in the treatment of metastatic colorectal cancer.

Risk of metastatic pheochromocytoma and paraganglioma in SDHx mutation carriers: a systematic review and updated meta-analysis.

BACKGROUND: Pheochromocytoma and paraganglioma (PPGL) are tumours that arise from chromaffin cells. Some genetic mutations influence PPGL, among which, those in genes encoding subunits of succinate dehydrogenase (SDHA, SDHB, SDHC and SDHD) and assembly factor (SDHAF2) are the most relevant. However, the risk of metastasis posed by these mutations is not reported except for SDHB and SDHD mutations. This study aimed to update the metastatic risks, considering prevalence and incidence of each SDHx mutation, which were dealt formerly all together. METHODS: We searched EMBASE and MEDLINE and selected 27 articles. The patients included in the studies were divided into three groups depending on the presence of PPGL. We checked the heterogeneity between studies and performed a meta-analysis using Hartung-Knapp-Sidik-Jonkman method based on a random effect model. RESULTS: The highest PPGL prevalence was for SDHB mutation, ranging from 23% to 31%, and for SDHC mutation (23%), followed by that for SDHA mutation (16%). The lowest prevalence was for SDHD mutation, ranging from 6% to 8%. SDHAF2 mutation showed no metastatic events. The PPGL incidence showed a tendency similar to that of its prevalence with the highest risk of metastasis posed by SDHB mutation (12%-41%) and the lowest risk by SDHD mutation (~4%). CONCLUSION: There was no integrated evidence of how SDHx mutations are related to metastatic PPGL. However, these findings suggest that SDHA, SDHB and SDHC mutations are highly associated and should be tested as indicators of metastasis in patients with PPGL.

MicroRNA-98 is a prognostic factor for asbestos-induced mesothelioma.

Malignant pleural mesothelioma (MPM) is a type of cancer characterized by a short survival time and poor prognosis. Malignant pleural mesothelioma is most frequently associated with exposure to asbestos and other elongated mineral fibers. The aim of this study was to examine molecular differences between asbestos-exposed and non-exposed MPM patients and assess prognostic significances of molecular factors. Clinical and genetic data were downloaded from Cancer Genome Atlas. To identify the molecular differences, Significant Analysis of Microarray method was used. Prognostic significances of differentially expressed genes were confirmed by using Kaplan-Meier curve with the Log-Rank test. Although mRNAs did not exhibit any significant differences between the two patient groups, nine miRNAs were found to be down-regulated in the asbestos-exposed group. The top five pathways most relevant to the selected miRNAs were extracted through pathway enrichment analysis. Survival analysis revealed that high expression of only hsa-miR-98 was significantly associated with poor prognosis in patients with asbestos-exposed MPM. Evidence suggests that management of the aggressiveness and progression of asbestos-induced MPM may require high levels of hsa-miR-98 due to its tumor-suppressive role. This study might be helpful in enhancing our understanding of the biological mechanisms underlying asbestos-induced MPM and for acquiring greater insights into targeted therapy.Abbreviations: FDR: false discovery rate; MM: malignant mesothelioma; MPM: malignant pleural mesothelioma; mRNA: messenger RNA; miRNA: microRNA; SAM: significance analysis of microarrays; TCGA: the cancer genome atlas.

A User-Friendly, Web-Based Integrative Tool (ESurv) for Survival Analysis: Development and Validation Study.

BACKGROUND: Prognostic genes or gene signatures have been widely used to predict patient survival and aid in making decisions pertaining to therapeutic actions. Although some web-based survival analysis tools have been developed, they have several limitations. OBJECTIVE: Taking these limitations into account, we developed ESurv (Easy, Effective, and Excellent Survival analysis tool), a web-based tool that can perform advanced survival analyses using user-derived data or data from The Cancer Genome Atlas (TCGA). Users can conduct univariate analyses and grouped variable selections using multiomics data from TCGA. METHODS: We used R to code survival analyses based on multiomics data from TCGA. To perform these analyses, we excluded patients and genes that had insufficient information. Clinical variables were classified as 0 and 1 when there were two categories (for example, chemotherapy: no or yes), and dummy variables were used where features had 3 or more outcomes (for example, with respect to laterality: right, left, or bilateral). RESULTS: Through univariate analyses, ESurv can identify the prognostic significance for single genes using the survival curve (median or optimal cutoff), area under the curve (AUC) with C statistics, and receiver operating characteristics (ROC). Users can obtain prognostic variable signatures based on multiomics data from clinical variables or grouped variable selections (lasso, elastic net regularization, and network-regularized high-dimensional Cox-regression) and select the same outputs as above. In addition, users can create custom gene signatures for specific cancers using various genes of interest. One of the most important functions of ESurv is that users can perform all survival analyses using their own data. CONCLUSIONS: Using advanced statistical techniques suitable for high-dimensional data, including genetic data, and integrated survival analysis, ESurv overcomes the limitations of previous web-based tools and will help biomedical researchers easily perform complex survival analyses.

Role of kif2c, A Gene Related to ALL Relapse, in Embryonic Hematopoiesis in Zebrafish.

Relapse of acute lymphoblastic leukemia (ALL) is dangerous and it worsens the prognosis of patients; however, prognostic markers or therapeutic targets for ALL remain unknown. In the present study, using databases such as TARGET, GSE60926 and GSE28460, we determined that KIF2C and its binding partner, KIF18B are overexpressed in patients with relapsed ALL compared to that in patients diagnosed with ALL for the first time. As 50% of the residues are exactly the same and the signature domain of KIF2C is highly conserved between human and zebrafish, we used zebrafish embryos as a model to investigate the function of kif2c in vivo. We determined that kif2c is necessary for lymphopoiesis in zebrafish embryos. Additionally, we observed that kif2c is not related to differentiation of HSCs; however, it is important for the maintenance of HSCs as it provides survival signals to HSCs. These results imply that the ALL relapse-related gene KIF2C is linked to the survival of HSCs. In conclusion, we suggest that KIF2C can serve as a novel therapeutic target for relapsed ALL.

Efficacy and safety of lanreotide in Korean patients with metastatic, well-differentiated gastroenteropancreatic-neuroendocrine tumors: a retrospective analysis.

Lanreotide autogel is a long-acting somatostatin analogue with proven efficacy and safety in patients with well-differentiated (WD) gastroenteropancreatic-neuroendocrine tumors (GEP-NETs) in a prior randomized phase III trial (CLARINET). However, the CLARINET study only enrolled patients with Ki-67 index <10%, and few patients of Asian ethnicity were included. We retrospectively analyzed the efficacy and safety of lanreotide in Korean patients with GEP-NETs in the daily practice setting. Between January 2015 and May 2018, 64 patients with metastatic WD GEP-NETs received lanreotide at Asan Medical Center, Seoul, Korea. Of them, 45 (70.3%) patients who received lanreotide as monotherapy were included in the current analysis. The most common primary tumor site was the pancreas (n = 22, 48.9%), followed by the rectum (10, 22.2%) and the small bowel (7, 15.6%). According to RECIST v1.1, a partial response was achieved in one patient (2.2%) and stable disease was achieved in 40 patients (88.9%). The median progression-free survival (PFS) was 16.4 months (95% confidence interval, 9.5-23.3 months). There were no differences in PFS according to the primary tumor site (p = 0.77). Hepatic tumor volume > 25% and prior systemic therapy were significantly associated with poorer PFS in the multivariate analysis. Lanreotide is well-tolerated and effective for Korean patients with GEP-NETs in the daily practice setting.

Comparison of genetic and epigenetic profiles of periodontitis according to the presence of type 2 diabetes.

Type 2 diabetes mellitus (T2DM) and periodontitis (PD) have intricated connections as chronic inflammatory diseases. While the immune response is a key factor that accounts for their association, the underlying mechanisms remain unclear. To gain a deeper understanding of the connection, we conducted research using a multiomics approach. We generated whole genome and methylation profiling array data from the periodontium of PD patients with DM (PDDM) and without DM to confirm genetic and epigenetic changes. Independent bulk and single-cell RNA sequencing data were employed to verify the expression levels of hypo-methylated genes. We observed a gradual rise in C>T base substitutions and hypomethylation in PD and PDDM patients compared with healthy participants. Furthermore, specific genetic and epigenetic alterations were prominently associated with the Fc-gamma receptor-mediated phagocytosis pathway. The upregulation of these genes was confirmed in both the periodontal tissues of PD patients and the pancreatic tissues of T2DM patients. Through single-cell RNA analysis of peripheral blood mononuclear cells, substantial upregulation of Fc-gamma receptors and related genes was particularly identified in monocytes. Our findings suggest that targeting the Fc-gamma signaling pathway in monocytes holds promise as a potential treatment strategy for managing systemic complications associated with diabetes.

Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types.

The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8887 TCGA, and 1261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n = 1261) including our lung cancer cohort (n = 497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.

Single-cell analysis of platelets from patients with periodontitis and diabetes.

Background: Blood platelets are known to play a role in the development of atherosclerotic disease, thrombi, and hemostasis. Investigation of blood platelet transcriptome could provide evidence of disorders that increase vulnerability to cardiovascular disease. However, research on the molecular insights of platelet activation in patients with periodontitis and patients with periodontitis and type 2 diabetes mellitus (DM) is still lacking. Objectives: In this study, we analyzed expression in blood platelets from patients with periodontitis and patients with concurrent periodontitis and DM to examine the transcriptomic profile of platelets induced by periodontitis and the modifying effects of DM. Methods: We obtained the transcriptional profiles of blood platelets from 11 healthy donors, 10 patients with periodontitis, and 6 patients with periodontitis and DM using single-cell RNA sequencing. The biological processes and coexpressed modules of transcriptionally altered genes were further explored. Results: Both the patients with periodontitis and DM and those with periodontitis without DM showed higher levels of platelet activation and coagulation signals than the healthy individuals. Platelets from the patients with periodontitis had higher expression levels of genes for RHO GTPase effectors, whereas platelets from the patients with periodontitis and DM demonstrated higher expression of genes involved in oxidative phosphorylation and cellular responses to stress than those from the controls. However, compared with the patients with only periodontitis, those with periodontitis and DM presented a lower expression level of genes for hemostasis and platelet receptors. Conclusion: These results suggest that periodontitis contributes to establishment of blood coagulation via platelet dysregulation, whereas the comorbidities of patients with periodontitis and DM impair the components of platelets, thus preventing normal functions.

Predicting prognosis through the discovery of specific biomarkers according to colorectal cancer lymph node metastasis.

Colorectal cancer (CRC) is a prevalent cancer worldwide, ranking as the third most common cancer and the second leading cause of cancer-related deaths. The presence or absence of lymph node metastases is one of the representative markers for predicting CRC prognosis, but often yields heterogeneous results. In this study, we conducted an integrative molecular analysis of CRC using publicly available data from The Cancer Genome Atlas database and NCBI's Gene Expression Omnibus. Through our analysis, we identified 372 upregulated genes that were differentially expressed in CRC patients. Additionally, Kyoto Encyclopedia of Genes and Genomes analysis revealed five significant pathways, including Hippo, FC-gamma, and forkhead box O signaling pathways, which are known to be associated with cancer. Survival analysis of 28 genes involved in these pathways led to the identification of 13 genes with prognostic significance (P < 0.05). To validate our findings, logistic regression models were generated and tested in multiple cohorts, demonstrating significant accuracy. Moreover, we identified six genes (BNIP3, CD63, RDX, RGCC, WASF1, and WASF3) whose combination predicted the best prognosis based on survival analysis. This predictive model holds promise as a potential biomarker for prognosis, survival, and treatment efficacy. In conclusion, our study provides valuable insights into the molecular characteristics of CRC and identifies prognostic biomarkers. The combination of differentially expressed genes and their involvement in cancer-related pathways enhances our understanding of CRC pathogenesis and opens avenues for personalized treatment approaches and improved patient outcomes.

Single-cell mapping of combinatorial target antigens for CAR switches using logic gates.

Identification of optimal target antigens that distinguish cancer cells from normal surrounding tissue cells remains a key challenge in chimeric antigen receptor (CAR) cell therapy for tumors with intratumoral heterogeneity. In this study, we dissected tissue complexity to the level of individual cells through the construction of a single-cell expression atlas that integrates ~1.4 million tumor, tumor-infiltrating normal and reference normal cells from 412 tumors and 12 normal organs. We used a two-step screening method using random forest and convolutional neural networks to select gene pairs that contribute most to discrimination between individual malignant and normal cells. Tumor coverage and specificity are evaluated for the AND, OR and NOT logic gates based on the combinatorial expression pattern of the pairing genes across individual single cells. Single-cell transcriptome-coupled epitope profiling validates the AND, OR and NOT switch targets identified in ovarian cancer and colorectal cancer.

Differential microbiota network in gingival tissues between periodontitis and periodontitis with diabetes.

Periodontitis and diabetes mellitus (DM) have a bidirectional relationship. Periodontitis is initiated by dysbiosis of oral microorganisms, and in particular, the characteristics of the microorganisms that have penetrated the tissue are directly related to the disease; therefore, we investigated the effect of DM on intragingival microbial profiling of patients with periodontitis. A total of 39 subjects were recruited and divided into three groups in this case control study as follows: healthy (NA, 10), periodontitis only (PD, 18), and periodontitis with DM (PD_DM, 11). Gingival tissue was collected, DNA was extracted, and whole-genome sequencing was performed. PD and PD_DM showed different characteristics from NA in diversity and composition of the microbial community; however, no difference was found between the PD nad PD_DM. PD_DM showed discriminatory characteristics for PD in the network analysis. PD showed a network structure in which six species were connected, including three red complex species, and PD_DM's network was more closely connected and expanded, with six additional species added to the PD network. Although DM did not significantly affect α- and ß-diversity or abundance of phyla and genera of microbiota that invaded the gingival tissue of patients with periodontitis, DM will affect the progression of periodontitis by strengthening the bacterial network in the gingival tissue.

DeepCIA: a novel deep-learning model for cancer type identification using class activation map via transcription factor expression.

Deep learning methods are powerful analytical tools for large-scale data analysis. Here, we introduce DeepCIA as a novel diagnostic deep-learning model for cancer type identification using a class activation map via transcription factor expression. Although many deep learning researches attempts have recently been made in relation to cancer diagnosis, there are difficulties in using cancer data due to a large-scale problem. Therefore, From The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) public databases, we selected transcription factor expression profiles of eight cancer types. TCGA included 3496 samples and divided the train and validation sets in an 8:2 ratio. ICGC included 552 samples and was used as a test set for external validation. To compare the performance of 1D-CNN models, we also used SVM and KNN from machine learning. In external validation, 1D-CNN showed a high average accuracy of 98% and was superior to support vector machine (SVM) and k-nearest neighbor (KNN) with a difference in the accuracy of 10-12%. Also, 1D-CNN performed very well in several performance metrics (98.2% Recall, 98.1% Precision, 98.2% F score, 99.8% Specificity, 99.8% AUC, and 99.0% Balanced Accuracy). In each data set evaluation, 1-network, 5-network, and 2-network with high accuracy were selected and visualized through the Class Activation Map. We identified the Cys2Hys2 zinc finger group with the highest distribution across all cancer types. Collectively, DeepCIA can be used as a decision support system for cancer and a classifier for diagnosing unknown primary cancer, while emphasizing its usefulness in cancer diagnosis.

Role of PCK2 in the proliferation of vascular smooth muscle cells in neointimal hyperplasia.

Vascular smooth muscle cell (VSMC) proliferation is a hallmark of neointimal hyperplasia (NIH) in atherosclerosis and restenosis post-balloon angioplasty and stent insertion. Although numerous cytotoxic and cytostatic therapeutics have been developed to reduce NIH, it is improbable that a multifactorial disease can be successfully treated by focusing on a preconceived hypothesis. We, therefore, aimed to identify key molecules involved in NIH via a hypothesis-free approach. We analyzed four datasets (GSE28829, GSE43292, GSE100927, and GSE120521), evaluated differentially expressed genes (DEGs) in wire-injured femoral arteries of mice, and determined their association with VSMC proliferation in vitro. Moreover, we performed RNA sequencing on platelet-derived growth factor (PDGF)-stimulated human VSMCs (hVSMCs) post-phosphoenolpyruvate carboxykinase 2 (PCK2) knockdown and investigated pathways associated with PCK2. Finally, we assessed NIH formation in Pck2 knockout (KO) mice by wire injury and identified PCK2 expression in human femoral artery atheroma. Among six DEGs, only PCK2 and RGS1 showed identical expression patterns between wire-injured femoral arteries of mice and gene expression datasets. PDGF-induced VSMC proliferation was attenuated when hVSMCs were transfected with PCK2 siRNA. RNA sequencing of PCK2 siRNA-treated hVSMCs revealed the involvement of the Akt-FoxO-PCK2 pathway in VSMC proliferation via Akt2, Akt3, FoxO1, and FoxO3. Additionally, NIH was attenuated in the wire-injured femoral artery of Pck2-KO mice and PCK2 was expressed in human femoral atheroma. PCK2 regulates VSMC proliferation in response to vascular injury via the Akt-FoxO-PCK2 pathway. Targeting PCK2, a downstream signaling mediator of VSMC proliferation, may be a novel therapeutic approach to modulate VSMC proliferation in atherosclerosis.

Risk stratification of patients with right-sided colorectal cancer based on the tumor-infiltrating M1 macrophage.

The homing of M1 and M2 macrophages may play distinct roles in the tumor microenvironment (TME). However, these roles of macrophages in the TME remain unclear. We downloaded RNA sequencing data from The Cancer Genome Atlas (TCGA) database for patients with CRC. Subsequently, Kaplan-Meier survival curves were generated to assess the differential infiltration of M1 and M2 macrophages based on CRC location. Differentially expressed gene (DEG) and functional analyses were performed to screen the roles of DEGs. Critical prognostic genes were identified using least absolute shrinkage and selection operator regression. The risk scores were calculated for each patient. In patients with right-sided CRC, reduced M1 macrophage infiltration was associated with poor prognosis. M1 macrophage infiltration positively correlated with CD8+ T cell infiltration. A risk model was developed and validated for performance using GSE103479 and GSE72970. Nine genes were identified as independent prognostic genes that could be potential biomarkers for effectively predicting survival in patients with right-sided CRC. Kaplan-Meier curves for overall survival and progression-free survival analyses revealed that the high-risk group of patients with right-sided CRC had a poor prognosis. This novel M1 macrophage-related risk model may provide a gene signature for predicting the survival outcomes of patients with right-sided CRC and facilitate further studies examining the relationship between infiltration of M1 macrophages and the prognosis of such patients.

Observation of spin-glass-like characteristics in ferrimagnetic TbCo through energy-level-selective approach.

Rare earth (RE)-transition metal (TM) ferrimagnetic alloys are gaining increasing attention because of their potential use in the field of antiferromagnetic spintronics. The moment from RE sub-lattice primarily originates from the 4f-electrons located far below the Fermi level (EF), and the moment from TM sub-lattice arises from the 3d-electrons across the EF. Therefore, the individual magnetic moment configurations at different energy levels must be explored to clarify the microscopic mechanism of antiferromagnetic spin dynamics. Considering these issues, here we investigate the energy-level-selective magnetic moment configuration in ferrimagnetic TbCo alloy. We reveal that magnetic moments at deeper energy levels are more easily altered by the external magnetic field than those near the EF. More importantly, we find that the magnetic moments at deeper energy levels exhibit a spin-glass-like characteristics such as slow dynamics and magnetic moment freezing whereas those at EF do not. These unique energy-level-dependent characteristics of RE-TM ferrimagnet may provide a better understanding of ferrimagnet, which could be useful in spintronic applications as well as in spin-glass studies.

Possible respiratory syncytial virus infection presenting as diffuse alveolar hemorrhage in an elderly treated with systemic corticosteroid: A case report.

INTRODUCTION: Respiratory syncytial virus infection is gaining interest in the elderly due to its growing morbidity and mortality. We present a Case of respiratory syncytial virus infection presenting as diffuse alveolar hemorrhage that was highly responsive to systemic corticosteroid in an elderly patient. CASE PRESENTATION: An 82-year old man was admitted to the intensive care unit with worsening hypoxic respiratory failure. Chest radiograph showed non-homogeneous air space opacities. Bronchoalveolar lavage showed a finding of alveolar hemorrhage. The diagnosis of diffuse alveolar hemorrhage was made and high-dose systemic corticosteroid was given. However, concomitant respiratory syncytial virus infection was later confirmed. Therefore, ribavirin and human immunoglobulin were added. During the course of his treatment, the steroid was stopped and restarted. Interestingly, the clinical course was highly responsive to systemic corticosteroid. CONCLUSION: It appears that diffuse alveolar hemorrhage in this patient may have been due to an immunological process caused by respiratory syncytial virus. Therefore, corticosteroid therapy was highly effective in improving the patient's hemoptysis and hypoxic respiratory failure. We suggest that further studies are required on the use of steroid in this subset of patients with respiratory syncytial virus lower respiratory tract infection.

Molecular differences between stable idiopathic pulmonary fibrosis and its acute exacerbation.

INTRODUCTION: The molecular mechanisms underlying acute exacerbations (AEs) of idiopathic pulmonary fibrosis (IPF) are poorly understood. To understand the gene expression patterns of the AEs of IPF, we studied gene expression profiling of AEs of IPF. METHODS: The GEO datasets included in this study are GSE44723 and GSE10667, and in-house RNA-seq data were used. DEG analysis used the limma package, and the STRING database was used to construct the protein-protein interaction (PPI) network, and its functional role was investigated through gene ontology analysis. RESULTS: The results of DEG analysis indicated 76 upregulated and 135 downregulated genes associated with an AE of IPF compared to stable IPF. The PPI network included three core modules containing 24 of the 211 DEGs. Eleven upregulated and six downregulated genes were evident in AEs of IPF compared with stable IPF after validation. The upregulated genes were associated with cell division. The downregulated genes were related to skeletal muscle differentiation and development. CONCLUSION: In previous studies, 17 genes were strongly associated with cell proliferation in various cell types. In particular, cyclin A2 (CCNA2) was overexpressed in the alveolar epithelium of the lungs presenting AEs of IPF. Aside from the previously described CCNA2, this study reveals 16 genes associated with AEs of IPF. This data could indicate new therapeutic targets and potential biomarkers for the AEs of IPF.