Stabilizing Interlayer Repulsion in Layered Sodium-Ion Oxide Cathodes via Hierarchical Layer Modification.

Layered sodium-ion oxides hold considerable promise in achieving high-performance sodium-ion batteries. However, the notorious phase transformation during charging, attributed to increased O2-─O2- repulsion, results in substantial performance decay. Here, a hierarchical layer modification strategy is proposed to stabilize interlayer repulsion. During desodiation, migrated Li+ from the transition metal layer and anchored Ca2+ in sodium sites maintain the cationic content within the sodium layer. Meanwhile, partial oxygen substitution by fluorine and the involvement of oxygen in redox reactions increase the average valence of the oxygen layer. This sustained cation presence and elevated anion valence collectively mitigate increasing O2-─O2- repulsion during sodium extraction, enabling the Na0.61Ca0.05[Li0.1Ni0.23Mn0.67]O1.95F0.05 (NCLNMOF) cathode to retain a pure P2-type structure across a wide voltage range. Unexpected insights reveal the interplay between different doping elements: the robust Li─F bonds and Ca2+ steric effects suppressing Li+ loss. The NCLNMOF electrode exhibits 82.5% capacity retention after 1000 cycles and a high-rate capability of 94 mAh g-1 at 1600 mA g-1, demonstrating the efficacy of hierarchical layer modification for high-performance layered oxide cathodes.

Regulatory T and CXCR3+ Circulating Tfh Cells Concordantly Shape the Neutralizing Antibody Responses in Individuals Who Have Recovered from Mild COVID-19.

Regulatory T (Treg) cells are involved in the antiviral immune response in patients with coronavirus disease 2019 (COVID-19); however, whether Treg cells are involved in the neutralizing antibody (nAb) response remains unclear. Here, we found that individuals who recovered from mild but not severe COVID-19 had significantly greater frequencies of Treg cells and lower frequencies of CXCR3+ circulating T follicular helper (cTfh) cells than healthy controls. Furthermore, the frequencies of Treg and CXCR3+ cTfh cells were negatively and positively correlated with the nAb responses, respectively, and Treg cells was inversely associated with CXCR3+ cTfh cells in individuals who recovered from mild COVID-19 but not in those with severe disease. Mechanistically, Treg cells inhibited memory B-cell differentiation and antibody production by limiting the activation and proliferation of cTfh cells, especially CXCR3+ cTfh cells, and functional molecule expression. This study provides novel insight showing that mild COVID-19 elicits concerted nAb responses, which are shaped by both Treg and Tfh cells.

Analytical Validation of a Telomerase Reverse Transcriptase (TERT) Promoter Mutation Assay.

CONTEXT: Telomerase reverse transcriptase (TERT) promoter-mutated thyroid cancers are associated with a decreased rate of disease-free and disease-specific survival. High-quality analytical validation of a diagnostic test promotes confidence in the results that inform clinical decision-making. OBJECTIVE: This work aimed to demonstrate the analytical validation of the Afirma TERT promoter mutation assay. METHODS: TERT promoter C228T and C250T variant detection in genomic DNA (gDNA) was analyzed by assessing variable DNA input and the limit of detection (LOD) of variant allele frequency (VAF). The negative and positive percentage agreement (NPA and PPA) of the Afirma TERT test was examined against a reference primer pair as was the analytical specificity from potential interfering substances (RNA and blood gDNA). Further, the intrarun, interrun, and interlaboratory reproducibility of the assay were tested. RESULTS: The Afirma TERT test is tolerant to variation in DNA input amount (7-13 ng) and can detect expected positive TERT promoter variants down to 5% VAF LOD at 7 ng DNA input with greater than 95% sensitivity. Both NPA and PPA were 100% against the reference primer pair. The test remains accurate in the presence of 20% RNA or 80% blood gDNA for an average patient sample that typically has 30% VAF. The test also demonstrated a 100% confirmation rate when compared with an external next-generation sequencing-based reference assay executed in a non-Veracyte laboratory. CONCLUSION: The analytical robustness and reproducibility of the Afirma TERT test support its routine clinical use among thyroid nodules with indeterminate cytology that are Afirma Genomic Sequencing Classifier suspicious or among Bethesda V/VI nodules.

TOP2A modulates signaling via the AKT/mTOR pathway to promote ovarian cancer cell proliferation.

Ovarian cancer (OC) is a form of gynecological malignancy that is associated with worse patient outcomes than any other cancer of the female reproductive tract. Topoisomerase II α (TOP2A) is commonly regarded as an oncogene that is associated with malignant disease progression in a variety of cancers, its mechanistic functions in OC have yet to be firmly established. We explored the role of TOP2A in OC through online databases, clinical samples, in vitro and in vivo experiments. And initial analyses of public databases revealed high OC-related TOP2A expression in patient samples that was related to poorer prognosis. This was confirmed by clinical samples in which TOP2A expression was elevated in OC relative to healthy tissue. Kaplan-Meier analyses further suggested that higher TOP2A expression levels were correlated with worse prognosis in OC patients. In vitro, TOP2A knockdown resulted in the inhibition of OC cell proliferation, with cells entering G1 phase arrest and undergoing consequent apoptotic death. In rescue assays, TOP2A was confirmed to regulate cell proliferation and cell cycle through AKT/mTOR pathway activity. Mouse model experiments further affirmed the key role that TOP2A plays as a driver of OC cell proliferation. These data provide strong evidence supporting TOP2A as an oncogenic mediator and prognostic biomarker related to OC progression and poor outcomes. At the mechanistic level, TOP2A can control tumor cell growth via AKT/mTOR pathway modulation. These preliminary results provide a foundation for future research seeking to explore the utility of TOP2A inhibitor-based combination treatment regimens in platinum-resistant recurrent OC patients.

Oncological and reproductive outcomes of endometrial atypical hyperplasia and endometrial cancer patients undergoing conservative therapy with hysteroscopic resection: A systematic review and meta-analysis.

INTRODUCTION: Our objective was to conduct a systematic review and meta-analysis of studies evaluating the oncological and reproductive outcomes of patients with endometrial atypical hyperplasia (AH) and endometrioid endometrial cancer (EEC) undergoing conservative therapy with hysteroscopic resection (HR). MATERIAL AND METHODS: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement for systematic reviews and meta-analyses. The study strictly followed the methodological framework proposed by the Cochrane Handbook and was retrospectively registered in PROSPERO (CRD42023469986). Searches were conducted in PubMed, Embase, and the Cochrane Library, from inception to October 10, 2023. A checklist based on items of the Newcastle-Ottawa Scale and the Methodological Index for Non-randomized Studies was used for quality assessment. The primary end points for this meta-analysis were complete response (CR), pregnancy, and live birth rates following HR-based therapy in patients with EEC or AH. The secondary end point was the recurrence rate (RR). RESULTS: Twenty-one articles involving 407 patients with clinical stage IA, low or intermediate grade, EEC, and 444 patients with AH managed with HR-based conservative treatment were included for this systematic review. CR to HR-based conservative therapy was achieved in 88.6% of patients with EEC and 97.0% of patients with AH. Of these, 30.6% and 24.2%, respectively, had live births. The overall pooled disease RR was 18.3% and 10.8% in patients with EEC and AH, respectively. Further subset analyses revealed that EEC patients with body mass index (BMI) ≤28 kg/m2 had higher CR rates as well as higher chances of pregnancy and live birth (91.6% CR, 32.9% pregnancy, 31.1% live birth) compared with patients with BMI >28 kg/m2 (86.4% CR, 28.4% pregnancy, 23.0% live birth). The HR followed by oral progestogen subgroup had higher CR rates and higher chances of pregnancy and live birth (91.8% CR, 36.3% pregnancy, 28.2% live birth) than the HR followed by the levonorgestrel intrauterine system subgroup (82.5% CR, 25.3% pregnancy, 16.3% live birth). CONCLUSIONS: Hysteroscopic resection followed by progestins appears to be a promising choice for fertility-sparing treatment in young patients with AH and EEC, with effective and safe responses. The live birth rate remains to be improved by providing medical guidance and encouragement.

SARS-CoV-2 spike-reactive naïve B cells and pre-existing memory B cells contribute to antibody responses in unexposed individuals after vaccination.

Introduction: Since December 2019, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has presented considerable public health challenges. Multiple vaccines have been used to induce neutralizing antibodies (nAbs) and memory B-cell responses against the viral spike (S) glycoprotein, and many essential epitopes have been defined. Previous reports have identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-reactive naïve B cells and preexisting memory B cells in unexposed individuals. However, the role of these spike-reactive B cells in vaccine-induced immunity remains unknown. Methods: To elucidate the characteristics of preexisting SARS-CoV-2 S-reactive B cells as well as their maturation after antigen encounter, we assessed the relationship of spike-reactive B cells before and after vaccination in unexposed human individuals. We further characterized the sequence identity, targeting domain, broad-spectrum binding activity and neutralizing activity of these SARS-CoV-2 S-reactive B cells by isolating monoclonal antibodies (mAbs) from these B cells. Results: The frequencies of both spike-reactive naïve B cells and preexisting memory B cells before vaccination correlated with the frequencies of spike-reactive memory B cells after vaccination. Isolated mAbs from spike-reactive naïve B cells before vaccination had fewer somatic hypermutations (SHMs) than mAbs isolated from spike-reactive memory B cells before and after vaccination, but bound SARS-CoV-2 spike in vitro. Intriguingly, these germline-like mAbs possessed broad binding profiles for SARS-CoV-2 and its variants, although with low or no neutralizing capacity. According to tracking of the evolution of IGHV4-4/IGKV3-20 lineage antibodies from a single donor, the lineage underwent SHMs and developed increased binding activity after vaccination. Discussion: Our findings suggest that spike-reactive naïve B cells can be expanded and matured by vaccination and cocontribute to vaccine-elicited antibody responses with preexisting memory B cells. Selectively and precisely targeting spike-reactive B cells by rational antigen design may provide a novel strategy for next-generation SARS-CoV-2 vaccine development.

Compound AC1Q3QWB upregulates CDKN1A and SOX17 by interrupting the HOTAIR-EZH2 interaction and enhances the efficacy of tazemetostat in endometrial cancer.

Endometrial cancer (EC) is a common malignancy of the female reproductive system, with an escalating incidence. Recurrent/metastatic EC presents a poor prognosis. The interaction between the long non-coding RNA (lncRNA) HOTAIR and the polycomb repressive complex 2 (PRC2) induces abnormal silencing of tumor suppressor genes, exerting a pivotal role in tumorigenesis. We have previously discovered AC1Q3QWB (AQB), a small-molecule compound targeting HOTAIR-EZH2 interaction. In the present study, we unveil that AQB selectively hampers the interaction between HOTAIR and EZH2 within EC cells, thus reversing the epigenetic suppression of tumor suppressor genes. Furthermore, our findings demonstrate AQB's synergistic effect with tazemetostat (TAZ), an EZH2 inhibitor, significantly boosting the expression of CDKN1A and SOX17. This, in turn, induces cell cycle arrest and impedes EC cell proliferation, migration, and invasion. In vivo experiments further validate AQB's potential by enhancing TAZ's anti-tumor efficacy at lower doses. Our results advocate AQB, a recently discovered small-molecule inhibitor, as a promising agent against EC cells. When combined with TAZ, it offers a novel therapeutic strategy for EC treatment.

SARS-CoV-2 spike-specific TFH cells exhibit unique responses in infected and vaccinated individuals.

Long-term humoral immunity to SARS-CoV-2 is essential for preventing reinfection. The production of neutralizing antibody (nAb) and B cell differentiation are tightly regulated by T follicular help (TFH) cells. However, the longevity and functional role of TFH cell subsets in COVID-19 convalescents and vaccine recipients remain poorly defined. Here, we show that SARS-CoV-2 infection and inactivated vaccine elicited both spike-specific CXCR3+ TFH cell and CXCR3- TFH cell responses, which showed distinct response patterns. Spike-specific CXCR3+ TFH cells exhibit a dominant and more durable response than CXCR3- TFH cells that positively correlated with antibody responses. A third booster dose preferentially expands the spike-specific CXCR3+ TFH cell subset induced by two doses of inactivated vaccine, contributing to antibody maturation and potency. Functionally, spike-specific CXCR3+ TFH cells have a greater ability to induce spike-specific antibody secreting cells (ASCs) differentiation compared to spike-specific CXCR3- TFH cells. In conclusion, the persistent and functional role of spike-specific CXCR3+ TFH cells following SARS-CoV-2 infection and vaccination may play an important role in antibody maintenance and recall response, thereby conferring long-term protection. The findings from this study will inform the development of SARS-CoV-2 vaccines aiming to induce long-term protective immune memory.

CCNE1 is a predictive and immunotherapeutic indicator in various cancers including UCEC: a pan-cancer analysis.

BACKGROUND: CCNE1 plays an important oncogenic role in several tumors, especially high-stage serous ovarian cancer and endometrial cancer. Nevertheless, the fundamental function of CCNE1 has not been explored in multiple cancers. Therefore, bioinformatics analyses of pan-cancer datasets were carried out to explore how CCNE1 regulates tumorigenesis. METHODS: A variety of online tools and cancer databases, including GEPIA2, SangerBox, LinkedOmics and cBioPortal, were applied to investigate the expression of CCNE1 across cancers. The pan-cancer datasets were used to search for links between CCNE1 expression and prognosis, DNA methylation, m6A level, genetic alterations, CCNE1-related genes, and tumor immunity. We verified that CCNE1 has biological functions in UCEC cell lines using CCK-8, EdU, and Transwell assays. RESULTS: In patients with different tumor types, a high mRNA expression level of CCNE1 was related to a poor prognosis. Genes related to CCNE1 were connected to the cell cycle, metabolism, and DNA damage repair, according to GO and KEGG enrichment analyses. Genetic alterations of CCNE1, including duplications and deep mutations, have been observed in various cancers. Immune analysis revealed that CCNE1 had a strong correlation with TMB, MSI, neoantigen, and ICP in a variety of tumor types, and this correlation may have an impact on the sensitivity of various cancers to immunotherapy. CCK-8, EdU and Transwell assays suggested that CCNE1 knockdown can suppress UCEC cell proliferation, migration and invasion. CONCLUSION: Our study demonstrated that CCNE1 is upregulated in multiple cancers in the TCGA database and may be a promising predictive biomarker for the immunotherapy response in some types of cancers. Moreover, CCNE1 knockdown can suppress the proliferation, migration and invasion of UCEC cells.

Real-World Performance of the Afirma Genomic Sequencing Classifier (GSC)-A Meta-analysis.

CONTEXT: The Afirma® GSC aids in risk stratifying indeterminate thyroid nodule cytology (ITN). The 2018 GSC validation study (VS) reported a sensitivity (SN) of 91%, specificity (SP) of 68%, positive predictive value (PPV) of 47%, and negative predictive value (NPV) of 96%. Since then, 13 independent real-world (RW) postvalidation studies have been published. OBJECTIVE: This study's objective is to compare the RW GSC performance to the VS metrics. METHODS: Rules and assumptions applying to this analysis include: (1) At least 1 patient with molecular benign results must have surgery for that study to be included in SN, SP, and NPV analyses. (2) Molecular benign results without surgical histology are considered true negatives (TN) (as are molecular benign results with benign surgical histology). (3) Unoperated patients with suspicious results are either excluded from analysis (observed PPV [oPPV] and observed SP [oSP]) or assumed histology negatives (false positives; conservative PPV [cPPV] and conservative SP [cSP]) 4. Noninvasive follicular thyroid neoplasm with papillary-like nuclear features is considered malignant. RESULTS: In RW studies, the GSC demonstrates a SN, oSP, oPPV, and NPV of 97%, 88%, 65%, 99% respectively, and conservative RW performance showed cSP of 80% and cPPV of 49%, all significantly higher than the VS except for SN and cPPV. There was also a higher benign call rate (BCR) of 67% in RW studies compared to 54% in the VS (P < 0.05). CONCLUSION: RW data for the Afirma GSC demonstrates significantly better oSP and oPPV performance than the VS, indicating an increased yield of cancers for resected GSC suspicious nodules. The higher BCR likely increases the overall rate of clinical observation in lieu of surgery.

Indoor Passive Visual Positioning by CNN-Based Pedestrian Detection.

Indoor positioning applications are developing at a rapid pace; active visual positioning is one method that is applicable to mobile platforms. Other methods include Wi-Fi, CSI, and PDR approaches; however, their positioning accuracy usually cannot achieve the positioning performance of the active visual method. Active visual users, however, must take a photo to obtain location information, raising confidentiality and privacy issues. To address these concerns, we propose a solution for passive visual positioning based on pedestrian detection and projection transformation. This method consists of three steps: pretreatment, pedestrian detection, and pose estimation. Pretreatment includes camera calibration and camera installation. In pedestrian detection, features are extracted by deep convolutional neural networks using neighboring frame detection results and the map information as the region of interest attention model (RIAM). Pose estimation computes accurate localization results through projection transformation (PT). This system relies on security cameras installed in non-private areas so that pedestrians do not have to take photos. Experiments were conducted in a hall about 100 square meters in size, with 41 test-points for the localization experiment. The results show that the positioning error was 0.48 m (RMSE) and the 90% error was 0.73 m. Therefore, the proposed passive visual method delivers high positioning performance.

Pan-cancer analysis combined with experiments predicts CTHRC1 as a therapeutic target for human cancers.

BACKGROUND: The function of collagen triple helix repeat containing 1 (CTHRC1) as an oncogene has been reported in a growing number of publications. Bioinformatics methods represent a beneficial approach to examine the mechanism and function of the CTHRC1 gene in the disease process of cancers from a pan-cancer perspective. METHODS: In this study, using the online databases UCSC, NCBI, HPA, TIMER2, Oncomine, GEPIA, UALCAN, cBioPortal, COSMIC, MEXPRESS, STRING, CCLE, LinkedOmics, GTEx, TCGA, CGGA, and SangerBox, we focused on the relationship between CTHRC1 and tumorigenesis, progression, methylation, immunity, and prognosis. qPCR was used to detect CTHRC1 expression in glioma tissues and cell lines. RESULTS: The pan-cancer analysis showed that CTHRC1 was overexpressed in most tumors, and a significant correlation was observed between CTHRC1 expression and the prognosis of patients with cancer. CTHRC1 genetic alterations occur in diverse tumors and are associated with tumor progression. Levels of CTHRC1 promoter methylation were decreased in most cancer tissues compared with normal tissues. In addition, CTHRC1 coordinated the activity of ICP genes through diverse signal transduction pathways, was also associated with immune cell infiltration and the tumor microenvironment, and potentially represented a promising immunotherapy target. We identified CTHRC1-related genes across cancers using the GEPIA2 tool. The single-gene GO analysis of CTHRC1 across cancers showed that it was involved in some signaling pathways and biological processes, such as the Wnt signaling pathway, cell migration, and positive regulation of protein binding. The expression and function of CTHRC1 were also further verified in glioma tissues and cell lines. CONCLUSIONS: CTHRC1 is overexpressed in various cancer types and functions as an important oncogene that may promote tumorigenesis and development through different mechanisms. CTHRC1 may represent an important therapeutic target for human cancers.

Pan-cancer evaluation of gene expression and somatic alteration data for cancer prognosis prediction.

BACKGROUND: Over the past decades, approaches for diagnosing and treating cancer have seen significant improvement. However, the variability of patient and tumor characteristics has limited progress on methods for prognosis prediction. The development of high-throughput omics technologies now provides multiple approaches for characterizing tumors. Although a large number of published studies have focused on integration of multi-omics data and use of pathway-level models for cancer prognosis prediction, there still exists a gap of knowledge regarding the prognostic landscape across multi-omics data for multiple cancer types using both gene-level and pathway-level predictors. METHODS: In this study, we systematically evaluated three often available types of omics data (gene expression, copy number variation and somatic point mutation) covering both DNA-level and RNA-level features. We evaluated the landscape of predictive performance of these three omics modalities for 33 cancer types in the TCGA using a Lasso or Group Lasso-penalized Cox model and either gene or pathway level predictors. RESULTS: We constructed the prognostic landscape using three types of omics data for 33 cancer types on both the gene and pathway levels. Based on this landscape, we found that predictive performance is cancer type dependent and we also highlighted the cancer types and omics modalities that support the most accurate prognostic models. In general, models estimated on gene expression data provide the best predictive performance on either gene or pathway level and adding copy number variation or somatic point mutation data to gene expression data does not improve predictive performance, with some exceptional cohorts including low grade glioma and thyroid cancer. In general, pathway-level models have better interpretative performance, higher stability and smaller model size across multiple cancer types and omics data types relative to gene-level models. CONCLUSIONS: Based on this landscape and comprehensively comparison, models estimated on gene expression data provide the best predictive performance on either gene or pathway level. Pathway-level models have better interpretative performance, higher stability and smaller model size relative to gene-level models.

The regulatory network for petal anthocyanin pigmentation is shaped by the MYB5a/NEGAN transcription factor in Mimulus.

Much of the visual diversity of angiosperms is due to the frequent evolution of novel pigmentation patterns in flowers. The gene network responsible for anthocyanin pigmentation, in particular, has become a model for investigating how genetic changes give rise to phenotypic innovation. In the monkeyflower genus Mimulus, an evolutionarily recent gain of petal lobe anthocyanin pigmentation in M. luteus var. variegatus was previously mapped to genomic region pla2. Here, we use sequence and expression analysis, followed by transgenic manipulation of gene expression, to identify MYB5a-orthologous to the NEGAN transcriptional activator from M. lewisii-as the gene responsible for the transition to anthocyanin-pigmented petals in M. l. variegatus. In other monkeyflower taxa, MYB5a/NEGAN is part of a reaction-diffusion network that produces semi-repeating spotting patterns, such as the array of spots in the nectar guides of both M. lewisii and M. guttatus. Its co-option for the evolution of an apparently non-patterned trait-the solid petal lobe pigmentation of M. l. variegatus-illustrates how reaction-diffusion can contribute to evolutionary novelty in non-obvious ways. Transcriptome sequencing of a MYB5a RNAi line of M. l. variegatus reveals that this genetically simple change, which we hypothesize to be a regulatory mutation in cis to MYB5a, has cascading effects on gene expression, not only on the enzyme-encoding genes traditionally thought of as the targets of MYB5a but also on all of its known partners in the anthocyanin regulatory network.

Cancer prognosis prediction using somatic point mutation and copy number variation data: a comparison of gene-level and pathway-based models.

BACKGROUND: Genomic profiling of solid human tumors by projects such as The Cancer Genome Atlas (TCGA) has provided important information regarding the somatic alterations that drive cancer progression and patient survival. Although researchers have successfully leveraged TCGA data to build prognostic models, most efforts have focused on specific cancer types and a targeted set of gene-level predictors. Less is known about the prognostic ability of pathway-level variables in a pan-cancer setting. To address these limitations, we systematically evaluated and compared the prognostic ability of somatic point mutation (SPM) and copy number variation (CNV) data, gene-level and pathway-level models for a diverse set of TCGA cancer types and predictive modeling approaches. RESULTS: We evaluated gene-level and pathway-level penalized Cox proportional hazards models using SPM and CNV data for 29 different TCGA cohorts. We measured predictive accuracy as the concordance index for predicting survival outcomes. Our comprehensive analysis suggests that the use of pathway-level predictors did not offer superior predictive power relative to gene-level models for all cancer types but had the advantages of robustness and parsimony. We identified a set of cohorts for which somatic alterations could not predict prognosis, and a unique cohort LGG, for which SPM data was more predictive than CNV data and the predictive accuracy is good for all model types. We found that the pathway-level predictors provide superior interpretative value and that there is often a serious collinearity issue for the gene-level models while pathway-level models avoided this issue. CONCLUSION: Our comprehensive analysis suggests that when using somatic alterations data for cancer prognosis prediction, pathway-level models are more interpretable, stable and parsimonious compared to gene-level models. Pathway-level models also avoid the issue of collinearity, which can be serious for gene-level somatic alterations. The prognostic power of somatic alterations is highly variable across different cancer types and we have identified a set of cohorts for which somatic alterations could not predict prognosis. In general, CNV data predicts prognosis better than SPM data with the exception of the LGG cohort.

Comparison of pathway and gene-level models for cancer prognosis prediction.

BACKGROUND: Cancer prognosis prediction is valuable for patients and clinicians because it allows them to appropriately manage care. A promising direction for improving the performance and interpretation of expression-based predictive models involves the aggregation of gene-level data into biological pathways. While many studies have used pathway-level predictors for cancer survival analysis, a comprehensive comparison of pathway-level and gene-level prognostic models has not been performed. To address this gap, we characterized the performance of penalized Cox proportional hazard models built using either pathway- or gene-level predictors for the cancers profiled in The Cancer Genome Atlas (TCGA) and pathways from the Molecular Signatures Database (MSigDB). RESULTS: When analyzing TCGA data, we found that pathway-level models are more parsimonious, more robust, more computationally efficient and easier to interpret than gene-level models with similar predictive performance. For example, both pathway-level and gene-level models have an average Cox concordance index of ~ 0.85 for the TCGA glioma cohort, however, the gene-level model has twice as many predictors on average, the predictor composition is less stable across cross-validation folds and estimation takes 40 times as long as compared to the pathway-level model. When the complex correlation structure of the data is broken by permutation, the pathway-level model has greater predictive performance while still retaining superior interpretative power, robustness, parsimony and computational efficiency relative to the gene-level models. For example, the average concordance index of the pathway-level model increases to 0.88 while the gene-level model falls to 0.56 for the TCGA glioma cohort using survival times simulated from uncorrelated gene expression data. CONCLUSION: The results of this study show that when the correlations among gene expression values are low, pathway-level analyses can yield better predictive performance, greater interpretative power, more robust models and less computational cost relative to a gene-level model. When correlations among genes are high, a pathway-level analysis provides equivalent predictive power compared to a gene-level analysis while retaining the advantages of interpretability, robustness and computational efficiency.

Mixed-gas CH4/CO2/CO detection based on linear variable optical filter and thermopile detector array.

This paper presents the design, fabrication, and characterization of a middle-infrared (MIR) linear variable optical filter (LVOF) and thermopile detectors that will be used in a miniaturized mixed gas detector for CH4/CO2/CO measurement. The LVOF was designed as a tapered-cavity Fabry-Pérot optical filter, which can transform the MIR continuous spectrum into multiple narrow band-pass spectra with peak wavelength in linear variation. Multi-layer dielectric structures were used to fabricate the Bragg reflectors on the both sides of tapered cavity as well as the antireflective film combined with the function of out-of-band rejection. The uncooled thermopile detectors were designed and fabricated as a multiple-thermocouple suspension structure using micro-electro-mechanical system technology. Experimentally, the LVOF exhibits a mean full-width-at-half-maximum of 400 nm and mean peak transmittance of 70% at the wavelength range of 2.3~5 µm. The thermopile detectors exhibit a responsivity of 146 µV/°C at the condition of room temperature. It is demonstrated that the detectors can achieve the quantification and identification of CH4/CO2/CO mixed gas.

Brain metabonomics study of the antidepressant-like effect of Xiaoyaosan on the CUMS-depression rats by 1H NMR analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Xiaoyaosan (XYS), a famous TCM prescription with a long history of clinical use for relieving a wide variety of depression symptoms, consists of Radix Bupleuri (Bupleurum chinense DC.), Radix Angelicae Sinensis (Angelica sinensis (Oliv.) Diels), Radix PaeoniaeAlba (Paeonia lactiflora Pall.), Rhizoma Atractylodis Macrocepha lae (Atractylodes macrocephala Koidz.), Poria (Poria cocos (Schw.)Wolf), Radix Glycyrrhizae (Glycyrrhiza uralensis Fisch.), Herba Menthae Haplocalycis (Mentha haplocalyx Briq.), and Rhizoma Zin-giberis Recens (Zingiber officinale Rosc.). AIM OF THE STUDY: We aimed to characterize the diversity and variation of two kinds metabolites of brain, i.e. aqueous and lipophilic metabolites, gaining comprehensive insights into the metabolic processes of depression-like behavior, and to reveal the mechanisms of antidepressant-like effects of XYS. MATERIALS AND METHODS: We first established a CUMS (Chronic Unpredictable Mild Stress)-induced depression-like behavior model. We then extracted both aqueous and lipophilic metabolites of rat brains by a two-phase extraction method, which were subsequently characterized by two differential sequences of 1H nuclear magnetic resonance (NMR). Multivariate analysis including Principal Components Analysis (PCA) and Orthogonal Partial Least Squares-Discriminate Analysis (OPLS-DA) was applied. RESULTS: Metabolic profiling by PCA indicated that XYS significantly reversed the metabolic perturbation caused by CUMS. OPLS-DA showed a total of 15 metabolites including 6 lipophilic and 9 aqueous metabolites was screened as potential biomarkers involved in CUMS-induced depression-like behavior. On top of this, five pathways including (1)D-glutamine and D-glutamate metabolism, (2) valine, leucine and isoleucine biosynthesis, (3) alanine, aspartate and glutamate metabolism, (4) taurine and hypotaurine metabolism and (5) arginine and proline metabolism were recognized as the most influenced pathways associated with the process of CUMS-induced depression-like behavior. Notably, XYS significantly reversed abnormality of 5 aqueous and 4 lipophilic metabolites to normal, suggesting that XYS synergistically mediated abnormalities of multiple pathways (1), (3), (4) and (5). CONCLUSIONS: It is the first report to investigate the antidepressant-like effects and underlying mechanisms of XYS from the perspective of brain metabolites. In a broad sense, this study brings novel and valuable insights to evaluate the efficacy of traditional Chinese medicine (TCM), to interpret mechanisms, and to provide the theoretical basis for further research on therapeutic mechanisms in clinical practice.

Association of Tongue Bacterial Flora and Subtypes of Liver-Fire Hyperactivity Syndrome in Hypertensive Patients.

Structural changes in symbiotic human microorganisms can affect host phenotype. Liver-fire hyperactivity syndrome (LFHS) presents as bitter taste, halitosis, xerostomia, odontalgia, and other oral symptoms. LFHS is associated with hypertension (EH). In this study, tongue flora was analyzed to further understand the intrinsic relationship between tongue flora and LFHS. Samples of tongue coating, from 16 patients with EH-LFHS, 16 with EH-non-LFHS, and 16 controls, were obtained; then, 16S rRNA variable (V3-V4) regions were amplified and sequenced by MiSeq PE300 Sequencing. Tag clustering and Operational Taxonomic Units (OTUs) abundance analysis were used to compare the OTU sequence with the 16S database. The species were classified, and diversity and structure of the bacterial flora were compared between the three groups. Alpha diversity analysis, including Observed Species index and Chao index, indicated significantly higher richness of species in patients with EH-LFHS (p < 0.05). Higher phylogenetic diversity, in patients with EH-non-LFHS, indicates greater differences in evolutionary history than in patients with EH-LFHS. Streptococcus, Rothia, Neisseria, and Sphingomonas were the most prevalent in patients with EH-LFHS, differed from the other two groups. This indicates that richer bacterial diversity, and structure associated with EH-LFHS, may affect the occurrence, development, and outcome of hypertension and syndrome subtypes recognized by TCM.