Protective autophagy enhances antistress ability through AMPK/ULK1 signaling pathway in human immortalized keratinocytes.

Keratinocytes, located in the outermost layer of human skin, are pivotal cells to resist environmental damage. Cellular autophagy plays a critical role in eliminating damaged organelles and maintaining skin cell homeostasis. Low-dose 5-Aminolevulinic acid photodynamic therapy (ALA-PDT) has been demonstrated to enhance skin's antistress ability; however, the regulatory mechanisms of autophagy in keratinocytes remain unclear. In this study, we treated immortalized human keratinocytes (HaCaT cells) with low-dose ALA-PDT (0.5 mmol/L, 3 J/cm2). Through RNA-sequencing analysis, we identified that low-dose ALA-PDT modulated autophagy-related pathways in keratinocytes and pinpointed Unc-51-like kinase 1 (ULK1) as a key gene involved. Western blot results revealed that low-dose ALA-PDT treatment upregulated the expression of autophagy-related proteins Beclin-1 and LC3-II/LC3-I ratio. Notably, low-dose ALA-PDT regulated autophagy by inducing an appropriate level of reactive oxygen species (ROS), transiently reducing mitochondrial membrane potential, and decreasing adenosine triphosphate production; all these processes functioned on the AMP-activated protein kinase (AMPK)/ULK1 pathway to activate autophagy. Finally, we simulated external environmental damage using ultraviolet B (UVB) at a dose of 60 mJ/cm2 and observed that low-dose ALA-PDT mitigated UVB-induced cell apoptosis; however, this protective effect was reversed when using the autophagy inhibitor 3-methyladenine. Overall, these findings highlight how low-dose ALA-PDT enhances antistress ability in HaCaT cells through controlling ROS generation and activating the AMPK/ULK1 pathway to arouse cellular autophagy.

Cognitive impairment in Alzheimer's disease FAD4T mouse model: Synaptic loss facilitated by activated microglia via C1qA.

Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disorder characterized by cognitive dysfunction. The connection between neuroinflammation and abnormal synaptic function in AD is recognized, but the underlying mechanisms remain unclear. In this study, we utilized a mouse model of AD, FAD4T mice aged 6-7 months, to investigate the molecular changes affecting cognitive impairment. Behavior tests showed that FAD4T mice exhibited impaired spatial memory compared with their wild-type littermates. Immunofluorescence staining revealed the presence of Aß plaques and abnormal glial cell activation as well as changes in microglial morphology in the cortex and hippocampus of FAD4T mice. Synaptic function was impaired in FAD4T mice. Patch clamp recordings of hippocampal neurons revealed reduced amplitude of miniature excitatory postsynaptic currents. Additionally, Golgi staining showed decreased dendritic spine density in the cortex and hippocampus of FAD4T mice, indicating aberrant synapse morphology. Moreover, hippocampal PSD-95 and NMDAR1 protein levels decreased in FAD4T mice. RNA-seq analysis revealed elevated expression of immune system and proinflammatory genes, including increased C1qA protein and mRNA levels, as well as higher expression of TNF-α and IL-18. Taken together, our findings suggest that excessive microglia activation mediated by complement factor C1qA may contribute to aberrant synaptic pruning, resulting in synapse loss and disrupted synaptic transmission, ultimately leading to AD pathogenesis and behavioral impairments in the FAD4T mouse model. Our study provides valuable insights into the underlying mechanisms of cognitive impairments and preliminarily explores a potentially effective treatment approach targeting on C1qA for AD.

Phase I/IIa Trial in Advanced Pancreatic Ductal Adenocarcinoma Treated with Cytotoxic Drug-Packaged, EGFR-Targeted Nanocells and Glycolipid-Packaged Nanocells.

PURPOSE: We assessed the safety and efficacy of an EGFR-targeted, super-cytotoxic drug, PNU-159682-packaged nanocells with α-galactosyl ceramide-packaged nanocells (E-EDV-D682/GC) in patients with advanced pancreatic ductal adenocarcinoma (PDAC) who had exhausted all treatment options. PATIENTS AND METHODS: ENG9 was a first-in-man, single-arm, open-label, phase I/IIa, dose-escalation clinical trial. Eligible patients had advanced PDAC, Eastern Cooperative Oncology Group status 0 to 1, and failed all treatments. Primary endpoints were safety and overall survival (OS). RESULTS: Of 25 enrolled patients, seven were withdrawn due to rapidly progressive disease and one patient withdrew consent. All 25 patients were assessed for toxicity, 24 patients were assessed for OS, which was also assessed for 17 patients completing one treatment cycle [evaluable subset (ES)]. Nineteen patients (76.0%) experienced at least one treatment-related adverse event (graded 1 to 2) resolving within hours. There were no safety concerns, dose reductions, patient withdrawal, or treatment-related deaths.Median OS (mOS) was 4.4 months; however, mOS of the 17 ES patients was 6.9 months [208 days; range, 83-591 days; 95.0% confidence interval (CI), 5.6-10.3 months] and mOS of seven patients who did not complete one cycle was 1.8 months (54 days; range, 21-72; 95.0% CI, 1.2-2.2 months). Of the ES, 47.1% achieved stable disease and one partial response. Ten subjects in the ES survived over 6 months, the longest 19.7 months. During treatments, 82.0% of the ES maintained stable weight. CONCLUSIONS: E-EDV-D682/GC provided significant OS, minimal side effects, and weight stabilization in patients with advanced PDAC. Advanced PDAC can be safely treated with super-cytotoxic drugs via EnGeneIC Dream Vectors to overcome multidrug resistance.

P2Y12 receptor mediates apoptosis and demyelination to affect functional recovery in mice with spinal cord injury.

Among diseases of the central nervous system (CNS), spinal cord injury (SCI) has a high fatality rate. It has been proven that P2Y G protein-coupled purinergic receptors have a neuroprotective role in apoptosis and regeneration inside the damaged spinal cord. The P2Y12 receptor (P2Y12R) has recently been linked to peripheral neuropathy and stroke. However, the role of P2Y12R after SCI remains unclear. Our study randomly divided C57BL/6J female mice into 3 groups: Sham+DMSO, SCI+DMSO, and SCI+MRS2395. MRS2395 as a P2Y12R inhibitor was intraperitoneally injected at a dose of 1.5 mg/kg once daily for 7 days. We showed that the P2Y12R was markedly activated after injury, and it was double labeled with the microglial and neuron. Behavioral tests were employed to assess motor function recovery. By using immunofluorescence staining, the NeuN expression level was detected. The morphology of neurons was observed by hematoxylin-eosin and Nissl staining. P2Y12R, Bax, GFAP, PCNA and calbindin expression levels were detected using Western blot. Meanwhile, mitochondria and myelin sheath were observed by transmission electron microscopy (TEM). Our findings demonstrated that MRS2395 significantly enhanced motor function induced by SCI and that was used to alleviate apoptosis and astrocyte scarring. NeuN positive cells in the SCI group were lower than in the therapy group, although Bax, GFAP, PCNA and calbindin expression levels were considerably higher. Moreover, following MRS2395 therapy, the histological damage was reversed. A notable improvement in myelin sheath and mitochondrial morphology was seen in the therapy group. Together, our findings indicate that activation of P2Y12R in damaged spinal cord may be a critical event and suggest that inhibition of P2Y12R might be a feasible therapeutic strategy for treating SCI.

Single-cell characterization of macrophages in uveal melanoma uncovers transcriptionally heterogeneous subsets conferring poor prognosis and aggressive behavior.

Uveal melanoma (UM) is the most frequent primary intraocular malignancy with high metastatic potential and poor prognosis. Macrophages represent one of the most abundant infiltrating immune cells with diverse functions in cancers. However, the cellular heterogeneity and functional diversity of macrophages in UM remain largely unexplored. In this study, we analyzed 63,264 single-cell transcriptomes from 11 UM patients and identified four transcriptionally distinct macrophage subsets (termed MΦ-C1 to MΦ-C4). Among them, we found that MΦ-C4 exhibited relatively low expression of both M1 and M2 signature genes, loss of inflammatory pathways and antigen presentation, instead demonstrating enhanced signaling for proliferation, mitochondrial functions and metabolism. We quantified the infiltration abundance of MΦ-C4 from single-cell and bulk transcriptomes across five cohorts and found that increased MΦ-C4 infiltration was relevant to aggressive behaviors and may serve as an independent prognostic indicator for poor outcomes. We propose a novel subtyping scheme based on macrophages by integrating the transcriptional signatures of MΦ-C4 and machine learning to stratify patients into MΦ-C4-enriched or MΦ-C4-depleted subtypes. These two subtypes showed significantly different clinical outcomes and were validated through bulk RNA sequencing and immunofluorescence assays in both public multicenter cohorts and our in-house cohort. Following further translational investigation, our findings highlight a potential therapeutic strategy of targeting macrophage subsets to control metastatic disease and consistently improve the outcome of patients with UM.

Upregulation of SLC12A3 and SLC12A9 Mediated by the HCP5/miR-140-5p Axis Confers Aggressiveness and Unfavorable Prognosis in Uveal Melanoma.

Perturbation of solute carriers (SLCs) has been implicated in metabolic disorders and cancer, highlighting the potential for drug discovery and therapeutic opportunities. However, there is relatively little exploration of the clinical relevance and potential molecular mechanisms underlying the role of the SLC12 family in uveal melanoma (UVM). Here, we performed an integrative multiomics analysis of the SLC12 family in multicenter UVM datasets and found that high expression of SLC12A3 and SLC12A9 was associated with unfavorable prognosis. Moreover, SLC12A3 and SLC12A9 were highly expressed in UVM in vivo. We experimentally characterized the roles of these proteins in tumorigenesis in vitro and explored their association with the prognosis of UVM. Lastly, we identified the HCP5-miR-140-5p axis as a potential noncoding RNA pathway upstream of SLC12A3 and SLC12A9, which was associated with immunomodulation and may represent a novel predictor for clinical prognosis and responsiveness to checkpoint blockade immunotherapy. These findings may facilitate a better understanding of the SLCome and guide future rationalized development of SLC-targeted therapy and drug discovery for UVM.

Integrated immunogenomic analysis of single-cell and bulk tissue transcriptome profiling unravels a macrophage activation paradigm associated with immunologically and clinically distinct behaviors in ovarian cancer.

INTRODUCTION: Increasing evidence demonstrates that the activation states and diverse spectrum of macrophage subtypes display dynamic heterogeneity in the tumor microenvironment, which plays a critical role in a variety of cancer types. OBJECTIVES: To investigate the heterogeneity and the homeostasis of different macrophage subtypes, as well as their effect on biological and clinical manifestations of ovarian cancer (OV). METHOD: Integrated immunogenomic analysis of single-cell and bulk tissuetranscriptome profiling was performed to systematically investigate the association between macrophage activation and prognostic and therapeutic efficacy. Consensus clustering analysis was used to define novel macrophage subtypes. An artificial neural network was used to simulate the dynamic activation of macrophages. RESULTS: The pan-cohort results suggested that high relative infiltration abundance of M0 and M1 macrophages was associated with improved outcome and therapeutic efficacy. However, it was the opposite for M2 macrophages. Unsupervised consensus clustering analysis revealed two OV subgroups characterized by a balance between M0, M1 and M2 macrophages with distinct clinical and immunological behaviors. Finally, a macrophage polarization-derived artificial neural network model was proposed to serve as a robust prognostic factor and predictive biomarker for therapeutic efficacy, which was validated in different independent patient cohorts. CONCLUSION: The present study provides a new understanding of macrophage heterogeneity and its association with OV prognosis and underlines the future clinical potential of a macrophage activation model for tumor prevention and treatment.

Pan-cancer landscape of T-cell exhaustion heterogeneity within the tumor microenvironment revealed a progressive roadmap of hierarchical dysfunction associated with prognosis and therapeutic efficacy.

BACKGROUND: T cells form the major component of anti-tumor immunity. A deeper understanding of T cell exhaustion (TEX) heterogeneity within the tumor microenvironment (TME) is key to overcoming TEX and improving checkpoint blockade immunotherapies in the clinical setting. METHODS: We conducted a comprehensive pan-cancer analysis of TEX subsets from 9564 tumor samples across 30 bulk solid cancer types. Pan-cancer TEX subtypes were identified using literature-derived hierarchical TEX-specific developmental pathway signatures. The potential multi-omics and clinical features involved in TEX heterogeneity were determined. FINDINGS: Our study yielded a dynamic, progressive roadmap and a hierarchical dysfunction landscape regarding TEX within the TME. In total, we identified five pan-cancer TEX subtypes, revealing tissue/cancer type-specific TEX patterns in low immunogenic tumors. By contrast, highly immunogenic tumors tend to harbor high frequencies of progenitor TEX subsets. In addition, the TEX profile also revealed distinct prognoses, intrinsic molecular subtype distribution, immune microenvironment and multi-omics features among the cancers. Network analysis identified four previously unknown TEX-associated cancer genes (tolloid-like 1, myosin heavy chain 111, P2Y receptor family member 8 and protein kinase D2), the possible association with anti-PD-1 immunotherapy response was validated using a single-cell dataset. Finally, a machine learning-based gene signature was developed to model the hierarchical TEX stages, verified in single-cell and immunotherapy patient cohorts. INTERPRETATION: Our study provided a TEX-derived system that can be applied for the immune subtyping of cancers and may have implications for the further optimization of personalized cancer immunotherapy. FUNDING: This study was supported by the National Natural Science Foundation of China (Grant No. 62072341 and 61973240). The funders had no roles in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

A multi-omics deep learning model for hypoxia phenotype to predict tumor aggressiveness and prognosis in uveal melanoma for rationalized hypoxia-targeted therapy.

Uveal melanoma (UM) represents the most common primary intraocular malignancy in adults and is characterized by aggressive behaviors and a lack of targeted therapies. Hypoxia-targeted therapy has become a promising new therapeutic strategy in tumors. Therefore, a better understanding of the tumor hypoxia microenvironment is critical to improve the treatment efficacy of UM. In this study, we conducted an extensive multi-omics analysis to explore the heterogeneity and prognostic significance of the hypoxia microenvironment. We found that UM revealed the most significant degree of intertumoral heterogeneity in hypoxia by quantifying tumor hypoxia compared with other solid tumor types. Then we systematically correlated the hypoxia phenotypes with clinicopathological features and found that hypoxic UM tumors were associated with an increased risk of metastasis, more aggressive phenotypes, and unfavorable clinical outcomes. Integrative multi-omics analyses identified multidimensional molecular alterations related to hypoxia phenotypes, including elevated genome instability, co-occurring of 8q arm gains and loss of chromosome 3, and BAP1 mutations. Furthermore, hypoxic UM tumors could be characterized by increased CD8+ T cell infiltration and decreased naïve B cell and dysregulated metabolic pathways. Finally, we introduced DNN2HM, an interpretable deep neural network model to decode hypoxia phenotypes from multi-omics data. We showed that the DNN2HM improves hypoxia phenotype prediction and robustly predicts tumor aggressiveness and prognosis in different multi-center datasets. In conclusion, our study provides novel insight into UM tumor microenvironment, which may have clinical implications for future rationalized hypoxia-targeted therapy.

iUMRG: multi-layered network-guided propagation modeling for the inference of susceptibility genes and potential drugs against uveal melanoma.

Uveal melanoma (UM) is the most common primary malignant intraocular tumor. The use of precision medicine for UM to enable personalized diagnosis, prognosis, and treatment require the development of computer-aided strategies and predictive tools that can identify novel high-confidence susceptibility genes (HSGs) and potential therapeutic drugs. In the present study, a computational framework via propagation modeling on integrated multi-layered molecular networks (abbreviated as iUMRG) was proposed for the systematic inference of HSGs in UM. Under the leave-one-out cross-validation experiments, the iUMRG achieved superior predictive performance and yielded a higher area under the receiver operating characteristic curve value (0.8825) for experimentally verified SGs. In addition, using the experimentally verified SGs as seeds, genome-wide screening was performed to detect candidate HSGs using the iUMRG. Multi-perspective validation analysis indicated that most of the top 50 candidate HSGs were indeed markedly associated with UM carcinogenesis, progression, and outcome. Finally, drug repositioning experiments performed on the HSGs revealed 17 potential targets and 10 potential drugs, of which six have been approved for UM treatment. In conclusion, the proposed iUMRG is an effective supplementary tool in UM precision medicine, which may assist the development of new medical therapies and discover new SGs.

Transcriptional landscape of circulating platelets from patients with COVID-19 reveals key subnetworks and regulators underlying SARS-CoV-2 infection: implications for immunothrombosis.

BACKGROUND: Thrombosis and coagulopathy are pervasive pathological features of coronavirus disease 2019 (COVID-19), and thrombotic complications are a sign of severe COVID-19 disease and are associated with multiple organ failure and increased mortality. Platelets are essential cells that regulate hemostasis, thrombus formation and inflammation; however, the mechanism underlying the interaction between platelets and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains unclear. RESULTS: The present study performed RNA sequencing on the RNA isolated from platelets obtained from 10 COVID-19 patients and eight healthy donors, and discovered that SARS-CoV-2 not only significantly altered the coding and non-coding transcriptional landscape, but also altered the function of the platelets, promoted thrombus formation and affected energy metabolism of platelets. Integrative network biology analysis identified four key subnetworks and 16 risk regulators underlying SARS-CoV-2 infection, involved in coronavirus disease-COVID-19, platelet activation and immune response pathways. Furthermore, four risk genes (upstream binding transcription factor, RNA polymerase II, I and III subunit L, Y-box binding protein 1 and yippee like 2) were found to be associated with COVID-19 severity. Finally, a significant alteration in the von Willebrand factor/glycoprotein Ib-IX-V axis was revealed to be strongly associated with platelet aggregation and immunothrombosis. CONCLUSIONS: The transcriptional landscape and the identification of critical subnetworks and risk genes of platelets provided novel insights into the molecular mechanisms of immunothrombosis in COVID-19 progression, which may pave the way for the development of novel therapeutic strategies for preventing COVID-19-associated thrombosis and improving the clinical outcome of COVID-19 patients.

Computational elucidation of spatial gene expression variation from spatially resolved transcriptomics data.

Recent advances in spatially resolved transcriptomics (SRT) have revolutionized biological and medical research and enabled unprecedented insight into the functional organization and cell communication of tissues and organs in situ. Identifying and elucidating gene spatial expression variation (SE analysis) is fundamental to elucidate the SRT landscape. There is an urgent need for public repositories and computational techniques of SRT data in SE analysis alongside technological breakthroughs and large-scale data generation. Increasing efforts to use in silico techniques in SE analysis have been made. However, these attempts are widely scattered among a large number of studies that are not easily accessible or comprehensible by both medical and life scientists. This study provides a survey and a summary of public resources on SE analysis in SRT studies. An updated systematic overview of state-of-the-art computational approaches and tools currently available in SE analysis are presented herein, emphasizing recent advances. Finally, the present study explores the future perspectives and challenges of in silico techniques in SE analysis. This study guides medical and life scientists to look for dedicated resources and more competent tools for characterizing spatial patterns of gene expression.

Cell-free DNA 5-hydroxymethylcytosine profiles of long non-coding RNA genes enable early detection and progression monitoring of human cancers.

BACKGROUND: 5-Hydroxymethylcytosine (5hmC) is a significant DNA epigenetic modification. However, the 5hmC modification alterations in genomic regions encoding long non-coding RNA (lncRNA) and their clinical significance remain poorly characterized. RESULTS: A three-phase discovery-modeling-validation study was conducted to explore the potential of the plasma-derived 5hmC modification level in genomic regions encoding lncRNAs as a superior alternative biomarker for cancer diagnosis and surveillance. Genome-wide 5hmC profiles in the plasma circulating cell-free DNA of 1632 cancer and 1379 non-cancerous control samples from different cancer types and multiple centers were repurposed and characterized. A large number of altered 5hmC modifications were distributed at genomic regions encoding lncRNAs in cancerous compared with healthy subjects. Furthermore, most 5hmC-modified lncRNA genes were cancer-specific, with only a relatively small number of 5hmC-modified lncRNA genes shared by various cancer types. A 5hmC-LncRNA diagnostic score (5hLD-score) comprising 39 tissue-shared 5hmC-modified lncRNA gene markers was developed using elastic net regularization. The 5hLD-score was able to accurately distinguish tumors from healthy controls with an area under the curve (AUC) of 0.963 [95% confidence interval (CI) 0.940-0.985] and 0.912 (95% CI 0.837-0.987) in the training and internal validation cohorts, respectively. Results from three independent validations confirmed the robustness and stability of the 5hLD-score with an AUC of 0.851 (95% CI 0.786-0.916) in Zhang's non-small cell lung cancer cohort, AUC of 0.887 (95% CI 0.852-0.922) in Tian's esophageal cancer cohort, and AUC of 0.768 (95% CI 0.746-0.790) in Cai's hepatocellular carcinoma cohort. In addition, a significant association was identified between the 5hLD-score and the progression from hepatitis to liver cancer. Finally, lncRNA genes modified by tissue-specific 5hmC alteration were again found to be capable of identifying the origin and location of tumors. CONCLUSION: The present study will contribute to the ongoing effort to understand the transcriptional programs of lncRNA genes, as well as facilitate the development of novel invasive genomic tools for early cancer detection and surveillance.

Pan-cancer characterization of lncRNA modifiers of immune microenvironment reveals clinically distinct de novo tumor subtypes.

The emerging field of long noncoding RNA (lncRNA)-immunity has provided a new perspective on cancer immunity and immunotherapies. The lncRNA modifiers of infiltrating immune cells in the tumor immune microenvironment (TIME) and their impact on tumor behavior and disease prognosis remain largely uncharacterized. In the present study, a systems immunology framework integrating the noncoding transcriptome and immunogenomics profiles of 9549 tumor samples across 30 solid cancer types was used, and 36 lncRNAs were identified as modifier candidates underlying immune cell infiltration in the TIME at the pan-cancer level. These TIME lncRNA modifiers (TIL-lncRNAs) were able to subclassify various tumors into three de novo pan-cancer subtypes characterized by distinct immunological features, biological behaviors, and disease prognoses. Finally, a TIL-lncRNA-derived immune state index (TISI) that was reflective of immunological and oncogenic states but also predictive of patients' prognosis was proposed. Furthermore, the TISI provided additional prognostic value for existing tumor immunological and molecular subtypes. By applying the TISI to tumors from different clinical immunotherapy cohorts, the TISI was found to be significantly negatively correlated with immune-checkpoint genes and to have the ability to predict the effectiveness of immunotherapy. In conclusion, the present study provided comprehensive resources and insights for future functional and mechanistic studies on lncRNA-mediated cancer immunity and highlighted the potential of the clinical application of lncRNA-based immunotherapeutic strategies in precision immunotherapy.

[Clinical Diagnosis and Treatment Recommendations for Immune Checkpoint Inhibitor-related Hematological Adverse Events].

Immune checkpoint inhibitors are able to reactivate the immune system therefore enhance the anti-tumor effects. However, over-activated T cells may induce immune related adverse events (irAEs). Hematological irAEs are rarely reported, which mainly represent as mono-lineage cytopenia or pancytopenia, including autoimmune hemolytic anemia (AIHA), immune thrombocytopenia (ITP), neutropenia and aplastic anemia, sometimes even lethal, such as hemophagocytic lymphohistiocytosis. The clinical manifestations of hematological irAEs will be summarized and recommendations of diagnosis and treatment are proposed.

Treatment and management of adrenal cancer in a specialized Australian endocrine surgical unit: approaches, outcomes and lessons learnt.

BACKGROUND: Adrenocortical carcinoma is a rare and heterogeneous malignancy with poor outcomes. Recent research has suggested that outcomes may be improved by centralization of care in specialist centres. We review our evolving 21-year experience in managing adrenocortical carcinoma with a view towards outcomes and lessons learnt. METHODS: A retrospective study of patients treated in our specialist endocrine surgical unit over 21 years was undertaken. RESULTS: Thirty-five patients were treated from diagnosis, 29 forming a primary study cohort. Additionally, seven patients were referred to us for quaternary care, forming a secondary study cohort. The European Network for the Study of Adrenal Tumours (ENSAT) stage and immunohistochemical marker Ki-67 index were strong prognostic indicators for survival. CONCLUSIONS: Early stage, complete resection and Ki-67 <10% are the best prognosticators for survival. Aggressive surgical resection at index operation and of recurrent oligometastatic disease along with multimodal adjuvant treatment has led to long-term survivors of patients with Stage 4 disease in our aggregate cohort.

Carvedilol Compared With Metoprolol Succinate in the Treatment and Prognosis of Patients With Stable Chronic Heart Failure: Carvedilol or Metoprolol Evaluation Study.

BACKGROUND: ß-Blockers exert a prognostic benefit in the treatment of chronic heart failure. Their pharmacological properties vary. The only substantial comparative trial to date-the Carvedilol or Metoprolol European Trial-has compared carvedilol with short-acting metoprolol tartrate at different dose equivalents. We therefore addressed the relative efficacy of equal doses of carvedilol and metoprolol succinate on survival in multicenter hospital outpatients with chronic heart failure. METHODS AND RESULTS: Four thousand sixteen patients with stable systolic chronic heart failure who were using either carvedilol or metoprolol succinate were identified in the Norwegian Heart Failure Registry and The Heart Failure Registry of the University of Heidelberg, Germany. Patients were individually matched on both the dose equivalents and the respective propensity scores for ß-blocker treatment. During a follow-up for 17 672 patient-years, it was found that 304 (27.2%) patients died in the carvedilol group and 1066 (36.8%) in the metoprolol group. In a univariable analysis of the general sample, metoprolol therapy was associated with higher mortality compared with carvedilol therapy (hazard ratio, 1.49; 95% confidence interval, 1.31-1.69; P<0.001). This difference was not seen after multivariable adjustment (hazard ratio, 0.93; 95% confidence interval, 0.57-1.50; P=0.75) and adjustment for propensity score and dose equivalents (hazard ratio, 1.06; 95% confidence interval, 0.94-1.20; P=0.36) or in the propensity and dose equivalent-matched sample (hazard ratio, 1.00; 95% confidence interval, 0.82-1.23; P=0.99). These results were essentially unchanged for all prespecified subgroups. CONCLUSIONS: In outpatients with chronic heart failure, no conclusive association between all-cause mortality and treatment with carvedilol or metoprolol succinate was observed after either multivariable adjustment or multilevel propensity score matching.

Papillary thyroid cancer-derived exosomes contain miRNA-146b and miRNA-222.

BACKGROUND: With the increasing diagnosis of indolent papillary thyroid cancer (PTC), the task of identifying those likely to suffer from recurrence is becoming ever more challenging. MicroRNA (miRNA/miR) in the circulation has been demonstrated as potential biomarkers of recurrence in PTC. This study aimed to investigate in vitro if extracellular miRNAs are contained in exosomes, and their potential effect on other cells. METHODS: TPC-1 (PTC) and NTHY (normal thyroid follicular) cell lines were treated with exosome isolates and conditioned medium (CM), both containing miR-146b and miR-222. The changes in proliferation over a 72-h period of TPC-1 and NTHY were compared. Student t-test and analysis of variance were used for significance testing, and P < 0.05 was considered significant. RESULTS: Exosomes derived from TPC-1 cells were demonstrated to contain miR-146b and miR-222 in relative abundance. These exosomes caused a negative proliferative effect on both TPC-1 and NTHY cells. Exosomes derived from NTHY cells did not exert a significant proliferative effect on either cell line. CM from both cell types caused an initial increase in TPC-1 proliferation at 24 h. No significant change in proliferation was seen with NTHY cells when treated with either of the CM. CONCLUSIONS: The results showed that PTC cells overexpress miR-146b and miR-222 in exosomes; and that factors released by both normal thyroid and PTC cells alter proliferation of other cells in a complex manner. The intercellular interactions were likely conferred in part by exosomal miRNA, which can potentially be developed as biomarkers of PTC recurrence.

Etiology-specific assessment of predictors of long-term survival in chronic systolic heart failure.

BACKGROUND: We sought to identify prognostic factors of long-term mortality, specific for the underlying etiology of chronic systolic heart failure (CHF). METHODS AND RESULTS: Between 1995 and 2009 baseline characteristics, treatment and follow-up data from 2318 CHF-patients due to ischemic (ICM; 1100 patients) or dilated cardiomyopathy (DCM; 1218 patients) were prospectively compared. To calculate hazard ratios with 95%-confidence intervals cox regression was used. We respectively established etiology-specific multivariable models of independent prognostic factors. During the follow-up period of up to 14.8 years (mean = 53.1 ± 43.5 months; 10,264 patient-years) 991 deaths (42.8%) occurred. In the ICM-cohort, 5-year-survival was 53.4% (95% CI: 49.9-56.7%), whereas in DCM-patients it was higher (68.1% (95% CI: 65.1-71.0%)). Age, ejection fraction, or hyponatremia were independent predictors for mortality in both cohorts, whereas diabetes, COPD, atrial fibrillation and a heart rate of ≥ 80/min carried independent predictive power only in ICM-patients. CONCLUSION: This study demonstrates the disparity of prognostic value of clinically derived risk factors between the two main causes of CHF. The effects of covariables in DCM-patients were lower, suggesting a less modifiable disease through risk factors considering mortality risk. An etiology-specific prognostic model may improve accuracy of survival estimations in CHF.

Dissociated stimulus and response conflict effect in the Stroop task: evidence from evoked brain potentials and brain oscillations.

The Stroop task is a classic paradigm that can be used to examine cognitive control as it contains conditions with and without interference. Cumulative evidence suggests that both stimulus and response conflict contribute to the Stroop interference effect. However, it remains unclear whether there are dissociable event-related potential (ERP) or frequency band-specific electroencephalographic (EEG) power changes associated with stimulus conflict and response conflict. To investigate potential markers for each form of conflict, we applied a Stroop 2-1 mapping task in 20 healthy young adults. Results showed that a negative deflection in the 350-500ms time window (N450) and a positive deflection in the 600-900ms time window (late positive component, LPC) were associated with response conflict and stimulus conflict, respectively. Time-frequency analyses found that both stimulus and response conflict induced theta band power changes and that response conflict additionally induced a beta band power change. These results indicate that stimulus and response conflict in the Stroop task are associated with different ERP effects and brain oscillatory features.