Comparative genomics on chloroplasts of Rubus (Rosaceae).

Rubus, the largest genus in Rosaceae, contains over 1400 species that distributed in multiple habitats across the world, with high species diversity in the temperate regions of Northern Hemisphere. Multiple Rubus species are cultivated for their valuable fruits. However, the intrageneric classification and phylogenetic relationships are still poorly understood. In this study, we sequenced, assembled, and characterized 17 plastomes of Rubus, and conducted comparative genomics integrating with 47 previously issued plastomes of this genus. The 64 plastomes of Rubus exhibited typical quadripartite structure with sizes ranging from 155,144 to 156,700 bp, and contained 132 genes including 87 protein-coding genes, 37 tRNA genes and eight rRNA genes. All plastomes are conservative in the gene order, the frequency of different types of long repeats and simple sequence repeats (SSRs), the codon usage, and the selection pressure of protein-coding genes. However, there are also some differences in the Rubus plastomes, including slight contraction and expansion of the IRs, a variation in the numbers of SSRs and long repeats, and some genes in certain clades undergoing intensified or relaxed purifying selection. Phylogenetic analysis based on whole plastomes showed that the monophyly of Rubus was strongly supported and resolved it into six clades corresponding to six subgenera. Moreover, we identified 12 highly variable regions that could be potential molecular markers for phylogenetic, population genetic, and barcoding studies. Overall, our study provided insight into plastomic structure and sequence diversification of Rubus, which could be beneficial for future studies on identification, evolution, and phylogeny in this genus.

An exploration of causal relationships between nine neurological diseases and the risk of breast cancer: a Mendelian randomization study.

BACKGROUND: Some preceding researches have observed that certain neurological disorders, such as Alzheimer's disease and multiple sclerosis, may affect breast cancer risk. However, whether there are causal relationships between these neurological conditions and breast cancer is inconclusive. This study was designed to explore whether neurological disorders affected the risks of breast cancer overall and of the two subtypes (ER+ and ER-). METHODS: In the course of this study, genome-wide association study (GWAS) data for nine neurological diseases (Alzheimer's disease, multiple sclerosis, Parkinson's disease, myasthenia gravis, generalized epilepsy, intracerebral haemorrhage, cerebral atherosclerosis, brain glioblastoma, and benign meningeal tumour) were collected from the Complex Trait Genetics lab and the MRC Integrative Epidemiology Unit, and single-nucleotide polymorphisms (SNPs) extensively associated with these neurological ailments had been recognized as instrumental variables (IVs). GWAS data on breast cancer were collected from the Breast Cancer Association Consortium (BCAC). Two-sample Mendelian randomization (MR) analyses as well as multivariable MR analyses were performed to determine whether these SNPs contributed to breast cancer risk. Additionally, the accuracy of the results was evaluated using the false discovery rate (FDR) multiple correction method. Both heterogeneity and pleiotropy were evaluated by analyzing sensitivities. RESULTS: According to the results of two-sample MR analyses, Alzheimer's disease significantly reduced the risks of overall (OR 0.925, 95% CI [0.871-0.982], P = 0.011) and ER+ (OR 0.912, 95% CI [0.853-0.975], P = 0.007) breast cancer, but there was a negative result in ER- breast cancer. However, after multiple FDR corrections, the effect of Alzheimer's disease on overall breast cancer was not statistically significant. In contrast, multiple sclerosis significantly increased ER+ breast cancer risk (OR 1.007, 95% CI [1.003-1.011], P = 0.001). In addition, the multivariable MR analyses showed that Alzheimer's disease significantly reduced the risk of ER+ breast cancer (IVW: OR 0.929, 95% CI [0.864-0.999], P=0.047; MR-Egger: OR 0.916, 95% CI [0.846-0.992], P=0.031); however, multiple sclerosis significantly increased the risk of ER+ breast cancer (IVW: OR 1.008, 95% CI [1.003-1.012], P=4.35×10-4; MR-Egger: OR 1.008, 95% CI [1.003-1.012], P=5.96×10-4). There were no significant associations between the remainder of the neurological diseases and breast cancer. CONCLUSIONS: This study found the trends towards a decreased risk of ER+ breast cancer in patients with Alzheimer's disease and an increased risk in patients with multiple sclerosis. However, due to the limitations of Mendelian randomization, we cannot determine whether there are definite causal relationships between neurological diseases and breast cancer risk. For conclusive evidences, more prospective randomized controlled trials will be needed in the future.

An exploratory study of whether axillary lymph node dissection can be avoided in breast cancer patients with positive lymph nodes.

Background: Breast cancer patients with positive axillary lymph nodes usually require axillary lymph node dissection (ALND), with many postoperative complications, such as lymphedema. For these patients, whether sentinel lymph node biopsy (SLNB) can replace ALND has been a research hotspot in the field of breast cancer. This study developed two risk stratification models for predicting the clinical outcomes of breast cancer patients with positive axillary lymph nodes receiving SLNB alone or ALND to determine which patients could potentially avoid ALND. Methods: A total of 21,942 breast cancer patients, including a training set (n=15,362) and a testing set (n=6,580), were enrolled in this study from Surveillance, Epidemiology, and End Results (SEER) between 2000 and 2017. The risk factors associated with breast cancer-specific survival (BCSS) and overall survival (OS) were evaluated using multivariate Cox regression analysis and then integrated into nomograms and risk stratification models examined by receiver operating characteristic (ROC) curves and calibration curves. The survival discrepancies were compared between the SLNB and ALND subgroups with different risk scores with Kaplan-Meier plots. Results: In multivariate Cox regression analyses, grade, marital status, T stage, radiotherapy and lymph node metastasis (GMTRL) were independent risk factors in breast cancer patients with both OS and BCSS status in the ALND cohort from the training set. Nomograms have been developed based on these factors to predict 3- and 5-year OS and BCSS in patients with ALND. Calibration curves and ROC curves in both the training and testing sets confirmed the excellent overall predictive performance of the nomograms. Furthermore, we developed two risk stratification models based on OS and BCSS status, revealing that patients with low GMTRL scores might avoid ALND in both OS and BCSS status [OS: hazard ratio (HR) =0.929, 95% confidence interval (CI): 0.841-1.027, P=0.150; BCSS: HR =0.953, 95% CI: 0.831-1.094, P=0.495], but patients with moderate (OS: HR =0.756, 95% CI: 0.666-0.859, P<0.001; BCSS: HR =0.643, 95% CI: 0.537-0.768, P<0.001) and high GMTRL scores could not (OS: HR =0.719, 95% CI: 0.549-0.940, P=0.014; BCSS: HR =0.731, 95% CI: 0.549-0.974, P=0.031). Conclusions: Breast cancer patients with positive nodes could be treated with SLNB alone rather than ALND without affecting prognosis based on GMTRL scores. Patients with high or moderate GMTRL scores benefited greatly from ALND, but not for patients with low GMTRL scores. This study may assist clinicians in tailoring treatments.

Quantum Dot-Based Immunoassays: Unraveling Sensitivity Discrepancies and Charting Future Frontiers.

The 2023 Nobel Prize in Chemistry honors the groundbreaking contributions of Alexei Ekimov, Louis Brus, and Moungi Bawendi to the field of quantum dots (QDs). In this spirit, we developed a direct competitive QD fluorescence immunoassay (dc-QD-FLISA) to detect aristolochic acid type I (AAI), a potent carcinogen found in herbal remedies. Unexpectedly, the dc-QD-FLISA exhibited lower sensitivity than that of an indirect competitive enzyme-linked immunosorbent assay (ic-ELISA), contrary to our initial expectations. This discrepancy in the sensitivity prompted a comprehensive analysis of the entire experimental process. We propose that steric hindrance between QDs and antigen-binding sites on antibodies may significantly diminish the binding efficiency, reducing sensitivity within the dc-QD-FLISA method. Furthermore, issues such as buffer conditions, antibody handling, and separation methods are also contributing factors. We recommend site-directed QD modification and stringent consideration of the experimental conditions. This study not only provides insights into QD-based immunoassays but also highlights the need for future advancements in immunoassay technology in terms of augmenting sensitivity and specificity, potentially revolutionizing disease diagnosis, biomarker discovery, and biomedical research.

Applications of photodynamic therapy in extramammary Paget's disease.

Extramammary Paget's disease (EMPD) is a rare form of adenocarcinoma usually found in apocrine gland-containing cutaneous regions. EMPD affects the vulvar area most commonly, followed by the perianal area, scrotum, penis, and axillary region. In its initial form, EMPD presents as an erythematous plaque with well-defined edges, fine scaling, excoriations, exulcerations, and lichenification. Generally, a definitive diagnosis can be made through histopathological analysis. Importantly, associated malignancies should be investigated prior to treatment initiation. Photodynamic therapy (PDT) is a modern, noninvasive treatment strategy for non-oncological diseases as well as various cancers. In recent years, PDT has been widely used to treat EMPD. This present article presents a discussion of the diagnosis and treatment of EMPD as well as the usefulness of PDT in its management.

Analysis of first responder-involved traffic incidents by mining news reports.

Roadside service and incident response personnel face the risk of being killed or severely injured by passing vehicles when performing their duties on or along a road. This study investigated 5,113 responder-involved event news reports to understand the characteristics of first responder-involved incidents. Through text mining, this study examined and compared the characteristics of three types of responder-involved incidents: near-miss incidents, struck-by incidents, and line-of-duty-deaths (LODD). A higher proportion of struck-by and LODD incidents are associated with law enforcement agencies. In terms of the time of day, morning and night incidents are frequently reported in the news. Driving under the influence (DUI) or driving while intoxicated (DWI) is a major cause of LODD incidents. Compared to struck-by incidents, LODD incidents have a larger portion related to out-of-control vehicles. Further, this study built a logistic regression model to relate the incident characteristics to the odds of an incident being a LODD incident. The modeling result shows that tow truck drivers are associated with a greater likelihood of being involved in a news-reported LODD incident than other responders. LODD incidents are more likely to occur on early morning. Compare to entering/leaving/staying at the scene, responders are more likely to be involved in LODD event when assisting. The results offer insights into understanding the characteristics and possible reasons for first responder-involved incidents so that potential countermeasures could be developed to improve responder safety.

Evaluation of Male Breast Cancer and the Application of Sentinel Lymph Node Biopsy: A Multicenter Retrospective Study.

Sentinel lymph node biopsy (SLNB) is currently used as a routine treatment for patients with breast cancer. However, it may not be applicable for patients with male breast cancer (MBC), because they have notably different clinicopathological features from those occurring in females. There is a lack of evidence of SLNB application and safe exemption from axillary lymph node dissection (ALND) in patients with MBC. This study aimed to evaluate the application of SLNB to provide information for the standardized treatment of patients with MBC. The MBC patient records from 4 institutions ranging from January 2001 to November 2020 were retrospectively reviewed. There were 220 patients with MBC with a median age of 60 (range 24-88) years and an average tumor size of 2.3 cm (range 0.5 cm-6.5 cm). Sixty-six percent of patients underwent SLNB, and 39% of them showed positive results. A total of 157 patients underwent ALND, while only half of them had positive nodes, causing unnecessary complications. For patients in the clinical early stage, we found that the SLNB showed a noninferiority to the ALND treatment in DFS (P = .18) and OS (P = .055). In conclusion, there are certain obstacles to the broad application of SLNB due to the lower proportion of patients with clinically negative lymph nodes. However, it is undeniable that SLNB can safely and effectively exempt patients with MBC at early stage with clinically negative nodes from ALND to reduce subsequent complications. It is still an ideal criterion for the axillary staging of patients with MBC.

An exploration of the correlations between seven psychiatric disorders and the risks of breast cancer, breast benign tumors and breast inflammatory diseases: Mendelian randomization analyses.

Background: Previous observational studies have showed that certain psychiatric disorders may be linked to breast cancer risk, there is, however, little understanding of relationships between mental disorders and a variety of breast diseases. This study aims to investigate if mental disorders influence the risks of overall breast cancer, the two subtypes of breast cancer (ER+ and ER-), breast benign tumors and breast inflammatory diseases. Methods: During our research, genome-wide association study (GWAS) data for seven psychiatric disorders (schizophrenia, major depressive disorder, bipolar disorder, post-traumatic stress disorder, panic disorder, obsessive-compulsive disorder and anorexia nervosa) from the Psychiatric Genomics Consortium (PGC) and the UK Biobank were selected, and single-nucleotide polymorphisms (SNPs) significantly linked to these mental disorders were identified as instrumental variables. GWAS data for breast diseases came from the Breast Cancer Association Consortium (BCAC) as well as the FinnGen consortium. We performed two-sample Mendelian randomization (MR) analyses and multivariable MR analyses to assess these SNPs' effects on various breast diseases. Both heterogeneity and pleiotropy were evaluated by sensitivity analyses. Results: When the GWAS data of psychiatric disorders were derived from the PGC, our research found that schizophrenia significantly increased the risks of overall breast cancer (two-sample MR: OR 1.05, 95%CI [1.03-1.07], p = 3.84 × 10-6; multivariable MR: OR 1.06, 95%CI [1.04-1.09], p = 2.34 × 10-6), ER+ (OR 1.05, 95%CI [1.02-1.07], p = 5.94 × 10-5) and ER- (two-sample MR: OR 1.04, 95%CI [1.01-1.07], p = 0.006; multivariable MR: OR 1.06, 95%CI [1.02-1.10], p = 0.001) breast cancer. Nevertheless, major depressive disorder only showed significant positive association with overall breast cancer (OR 1.12, 95%CI [1.04-1.20], p = 0.003) according to the two-sample MR analysis, but not in the multivariable MR analysis. In regards to the remainder of the mental illnesses and breast diseases, there were no significant correlations. While as for the data from the UK Biobank, schizophrenia did not significantly increase the risk of breast cancer. Conclusions: The correlation between schizophrenia and breast cancer found in this study may be false positive results caused by underlying horizontal pleiotropy, rather than a true cause-and-effect relationship. More prospective studies are still needed to be carried out to determine the definitive links between mental illnesses and breast diseases.

Infiltrating myeloid cell diversity determines oncological characteristics and clinical outcomes in breast cancer.

BACKGROUND: Breast cancer presents as one of the top health threats to women around the world. Myeloid cells are the most abundant cells and the major immune coordinator in breast cancer tumor microenvironment (TME), target therapies that harness the anti-tumor potential of myeloid cells are currently being evaluated in clinical trials. However, the landscape and dynamic transition of myeloid cells in breast cancer TME are still largely unknown. METHODS: Myeloid cells were characterized in the single-cell data and extracted with a deconvolution algorithm to be assessed in bulk-sequencing data. We used the Shannon index to describe the diversity of infiltrating myeloid cells. A 5-gene surrogate scoring system was then constructed and evaluated to infer the myeloid cell diversity in a clinically feasible manner. RESULTS: We dissected the breast cancer infiltrating myeloid cells into 15 subgroups including macrophages, dendritic cells (DCs), and monocytes. Mac_CCL4 had the highest angiogenic activity, Mac_APOE and Mac_CXCL10 were highly active in cytokine secretion, and the DCs had upregulated antigen presentation pathways. The infiltrating myeloid diversity was calculated in the deconvoluted bulk-sequencing data, and we found that higher myeloid diversity was robustly associated with more favorable clinical outcomes, higher neoadjuvant therapy responses, and a higher rate of somatic mutations. We then used machine learning methods to perform feature selection and reduction, which generated a clinical-friendly scoring system consisting of 5 genes (C3, CD27, GFPT2, GMFG, and HLA-DPB1) that could be used to predict clinical outcomes in breast cancer patients. CONCLUSIONS: Our study explored the heterogeneity and plasticity of breast cancer infiltrating myeloid cells. By using a novel combination of bioinformatic approaches, we proposed the myeloid diversity index as a new prognostic metric and constructed a clinically practical scoring system to guide future patient evaluation and risk stratification.

Establishment and validation of a multigene model to predict the risk of relapse in hormone receptor-positive early-stage Chinese breast cancer patients.

BACKGROUND: Breast cancer patients who are positive for hormone receptor typically exhibit a favorable prognosis. It is controversial whether chemotherapy is necessary for them after surgery. Our study aimed to establish a multigene model to predict the relapse of hormone receptor-positive early-stage Chinese breast cancer after surgery and direct individualized application of chemotherapy in breast cancer patients after surgery. METHODS: In this study, differentially expressed genes (DEGs) were identified between relapse and nonrelapse breast cancer groups based on RNA sequencing. Gene set enrichment analysis (GSEA) was performed to identify potential relapse-relevant pathways. CIBERSORT and Microenvironment Cell Populations-counter algorithms were used to analyze immune infiltration. The least absolute shrinkage and selection operator (LASSO) regression, log-rank tests, and multiple Cox regression were performed to identify prognostic signatures. A predictive model was developed and validated based on Kaplan-Meier analysis, receiver operating characteristic curve (ROC). RESULTS: A total of 234 out of 487 patients were enrolled in this study, and 1588 DEGs were identified between the relapse and nonrelapse groups. GSEA results showed that immune-related pathways were enriched in the nonrelapse group, whereas cell cycle- and metabolism-relevant pathways were enriched in the relapse group. A predictive model was developed using three genes ( CKMT1B , SMR3B , and OR11M1P ) generated from the LASSO regression. The model stratified breast cancer patients into high- and low-risk subgroups with significantly different prognostic statuses, and our model was independent of other clinical factors. Time-dependent ROC showed high predictive performance of the model. CONCLUSIONS: A multigene model was established from RNA-sequencing data to direct risk classification and predict relapse of hormone receptor-positive breast cancer in Chinese patients. Utilization of the model could provide individualized evaluation of chemotherapy after surgery for breast cancer patients.

An overview of the correlation between IPI and prognosis in primary breast lymphoma.

Primary breast lymphoma (PBL), with diffuse large B-cell lymphoma (DLBCL) as the most histopathological type, is a rare disease with a poor prognosis. The International Prognostic Index (IPI) is an important clinical characteristic for risk stratification of PBL patients with different prognoses. However, the prognostic value of the IPI in PBL is controversial and needs to be refined. In this review, we described the clinical characteristics, pathogenesis, and treatment of PBL, with emphasis on the prognostic value of the IPI, its updated versions and IPIs for certain subtypes. A total of 9 types of IPIs were presented. In addition, the key issues with the various treatment modalities available were addressed, as well as the role of rituximab in therapy. We also summarized the current evidence and future challenges facing other types of prognostic indices. In particular, prospective clinical studies of treatment are rare, and the available data were mainly obtained from retrospective case series that included a small number of patients. Therefore, our conclusions and recommendations cannot serve as formal guidelines. However, this review attempts to provide an unbiased analysis of published data to provide clinicians with useful assistance in the treatment of this uncommon form of extranodal lymphoma.

Localizing safety performance functions for two-way STOP-controlled (TWST) three-leg intersections on rural two-lane two-way (TLTW) roadways in Alabama: A geospatial modeling approach with clustering analysis.

Safety Performance Functions (SPFs) can be used to predict the number of crashes for highway facilities by site characteristics, including traffic exposures and other specific site factors. The traditional approach to developing SPFs relies on factors that are observed in the data and has an unstated assumption that the relationships between safety performance and observed factors are stationary. However, there might be factors that are not captured by the data but also have significant impacts on roadway safety performance. These factors can lead to significant unobserved heterogeneity in safety performance at different sites. Failure to capture such unobserved heterogeneity in developing SPFs may result in biases and decrease the predictive accuracy. Given the interactions between highway traffic and roadway environments, the unobserved heterogeneity is likely related to the geographic space of the highway network. This study employs a spatial modeling approach, namely Geographically Weighted Negative Binomial Regression (GWNBR), to incorporate spatial heterogeneity into SPF model estimation. The GWNBR model can generate a local SPF for every site instead of a global SPF for one entire jurisdiction (e.g., a state) from the traditional approach. Local SPFs (or l-SPFs) are high-resolution and may be difficult for practitioners to use. To support the implementation of l-SPFs, this study proposes a method to aggregate l-SPFs to various geographic levels. This study first uses the 2014-2018 geo-referenced crash data from Alabama to develop l-SPFs for two-way STOP-controlled (TWST) three-leg intersections on rural two-lane two-way (TLTW) roadways in the state. The results show that l-SPFs vary substantially across Alabama. For example, the coefficients of traffic volume (AADT) on major roads range from 0.126 to 1.203 across different areas of the state. Then, an aggregation method based on K-means clustering is demonstrated to aggregate l-SPFs to various geographic levels of interest. The l-SPFs and their aggregation provide geographic flexibility in developing countermeasures and allocating funds to improve traffic safety considering local conditions.

Microbiome and its implications in oncogenesis: a Mendelian randomization perspective.

The human microbiome, an intricate ecological network, has garnered significant attention due to its potential implications in oncogenesis. This paper delves into the multifaceted relationships between the microbiome, its metabolites, and cancer development, emphasizing the human intestinal tract as the primary microbial habitat. Highlighting the potential causative associations between microbial disturbances and cancer progression, we underscore the role of specific bacterial strains in various cancers, such as stomach and colorectal cancer. Traditional causality assessment methods, like randomized controlled trials (RCTs), have limitations. Therefore, we advocate using Mendelian Randomization (MR) as a powerful alternative to study causal relationships, leveraging genetic variants as instrumental variables. With the proliferation of genome-wide association studies, MR harnesses genetic variations to infer causality, which is especially beneficial when addressing confounders like diet and lifestyle that can skew microbial research. We systematically review MR's application in understanding the microbiome-cancer nexus, emphasizing its strengths and challenges. While MR offers a unique perspective on causality, it faces hurdles like horizontal pleiotropy and weak instrumental variable bias. Integrating MR with multi-omics data, encompassing genomics, transcriptomics, proteomics, and metabolomics, holds promise for future research, potentially heralding groundbreaking discoveries in microbiology and genetics. This comprehensive review underscores the critical role of the human microbiome in oncogenesis and champions MR as an indispensable tool for advancing our understanding in this domain.

The prognostic value of IPI in patients with primary breast lymphoma, a multicenter retrospective study.

BACKGROUND: Due to the rarity of PBL and the lack of large-scale studies, the prognostic value of IPI in PBL was controversial. Especially in the rituximab era, the ability of IPI to stratify prognosis in patients receiving immunochemotherapy was severely reduced. Then revised IPI (R-IPI) and National Comprehensive Cancer Network IPI (NCCN-IPI) were introduced. The present study aimed to evaluate the prognostic value of IPI and the other IPIs in patients with PBL in a Chinese population. METHODS: We performed a multicenter retrospective study of 71 patients with PBL from 3 institutions in China. The Kaplan-Meier method and log-rank tests were used for the survival analysis. Cox regression analysis was performed to evaluate the prognostic factors. Subgroup analysis was performed to assess the prognostic significance of IPI scores, R-IPI scores, and NCCN-IPI scores. RESULTS: The median follow-up was 4.7 years (0.7-21.8 years). The 5-year progression-free survival (PFS) and overall survival (OS) rates were 90.2% and 96.3%. In the multivariate analysis, only IPI scores and radiotherapy were significantly associated with OS and PFS (P < 0.05). Applying the R-IPI in our patient cohort indicates a significant difference in PFS between the two groups of R-IPI (P = 0.034) but not for OS (P = 0.072). And the NCCN-IPI was prognostic for OS (P = 0.025) but not for PFS (P = 0.066). Subgroup analyses of IPI showed that survival analysis of IPI scores for the PFS and OS of patients using rituximab were not significantly different (P > 0.05). CONCLUSIONS: Our study confirms the prognostic value of IPI in patients with PBL, but the predictive value of IPI proved to be relatively low with the addition of the rituximab. The R-IPI and NCCN-IPI can accurately assess the high and low-risk groups of PBL patients but were insufficient to evaluate the intermediate risk group.

Electric Bicyclist Injury Severity during Peak Traffic Periods: A Random-Parameters Approach with Heterogeneity in Means and Variances.

Accidents involving electric bicycles, a popular means of transportation in China during peak traffic periods, have increased. However, studies have seldom attempted to detect the unique crash consequences during this period. This study aims to explore the factors influencing injury severity in electric bicyclists during peak traffic periods and provide recommendations to help devise specific management strategies. The random-parameters logit or mixed logit model is used to identify the relationship between different factors and injury severity. The injury severity is divided into four categories. The analysis uses automobile and electric bicycle crash data of Xi'an, China, between 2014 and 2019. During the peak traffic periods, the impact of low visibility significantly varies with factors such as areas with traffic control or without streetlights. Furthermore, compared with traveling in a straight line, three different turnings before the crash reduce the likelihood of severe injuries. Roadside protection trees are the most crucial measure guaranteeing riders' safety during peak traffic periods. This study reveals the direction, magnitude, and randomness of factors that contribute to electric bicycle crashes. The results can help safety authorities devise targeted transportation safety management and planning strategies for peak traffic periods.

Mechanical Ventilation Exacerbates Poly (I:C) Induced Acute Lung Injury: Central Role for Caspase-11 and Gut-Lung Axis.

Background: The mechanisms by which moderate tidal volume ventilation (MTV) exacerbates preexisting lung injury are unclear. We hypothesized that systemic endotoxemia via the gut-lung axis would lead to non-canonical and canonical inflammasome activation and pyroptosis in a two-hit model involving polyinosinic-polycytidylic acid (Poly(I:C)), a synthetic analog of dsRNA and MTV and that this would associate with acute lung injury (ALI). Methods: Anesthetized mice were administered Poly(I:C) intratracheally and then 6 h later, they were mechanically ventilated for 4 h with otherwise non-injurious MTV (10ml/kg). Changes in intestinal and alveolar capillary permeability were measured. Further documentation of ALI was assessed by evans blue albumin permeability, protein and IL-1 family concentration in bronchoalveolar lavage fluid (BALF) or plasma, and histopathology in cohorts of wildtype (WT), whole body genetically ablated caspase-11 (caspase-11-/-), caspase-1/caspase-11 double knockout (caspase-1/11-/-), gasdermin D (GSDMD)-/-, nucleotide-binding domain leucine-rich repeat-containing protein 3 (NLRP3)-/- and advanced glycosylation end product-specific receptor (RAGE) -/- mice. Results: Non-injurious MTV exacerbated the mild lung injury associated with Poly(I:C) administration. This included the disruption of alveolar-capillary barrier and increased levels of interleukin (IL)-6, high mobility group proteins 1 (HMGB-1), IL-1ß in BALF and IL-18 in plasma. Combined (Poly(I:C)-MTV) injury was associated with increase in gastrointestinal permeability and endotoxin in plasma and BALF. Poly(I:C)-MTV injury was sensitive to caspase-11 deletion with no further contribution of caspase-1 except for maturation and release of IL-18 (that itself was sensitive to deletion of NLRP3). Combined injury led to large increases in caspase-1 and caspase-11. Genetic ablation of GSDMD attenuated alveolar-capillary disruption and release of cytokines in combined injury model. Conclusions: The previously noted exacerbation of mild Poly(I:C)-induced ALI by otherwise non-injurious MTV is associated with an increase in gut permeability resulting in systemic endotoxemia. The gut-lung axis resulted in activation of pulmonary non-canonical (cytosolic mediated caspase-11 activation) and canonical (caspase-1) inflammasome (NLRP3) mediated ALI in this two-hit model resulting in GSDMD sensitive alveolar capillary barrier disruption, pyroptosis (alveolar macrophages) and cytokine maturation and release (IL-1ß; IL-18). Pharmacologic strategies aimed at disrupting communication between gut and lung, inhibition of inflammasomes or GSDMD in pyroptosis may be useful in ALI.

The Diagnostic Value of Conventional MRI and CT Features in the Identification of the IDH1-Mutant and 1p/19q Co-Deletion in WHO Grade II Gliomas.

RATIONALE AND OBJECTIVES: The classification of patients based on pathology and molecular features is important for improving WHO grade II glioma patient prognosis, especially for the initially diagnosed patients. Less invasive and more convenient methods for the prediction of the pathological type and gene status are desired. MATERIALS AND METHODS: This study investigates the ability to use conventional magnetic resonance imaging (MRI) and computed tomography (CT) features for determining the Isocitrate Dehydrogenase (IDH)-mutant and 1p/19q-codeletion status, through a retrospective review of information obtained from 189 WHO grade II glioma patients. Diffuse astrocytoma (IDH-mutant), Diffuse astrocytoma (IDH- wildtype) and Oligodendroglioma (IDH-mutant and 1p/19q co-deletion) were included in this cohort. All patients were divided into IDH-mutant group and IDH-wildtype group according to the IDH R132H mutation status. Moreover, all patients were divided into 1p/19q co-deletion group and 1p/19q non-codeletion group according to the 1p and 19q chromosome status. Patients underwent pre-operative CT and MRI scans, followed by operation and histopathological analyses, including immunohistochemistry and polymerase chain reaction analysis for IDH mutants, and fluorescence capillary electrophoresis analysis for the 1p/19q co-deletion. The χ2 test, logistical regression and receiver operating characteristic curve analysis were conducted for statistical analysis. RESULTS: IDH-mutant group patients exhibited a higher calcification frequency (25.2% vs 2.4%, p = 0.006) and lower frequency of T1 enhancement (20.4% vs 38.1%, p = 0.028) comparing patients in IDH-wildtype group, while 1p/19q co-deletion group patients exhibited a higher calcification frequency (46.67% vs 2.6%, p < 0.001) and lower homogenous signal frequency in T2WI (12.0% vs 31.6%, p = 0.014), sharp lesion margins (14.7% vs 43.0%, p = 0.010), T2/fluid attenuated inversion recovery mismatch signs (22.7% vs 50.9%, p = 0.001), and subventricular zone involvement (64.0% vs 15.8%, p = 0.021) comparing patients in 1p/19q non-codeletion group. According to the results of receiver operating characteristic analysis, these features were observed to have certain diagnostic abilities, especially with regard to combination parameters, which had a high diagnostic capability, with an area under the curve of 0.848. CONCLUSION: Conventional MRI and CT features, which still represent the most convenient and widely used predictive method, might be a promising noninvasive predictor for differentiating between varied WHO grade II gliomas. Patients with calcification and T1 nonenhancement are more likely to be IDH-mutant. Moreover, patients with noncalcification, homogenous signal, sharp lesion margins, subventricular zone involvement on T2 and T2/fluid attenuated inversion recovery mismatch signs are more likely to be 1p/19q non-codeletion.

Hepatocyte high-mobility group box 1 protects against steatosis and cellular stress during high fat diet feeding.

BACKGROUND: Circulating high-mobility group box 1 (HMGB1) plays important roles in the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Intracellular HMGB1 is critical for the biology of hepatocytes. However, the intracellular role of HMGB1 in hepatocellular steatosis is unknown. Therefore, we aimed to investigate the role of hepatocyte-specific HMGB1 (HC-HMGB1) in development of hepatic steatosis. METHODS: Wild type (WT) C57BL/6 and HC-HMGB1-/- mice were fed high-fat diet (HFD) or low-fat diet (LFD) for up to 16 weeks. RESULTS: As expected, HMGB1 translocated from nuclear into cytoplasm and released into circulation after HFD treatment. HC-HMGB1 deficiency significantly reduced circulating HMGB1, suggesting that hepatocyte is a major source of circulating HMGB1 during NAFLD. Unexpectedly, HC-HMGB1 deficiency promoted rapid weight gain with enhanced hepatic fat deposition compared with WT at as early as 4 weeks after HFD treatment. Furthermore, there was no difference between WT and HC-HMGB1-/- mice in glucose tolerance, energy expenditure, liver damage or systemic inflammation. Interestingly, hepatic gene expression related to free fatty acid (FFA) ß-oxidation was significantly down-regulated in HC-HMGB1-/- mice compared with WT, and endoplasmic reticulum (ER) stress markers were significantly higher in livers of HC-HMGB1-/- mice. In vitro experiments using primary mouse hepatocytes showed absence of HMGB1 increased FFA-induced intracellular lipid accumulation, accompanied by increased ER-stress, significant downregulation of FFA ß-oxidation, and reduced oxidative phosphorylation. CONCLUSIONS: Our findings suggest that hepatocyte HMGB1 protects against dysregulated lipid metabolism via maintenance of ß-oxidation and prevention of ER stress. This represents a novel mechanism for HMGB1-regulation of hepatocellular steatosis, and suggests that stabilizing HMGB1 in hepatocytes may be effective strategies for prevention and treatment of NAFLD.

Notch signaling protects CD4 T cells from STING-mediated apoptosis during acute systemic inflammation.

Dysregulation of T cell apoptosis contributes to the pathogenesis of acute systemic inflammation-induced immunosuppression, as seen in sepsis and trauma. However, the regulatory mechanisms of T cell apoptosis are unclear. Activation of stimulator of interferon genes (STING) has been shown to induce T cell apoptosis. Notch was previously identified as the top negative regulator of STING in macrophages through a kinase inhibitor library screening. However, how Notch signaling regulates STING activation in T cells is unknown. Here, using a γ-secretase inhibitor to block Notch signaling, we found that Notch protected CD4 T cells from STING-mediated apoptosis during endotoxemia. Mechanistically, Notch intracellular domain (NICD) interacted with STING at the cyclic dinucleotide (CDN) binding domain and competed with CDN to inhibit STING activation. In conclusion, our data reveal a previously unidentified role of Notch in negative regulation of STING-mediated apoptosis in CD4 T cells.