Search

BackgroundPathologic staging is crucial in colorectal cancer (CRC). Unlike the majority of solid tumors, the current staging model does not use tumor size as a criterion. We evaluated the predictive and prognostic impact of primary tumor size on all stages of CRC.MethodsUsing the National Cancer Database (NCDB), we conducted an analysis of CRC patients diagnosed between 2010 and 2015 who underwent resection of their primary cancer. Univariate and multivariate analyses were used to identify predictive and prognostic factors, Kaplan-Meier analysis and Cox proportional hazards models for association between tumor size and survival.ResultsAbout 61,000 patients met the inclusion criteria. Median age was 63 years and majority of the tumors were colon primary (82.7%). AJCC stage distribution was: I - 20.1%; II - 32.1%; III - 34.7% and IV - 13.1%. The prognostic impact of tumor size was strongly associated with survival in stage III disease. Compared to patients with tumors 10cm (HR 1.95 (1.65-2.31; p

BackgroundHigh-risk features, such as T4 disease, bowel obstruction, poorly/undifferentiated histology, lymphovascular, perineural invasion, and 1, and older age. Adjuvant chemotherapy administration was associated with better OS, regardless of the high-risk features in dMMR/MSI-H (log-rank test, p = 0.001) or not (p = 0.0006). When stratified by age, the benefit of chemotherapy was evident only in patients age ≥65 with high-risk features.ConclusionHigh-risk features are prognostic in the setting of dMMR/MSI-H stage II CC. Adjuvant chemotherapy may improve survival specifically in patients ≥65 years and with high-risk features.

BackgroundTumor sidedness as a prognostic factor in advanced stage colon cancer (CC) is well established. The impact of tumor sidedness on the clinical outcomes of stage II and III CC has not been well studied.MethodsThe National Cancer Database (NCDB) was utilized to identify patients with pathological stage II and III primary adenocarcinoma of the colon from 2010 to 2015 using ICD-O-3 morphology and topography codes: 8140-47, 8210-11, 8220-21, 8260-63, 8480-81, 8490 and C18.0, 18.2,18.3, 18.5,18.6, 18.7. Univariate (UVA) and multivariable (MVA) survival analyses and Kaplan–Meier Curves with Log-rank test were utilized to compare overall survival (OS) based on tumor location and treatment received.ResultsA total of 35,071 patients with stage II (n = 17,629) and III (n = 17,442) CC were identified. 51.3% female; 81.5% Caucasian; median age 66 (range, 18–90). Majority of stage II and III tumors were right sided, 61.2% (n = 10,794) and 56.0% (n = 9,763). Microsatellite instability high (MSI-H) was more common in stage II compared to III, 23.3% (n = 4,115) vs 18.2% (n = 3,171) (p < 0.0001). In stage II MSI-H CC right was more common than left, 78.3% (n = 3223) vs 21.7% (n = 892). There was no significant difference in survival between stage II MSI-H left vs right (5-year OS 76.2 vs 74.7%, p = 0.1578). Stage II MSS CC right was more common than left, 56.0% (n = 7571) vs 44.0% (n = 5943), and survival was better in the left vs right (5-year OS 73.2 vs 70.8%, p = 0.0029). Stage III MSI-H CC was more common in the right than in the left, 75.6% (n = 2,397) vs 24.4% (n = 774) and survival was better in the left (5-year OS 62.5 vs 56.5%, p = 0.0026). Stage III MSS CC was more common in the right than in the left, 51.6% (n = 7,366) vs 48.4% (n = 6,905), and survival was better in the left vs right (5-year OS 67.0 vs 54.4%, p < 0.001).ConclusionSurvival was better in left sided tumors compared to right in stage II MSS, stage III MSS, and stage III MSI-H CC.

Predictive coding models of brain processing propose that top-down cortical signals promote efficient neural signaling by carrying predictions about incoming sensory information. These “priors” serve to constrain bottom-up signal propagation where prediction errors are carried via feedforward mechanisms. Depression, traditionally viewed as a disorder characterized by negative cognitive biases, is associated with disrupted reward prediction error encoding and signaling. Accumulating evidence also suggests that depression is characterized by impaired local and long-range prediction signaling across multiple sensory domains. This review highlights the electrophysiological and neuroimaging evidence for disrupted predictive processing in depression. The discussion is framed around the manner in which disrupted generative predictions about the sensorium could lead to depressive symptomatology, including anhedonia and negative bias. In particular, the review focuses on studies of sensory deviance detection and reward processing, highlighting research evidence for both disrupted generative predictions and prediction error signaling in depression. The role of the monoaminergic and glutamatergic systems in predictive coding processes is also discussed. This review provides a novel framework for understanding depression using predictive coding principles and establishes a foundational roadmap for potential future research.

Rapid-acting interventions for the suicide crisis have the potential to transform treatment. In addition, recent innovations in suicide research methods may similarly expand our understanding of the psychological and neurobiological correlates of suicidal thoughts and behaviors. This review discusses the limitations and challenges associated with current methods of suicide risk assessment and presents new techniques currently being developed to measure rapid changes in suicidal thoughts and behavior. These novel assessment strategies include ecological momentary assessment, digital phenotyping, cognitive and implicit bias metrics, and neuroimaging paradigms and analysis methodologies to identify neural circuits associated with suicide risk. This review is intended to both describe the current state of our ability to assess rapid changes in suicide risk as well as to explore future directions for clinical, neurobiological, and computational markers research in suicide-focused clinical trials.

At the heart of most Power-to-X (PtX) concepts is the utilization of renewable electricity to produce hydrogen through the electrolysis of water. This hydrogen can be used directly as a final energy carrier or it can be converted into, for example, methane, synthesis gas, liquid fuels, electricity, or chemicals. Technical demonstration and systems integration are of major importance for integrating PtX into energy systems. As of June 2020, a total of 220 PtX research and demonstration projects in Europe have either been realized, completed, or are currently being planned. The central aim of this review is to identify and assess relevant projects in terms of their year of commissioning, location, electricity and carbon dioxide sources, applied technologies for electrolysis, capacity, type of hydrogen post-processing, and the targeted field of application. The latter aspect has changed over the years. At first, the targeted field of application was fuel production, for example for hydrogen buses, combined heat and power generation, and subsequent injection into the natural gas grid. Today, alongside fuel production, industrial applications are also important. Synthetic gaseous fuels are the focus of fuel production, while liquid fuel production is severely under-represented. Solid oxide electrolyzer cells (SOECs) represent a very small proportion of projects compared to polymer electrolyte membranes (PEMs) and alkaline electrolyzers. This is also reflected by the difference in installed capacities. While alkaline electrolyzers are installed with capacities between 50 and 5000 kW (2019/20) and PEM electrolyzers between 100 and 6000 kW, SOECs have a capacity of 150 kW. France and Germany are undertaking the biggest efforts to develop PtX technologies compared to other European countries. On the whole, however, activities have progressed at a considerably faster rate than had been predicted just a couple of years ago.