Impact of cachexia on disease recurrence and survival outcomes in endometrial cancer patients.

Objective: Cancer cachexia is progressive weight loss due to muscle/adipose tissue wasting and inadequate intake that occurs in response to malignancy. It is an independent predictor of disease recurrence and reduced survival in several cancers. However, cachexia's relationship with gynecologic malignancy outcomes has only been examined in small studies with limited follow-up and inconsistent definitions of cachexia. This study investigated the impact of cachexia on disease recurrence and overall survival in high-risk endometrial carcinoma patients. Methods: This retrospective cohort study examined data from patients with high-risk non-metastatic primary endometrial carcinoma treated at a single institution from 2015 to 2020. Treatment for all subjects included total hysterectomy, surgical staging, pelvic external beam radiotherapy with or without adjuvant chemotherapy. Radiation planning CT datasets were used to measure skeletal musculature at the L3 vertebral level. Skeletal muscle index (SMI) was defined as total L3 skeletal muscle cross sectional area (cm2)/height2 (m2), and cachexia was defined based on SMI. Results: 55 patients were eligible for analysis. Several SMI thresholds were used to define cachexia, and analysis was performed for each definition. Kaplan-Meier and Cox-proportional hazards regression analysis yielded no significant reduction in overall survival (OS) or progression-free survival (PFS) in patients with cachexia, regardless of threshold chosen. However, 4 of 13 definitions of cachexia showed significantly improved OS in patients without cachexia, relative to those with cachexia. There were no significant differences in disease recurrence. Conclusions: Cachexia as defined in this study was not associated with poor outcomes in endometrial carcinoma patients based on OS, PFS, or disease recurrence.

MLKL promotes hepatocarcinogenesis through inhibition of AMPK-mediated autophagy.

The pseudokinase mixed lineage kinase domain-like (MLKL) is an essential component of the activation of the necroptotic pathway. Emerging evidence suggests that MLKL plays a key role in liver disease. However, how MLKL contributes to hepatocarcinogenesis has not been fully elucidated. Herein, we report that MLKL is upregulated in a diethylnitrosamine (DEN)-induced murine HCC model and is associated with human hepatocellular carcinomas. Hepatocyte-specific MLKL knockout suppresses the progression of hepatocarcinogenesis. Conversely, MLKL overexpression aggravates the initiation and progression of DEN-induced HCC. Mechanistic study reveals that deletion of MLKL significantly increases the activation of autophagy, thereby protecting against hepatocarcinogenesis. MLKL directly interacts with AMPKα1 and inhibits its activity independent of its necroptotic function. Mechanistically, MLKL serves as a bridging molecule between AMPKα1 and protein phosphatase 1B (PPM1B), thus enhancing the dephosphorylation of AMPKα1. Consistently, MLKL expression correlates negatively with AMPKα1 phosphorylation in HCC patients. Taken together, our findings highlight MLKL as a novel AMPK gatekeeper that plays key roles in inhibiting autophagy and driving hepatocarcinogenesis, suggesting that the MLKL-AMPKα1 axis is a potential therapeutic target for HCC.

Development and Validation of a Prostate Biopsy Risk Calculator in Black Men.

PURPOSE: We sought to develop and validate a prostate biopsy risk calculator for Black men and compare it with the Prostate Cancer Prevention Trial version 2.0, Prostate Biopsy Collaborative Group, and Kaiser Permanente Prostate Cancer Risk Calculators for the detection of Gleason Grade Group (GG) ≥ 2 prostate cancer (PCa). MATERIALS AND METHODS: We prospectively recruited 2 cohorts of men undergoing prostate biopsy from 5 facilities in Chicago. The first cohort was split into development (70%) and internal validation (30%) groups. The second was used for external validation. Iterative logistic regression was used to develop 3 models for predicting GG ≥ 2 PCa. Models were compared for discrimination using the C statistics, calibration curves, and net benefit curves. The frequency of unnecessary biopsies and missed PCas was compared at 10% and 30% risk thresholds. RESULTS: The 2 cohorts included 393 and 292 Black men, respectively. Our first model, Mistry-Sun 1, used serum PSA and prior negative biopsy. Mistry-Sun 2 added abnormal digital rectal exam (DRE) and an interaction term with abnormal DRE and PSA to Mistry-Sun 1. Mistry-Sun 3 added prostate volume, abnormal DRE, and age to Mistry-Sun 1. The C statistics were 0.74, 0.74, and 0.78, respectively, and were similar to or higher than established calculators. At the 10% and 30% risk thresholds our models had the fewest unnecessary biopsies and an appropriate proportion of missed GG ≥ 2 PCas. CONCLUSIONS: Tailoring a risk calculator to detect clinically significant PCa in Black men may improve biopsy decision-making and outcomes compared to tools developed in non-Black populations.

Pre-treatment inflamed tumor immune microenvironment is associated with FOLFIRINOX response in pancreatic cancer.

Introduction: Pancreatic adenocarcinoma (PDAC) is an aggressive tumor with limited response to both chemotherapy and immunotherapy. Pre-treatment tumor features within the tumor immune microenvironment (TiME) may influence treatment response. We hypothesized that the pre-treatment TiME composition differs between metastatic and primary lesions and would be associated with response to modified FOLFIRINOX (mFFX) or gemcitabine-based (Gem-based) therapy. Methods: Using RNAseq data from a cohort of treatment-naïve, advanced PDAC patients in the COMPASS trial, differential gene expression analysis of key immunomodulatory genes in were analyzed based on multiple parameters including tumor site, response to mFFX, and response to Gem-based treatment. The relative proportions of immune cell infiltration were defined using CIBERSORTx and Dirichlet regression. Results: 145 samples were included in the analysis; 83 received mFFX, 62 received Gem-based therapy. Metastatic liver samples had both increased macrophage (1.2 times more, p < 0.05) and increased eosinophil infiltration (1.4 times more, p < 0.05) compared to primary lesion samples. Further analysis of the specific macrophage phenotypes revealed an increased M2 macrophage fraction in the liver samples. The pre-treatment CD8 T-cell, dendritic cell, and neutrophil infiltration of metastatic samples were associated with therapy response to mFFX (p < 0.05), while mast cell infiltration was associated with response to Gem-based therapy (p < 0.05). Multiple immunoinhibitory genes such as ADORA2A, CSF1R, KDR/VEGFR2, LAG3, PDCD1LG2, and TGFB1 and immunostimulatory genes including C10orf54, CXCL12, and TNFSF14/LIGHT were significantly associated with worse survival in patients who received mFFX (p = 0.01). There were no immunomodulatory genes associated with survival in the Gem-based cohort. Discussion: Our evidence implies that essential differences in the PDAC TiME exist between primary and metastatic tumors and an inflamed pretreatment TiME is associated with mFFX response. Defining components of the PDAC TiME that influence therapy response will provide opportunities for targeted therapeutic strategies that may need to be accounted for in designing personalized therapy to improve outcomes.

Impact of genomic testing on urologists' treatment preference in favorable risk prostate cancer: A randomized trial.

INTRODUCTION: The Oncotype Dx Genomic Prostate Score (GPS) is a 17-gene relative expression assay that predicts adverse pathology at prostatectomy. We conducted a novel randomized controlled trial to assess the impact of GPS on urologist's treatment preference for favorable risk prostate cancer (PCa): active surveillance versus active treatment (i.e., prostatectomy/radiation). This is a secondary endpoint from the ENACT trial which recruited from three Chicago hospitals from 2016 to 2019. METHODS: Ten urologists along with men with very low to favorable-intermediate risk PCa were included in the study. Participants were randomly assigned to standardized counseling with or without GPS assay. The main outcome was urologists' preference for active treatment at Visit 2 by study arm (GPS versus Control). Multivariable best-fit binary logistic regressions were constructed to identify factors independently associated with urologists' treatment preference. RESULTS: Two hundred men (70% Black) were randomly assigned to either the Control (96) or GPS arm (104). At Visit 2, urologists' preference for prostatectomy/radiation almost doubled in the GPS arm to 29.3% (29) compared to 14.1% (13) in the Control arm (p = 0.01). Randomization to the GPS arm, intermediate NCCN risk level, and lower patient health literacy were predictors for urologists' preference for active treatment. DISCUSSION: Limitations included sample size and number of urologists. In this study, we found that GPS testing reduced urologists' likelihood to prefer active surveillance. CONCLUSIONS: These findings demonstrate how obtaining prognostic biomarkers that predict negative outcomes before treatment decision-making might influence urologists' preference for recommending aggressive therapy in men eligible for active surveillance.

A Bayesian framework for pathway-guided identification of cancer subgroups by integrating multiple types of genomic data.

In recent years, comprehensive cancer genomics platforms, such as The Cancer Genome Atlas (TCGA), provide access to an enormous amount of high throughput genomic datasets for each patient, including gene expression, DNA copy number alterations, DNA methylation, and somatic mutation. While the integration of these multi-omics datasets has the potential to provide novel insights that can lead to personalized medicine, most existing approaches only focus on gene-level analysis and lack the ability to facilitate biological findings at the pathway-level. In this article, we propose Bayes-InGRiD (Bayesian Integrative Genomics Robust iDentification of cancer subgroups), a novel pathway-guided Bayesian sparse latent factor model for the simultaneous identification of cancer patient subgroups (clustering) and key molecular features (variable selection) within a unified framework, based on the joint analysis of continuous, binary, and count data. By utilizing pathway (gene set) information, Bayes-InGRiD does not only enhance the accuracy and robustness of cancer patient subgroup and key molecular feature identification, but also promotes biological understanding and interpretation. Finally, to facilitate an efficient posterior sampling, an alternative Gibbs sampler for logistic and negative binomial models is proposed using Pólya-Gamma mixtures of normal to represent latent variables for binary and count data, which yields a conditionally Gaussian representation of the posterior. The R package "INGRID" implementing the proposed approach is currently available in our research group GitHub webpage (https://dongjunchung.github.io/INGRID/).

Position-Aware Relational Transformer for Knowledge Graph Embedding.

Although Transformer has achieved success in language and vision tasks, its capacity for knowledge graph (KG) embedding has not been fully exploited. Using the self-attention (SA) mechanism in Transformer to model the subject-relation-object triples in KGs suffers from training inconsistency as SA is invariant to the order of input tokens. As a result, it is unable to distinguish a (real) relation triple from its shuffled (fake) variants (e.g., object-relation-subject) and, thus, fails to capture the correct semantics. To cope with this issue, we propose a novel Transformer architecture, namely, for KG embedding. It incorporates relational compositions in entity representations to explicitly inject semantics and capture the role of an entity based on its position (subject or object) in a relation triple. The relational composition for a subject (or object) entity of a relation triple refers to an operator on the relation and the object (or subject). We borrow ideas from the typical translational and semantic-matching embedding techniques to design relational compositions. We carefully design a residual block to integrate relational compositions into SA and efficiently propagate the composed relational semantics layer by layer. We formally prove that the SA with relational compositions is able to distinguish the entity roles in different positions and correctly capture relational semantics. Extensive experiments and analyses on six benchmark datasets show that achieves state-of-the-art performance on both link prediction and entity alignment.

Marine ship instance segmentation by deep neural networks using a global and local attention (GALA) mechanism.

Marine ships are the transport vehicle in the ocean and instance segmentation of marine ships is an accurate and efficient analysis approach to achieve a quantitative understanding of marine ships, for example, their relative locations to other ships or obstacles. This relative spatial information is crucial for developing unmanned ships to avoid crashing. Visible light imaging, e.g. using our smartphones, is an efficient way to obtain images of marine ships, however, so far there is a lack of suitable open-source visible light datasets of marine ships, which could potentially slow down the development of unmanned ships. To address the problem of insufficient datasets, here we built two instance segmentation visible light datasets of marine ships, MariBoats and MariBoatsSubclass, which could facilitate the current research on instance segmentation of marine ships. Moreover, we applied several existing instance segmentation algorithms based on neural networks to analyze our datasets, but their performances were not satisfactory. To improve the segmentation performance of the existing models on our datasets, we proposed a global and local attention mechanism for neural network models to retain both the global location and semantic information of marine ships, resulting in an average segmentation improvement by 4.3% in terms of mean average precision. Therefore, the presented new datasets and the new attention mechanism will greatly advance the marine ship relevant research and applications.

Treatment decision-making among patients with metastatic prostate cancer: Impact of decision locus of control on functional outcomes and decision satisfaction.

BACKGROUND: Shared decision-making (SDM) for metastatic prostate cancer (mPC) engages patients in the decision-making process and may be associated with better outcomes relative to physician- or patient-directed decision-making. We assessed the association between decision locus of control (DLOC) and patient-reported quality of life (QOL), functional outcomes, and decision satisfaction among mPC patients. METHODS: After a clinic visit in which a treatment decision was made (baseline), mPC patients completed DLOC and QOL surveys. QOL was re-assessed at 2- and 4-months post-baseline. Mean scores for each QOL dimension (physical, emotional, cognitive, social, and role functioning) were compared by DLOC group using mixed effects models. Patient preferences for DLOC and provider communication techniques were similarly collected via survey. RESULTS: Median age of participants (N = 101) was 69 years (range: 49-92); most were White (80%) and married (82%). 62% reported using SDM. At baseline, there were no differences in QOL dimensions between DLOC groups. At 4 months, patient-directed (p = 0.01) and SDM (p = 0.03) were associated with better physical functioning than physician-directed decision-making, and there was an indication of potentially greater decision satisfaction among patients who reported patient-directed (p = 0.06) or SDM (p = 0.10). SDM was the most reported preferred DLOC. CONCLUSION: mPC patients reporting SDM had better physical functioning at 4 months than physician- or patient-directed decision-making, suggesting measurable benefit from patient involvement in decision-making. Future investigations of these associations in larger, more diverse populations can further clarify these previously unmeasured benefits of patient engagement in treatment decisions.

Brown adipose tissue involution associated with progressive restriction in progenitor competence.

Human brown adipose tissue (BAT) undergoes progressive involution. This involution process is not recapitulated in rodents, and the underlying mechanisms are poorly understood. Here we show that the interscapular BAT (iBAT) of rabbits whitens rapidly during early adulthood. The transcriptomic remodeling and identity switch of mature adipocytes are accompanied by loss of brown adipogenic competence of progenitors. Single-cell RNA sequencing reveals that rabbit and human iBAT progenitors highly express the FSTL1 gene. When iBAT involutes in rabbits, adipocyte progenitors reduce FSTL1 expression and are refractory to brown adipogenic recruitment. Conversely, FSTL1 is constitutively expressed in mouse iBAT to sustain WNT signaling and prevent involution. Progenitor incompetence and iBAT paucity can be induced in mice by genetic deletion of the Fstl1 gene or ablation of Fstl1+ progenitors. Our results highlight the hierarchy and dynamics of the BAT progenitor compartment and implicate the functional incompetence of FSTL1-expressing progenitors in BAT involution.

Treatment with soluble CD24 attenuates COVID-19-associated systemic immunopathology.

BACKGROUND: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19) through direct lysis of infected lung epithelial cells, which releases damage-associated molecular patterns and induces a pro-inflammatory cytokine milieu causing systemic inflammation. Anti-viral and anti-inflammatory agents have shown limited therapeutic efficacy. Soluble CD24 (CD24Fc) blunts the broad inflammatory response induced by damage-associated molecular patterns via binding to extracellular high mobility group box 1 and heat shock proteins, as well as regulating the downstream Siglec10-Src homology 2 domain-containing phosphatase 1 pathway. A recent randomized phase III trial evaluating CD24Fc for patients with severe COVID-19 (SAC-COVID; NCT04317040) demonstrated encouraging clinical efficacy. METHODS: Using a systems analytical approach, we studied peripheral blood samples obtained from patients enrolled at a single institution in the SAC-COVID trial to discern the impact of CD24Fc treatment on immune homeostasis. We performed high dimensional spectral flow cytometry and measured the levels of a broad array of cytokines and chemokines to discern the impact of CD24Fc treatment on immune homeostasis in patients with COVID-19. RESULTS: Twenty-two patients were enrolled, and the clinical characteristics from the CD24Fc vs. placebo groups were matched. Using high-content spectral flow cytometry and network-level analysis, we found that patients with severe COVID-19 had systemic hyper-activation of multiple cellular compartments, including CD8+ T cells, CD4+ T cells, and CD56+ natural killer cells. Treatment with CD24Fc blunted this systemic inflammation, inducing a return to homeostasis in NK and T cells without compromising the anti-Spike protein antibody response. CD24Fc significantly attenuated the systemic cytokine response and diminished the cytokine coexpression and network connectivity linked with COVID-19 severity and pathogenesis. CONCLUSIONS: Our data demonstrate that CD24Fc rapidly down-modulates systemic inflammation and restores immune homeostasis in SARS-CoV-2-infected individuals, supporting further development of CD24Fc as a novel therapeutic against severe COVID-19.

The interaction between PDCD4 and YB1 is critical for cervical cancer stemness and cisplatin resistance.

Cancer multidrug resistance (MDR) is existence in stem cell-like cancer cells characterized by stemness including high-proliferation and self-renewal. Programmed cell death 4 (PDCD4), as a proapoptotic gene, whether it engaged in cancer stemness and cisplatin resistance is still unknown. Here we showed that PDCD4 expressions in Hela/DDP (cisplatin resistance) cells were lower than in parental Hela cells. Moreover, the levels of drug resistance genes and typical stemness markers were markedly elevated in Hela/DDP cells. In vivo, xenograft tumor assay confirmed that knockdown of PDCD4 accelerated the grafted tumor growth. In vitro, colony formation and MTT assay demonstrated that PDCD4 overexpression inhibited cells proliferation in conditions with or without cisplatin. By contrast, PDCD4 deficiency provoked cell proliferation and cisplatin resistance. On mechanism, PDCD4 decreased the protein levels of pAKT and pYB1, accompanied by reduced MDR1 expression. Correspondingly, luciferase reporter assay showed PDCD4 regulated MDR1 promoter activity entirely relied on YB1. Furthermore, Ch-IP, GST-pulldown, and Co-IP assays provided novel evidence that PDCD4 could directly bind with YB1 by the nucleolar localization signal (NOLS) segment, causing the reduced YB1 binding into the MDR1 promoter region through blocking YB1 nucleus translocation, triggering the decreased MDR1 transcription. Taken together, PDCD4-pAKT-pYB1 forms the integrated molecular network to regulate MDR1 transcription during the process of stemness-associated cisplatin resistance.

TREATMENT WITH SOLUBLE CD24 ATTENUATES COVID-19-ASSOCIATED SYSTEMIC IMMUNOPATHOLOGY.

BACKGROUND: SARS-CoV-2 causes COVID-19 through direct lysis of infected lung epithelial cells, which releases damage-associated molecular patterns (DAMPs) and induces a pro-inflammatory cytokine milieu causing systemic inflammation. Anti-viral and anti-inflammatory agents have shown limited therapeutic efficacy. Soluble CD24 (CD24Fc) is able to blunt the broad inflammatory response induced by DAMPs in multiple models. A recent randomized phase III trial evaluating the impact of CD24Fc in patients with severe COVID-19 demonstrated encouraging clinical efficacy. METHODS: We studied peripheral blood samples obtained from patients enrolled at a single institution in the SAC-COVID trial (NCT04317040) collected before and after treatment with CD24Fc or placebo. We performed high dimensional spectral flow cytometry analysis of peripheral blood mononuclear cells and measured the levels of a broad array of cytokines and chemokines. A systems analytical approach was used to discern the impact of CD24Fc treatment on immune homeostasis in patients with COVID-19. FINDINGS: Twenty-two patients were enrolled, and the clinical characteristics from the CD24Fc vs. placebo groups were matched. Using high-content spectral flow cytometry and network-level analysis, we found systemic hyper-activation of multiple cellular compartments in the placebo group, including CD8+ T cells, CD4+ T cells, and CD56+ NK cells. By contrast, CD24Fc-treated patients demonstrated blunted systemic inflammation, with a return to homeostasis in both NK and T cells within days without compromising the ability of patients to mount an effective anti-Spike protein antibody response. A single dose of CD24Fc significantly attenuated induction of the systemic cytokine response, including expression of IL-10 and IL-15, and diminished the coexpression and network connectivity among extensive circulating inflammatory cytokines, the parameters associated with COVID-19 disease severity. INTERPRETATION: Our data demonstrates that CD24Fc treatment rapidly down-modulates systemic inflammation and restores immune homeostasis in SARS-CoV-2-infected individuals, supporting further development of CD24Fc as a novel therapeutic against severe COVID-19. FUNDING: NIH.

Quercetin inhibits invasion and angiogenesis of esophageal cancer cells.

BACKGROUND: Esophageal carcinoma has poor prognosis and novel therapies for esophageal carcinoma are urgently needed. Quercetin is a natural flavonoid compound that can be found in many foods. In this study, we investigated the effects of quercetin on invasion and angiogenesis of esophageal cancer cells. METHODS: Human esophageal cancer cell line Eca109 was treated with 5 µg/mL or 10 µg/mL of quercetin. Colony formation assay was performed. Cell migration and invasion were evaluated by wound healing and transwell assays, respectively. Human umbilical vein/vascular endothelium cells (CLR-1730) were treated with Eca109 conditioned medium, and the effects of quercetin on CLR-1730 were evaluated by wound healing and tube formation assays. Protein levels of VEGF-A, MMP9, and MMP2 were determined by Western blotting. RESULTS: The ability of colony forming in Eca109 was reduced with the administration of 10 µg/mL quercetin, but there was no difference between the 5 µg/mL quercetin group and control. The migration distance and the number of invasive cells were significantly reduced in the 10 µg/mL quercetin group. At the lower level of quercetin at 5 µg/mL, only the invasion of cells was significantly inhibited. In endothelial cells treated with Eca109 conditioned medium, cell migration and tube forming ability were suppressed. The decreased protein levels of VEGF-A, MMP9, and MMP2 were observed at the 10 µg/mL quercetin group. CONCLUSION: Quercetin suppressed the invasion and angiogenesis of esophageal cancer cells, and the effects were associated with the decreased expression of VEGF-A, MMP2, and MMP9.

Differential immune signatures in the tumor microenvironment are associated with colon cancer racial disparities.

BACKGROUND: Disparities in colon cancer (CC) outcomes may be due to a more aggressive phenotype in African American patients in the setting of a decreased tumor immunity, though the precise mechanism for this result has not been well elucidated. To explore the molecular factors underlying CC disparities, we compared the immunogenomic signatures of CC from African American and European American patients. METHODS: We identified all CC patients from the publicly available Cancer Genome Atlas for whom race and survival data are available. Immunophenotype signatures were established for African American and European American patients. Comparisons were made regarding survival and a multivariable linear regression model was created to determine the association of immune cellular components with race. Differential gene expression was also assessed. RESULTS: Of the 254 patients identified, 58 (23%) were African American and 196 (77%) were European American. African American patients had a decreased progression free survival (p = 0.04). Tumors from African American patients displayed a reduced fraction of macrophages and CD8+ T cells and an increased fraction of B cells compared with tumors from European Americans. Differences persisted when controlling for sex, age, and disease stage. Immunostimulatory and immunoinhibitory gene profiles including major histocompatibility complex expression differed by race. CONCLUSIONS: Differences in the tumor immune microenvironment of African American as compared to European American CC specimens may play a role in the survival differences between the groups. These differences may provide targeted therapeutic opportunities.

Testing for correlation between two time series using a parametric bootstrap.

We study the problem of determining if two time series are correlated in the mean and variance. Several test statistics, originally designed for determining the correlation between two mean processes or goodness-of-fit testing, are explored and formally introduced for determining cross-correlation in variance. Simulations demonstrate the theoretical asymptotic distribution can be ineffective in finite samples. Parametric bootstrapping is shown to be an effective tool in such an enterprise. A large simulation study is provided demonstrating the efficacy of the bootstrapping method. Lastly, an empirical example explores a correlation between the Standard & Poor's 500 index and the Euro/US dollar exchange rate while also demonstrating a level of robustness for the proposed method.

Successful Treatment of Pseudomembranous Colitis with Fecal Microbiota Transplantation - A Case Study on A Patient Rescued by Extracorporeal Cardiopulmonary Resuscitation After Cardiac Arrest.

BACKGROUND Pseudomembranous colitis (PMC) is an opportunistic, nosocomial infection caused by Clostridium difficile. CASE REPORT Here we described a patient who developed PMC during her recovery from cardiac arrest. A 16-year-old female high school student experienced sudden cardiac arrest. Spontaneous circulation was not returned by standard cardiopulmonary resuscitation. After her admission to the emergency unit, her cardiac function and neurologic function were finally resumed by extracorporeal cardiopulmonary resuscitation (ECPR); however, after 14 days, her recovery was complicated with excessive diarrhea and shock. Colonoscopy confirmed the diagnosis of PMC. Metronidazole and vancomycin were immediately administered; however, the treatment did not result in any improvement. Fecal microbiota transplantation was then performed, and after 4 transplantations, her diarrhea was significantly ameliorated. After hospital stay for 135 days, the patient was finally discharged with grade II brain function. She later recovered self-care ability in follow-up. CONCLUSIONS The patient suffered from a long-term gastrointestinal ischemia-hypoxia resulting from cardiac arrest. The use of broad-spectrum antibiotics in the later treatment led to refractory PMC, which was successfully managed by multiple fecal microbiota transplantation.

Semi-supervised identification of cancer subgroups using survival outcomes and overlapping grouping information.

Identification of cancer patient subgroups using high throughput genomic data is of critical importance to clinicians and scientists because it can offer opportunities for more personalized treatment and overlapping treatments of cancers. In spite of tremendous efforts, this problem still remains challenging because of low reproducibility and instability of identified cancer subgroups and molecular features. In order to address this challenge, we developed Integrative Genomics Robust iDentification of cancer subgroups (InGRiD), a statistical approach that integrates information from biological pathway databases with high-throughput genomic data to improve the robustness for identification and interpretation of molecularly-defined subgroups of cancer patients. We applied InGRiD to the gene expression data of high-grade serous ovarian cancer from The Cancer Genome Atlas and the Australian Ovarian Cancer Study. The results indicate clear benefits of the pathway-level approaches over the gene-level approaches. In addition, using the proposed InGRiD framework, we also investigate and address the issue of gene sharing among pathways, which often occurs in practice, to further facilitate biological interpretation of key molecular features associated with cancer progression. The R package "InGRiD" implementing the proposed approach is currently available in our research group GitHub webpage ( https://dongjunchung.github.io/INGRID/ ).

Cimicifuga foetida L. plus adefovir effectively inhibits the replication of hepatitis B virus in patients with chronic hepatitis B.

The aim of the present study was to assess the anti-hepatitis B virus (HBV) effect of Cimicifuga foetida L. (C. foetida) in the patients with chronic hepatitis B (CHB). A total of 60 randomly selected patients with CHB were recruited and divided into groups I and II. The patients in group I received a monotherapy of adefovir (ADV), and the patients in group II received a combination therapy of ADV and C. foetida for >48 weeks. Intrahepatic (IH) HBV covalently closed circular DNA (cccDNA), serum HBV DNA, hepatitis B surface antigen (HBsAg), alanine aminotransferase levels and serum interferon-γ (IFN-γ) and transforming growth factor-ß (TGF-ß) levels were quantified during the test. Following the treatment, a significant reduction of the median IH cccDNA level was identified in group II (P=0.017), but not in group I (P=0.05, and P=0.01 between the 2 groups), and a significant reduction of log10 HBsAg was identified in groups I (P=0.012) and II (P<0.0001, and P=0.20 between the 2 groups). A significant increase of the median serum IFN-γ level was found in group II (P=0.0005), but not in group I (P=0.06, and P=0.004 between the 2 groups), and a significant reduction of the median TGF-ß level was identified in groups I (P<0.0001) and II (P<0.0001, and P=0.002 between the 2 groups). A total of 24 patients in group I, and 27 patients in group II achieved a sustained virological response (P=0.0386), and 20 patients in group I and 24 in group II achieved hepatitis B e antigen seroclearance (P=0.0442). In conclusion, C. foetida can effectively inhibit HBV transcription and replication in the patients by stimulating the release of the inflammatory cytokines, such as IFN-γ.