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This review paper summarizes major developments in vehicular emissions regulations and technologies from 2014. The paper starts with the key regulatory advancements in the field, including newly proposed Non-Road Mobile Machinery regulations for 2019-20 in Europe, and the continuing developments towards real driving emissions (RDE) standards. An expert panel in India proposed a roadmap through 2025 for clean fuels and tailpipe regulations. LD (light duty) and HD (heavy-duty) engine technology continues showing marked improvements in engine efficiency. Key developments are summarized for gasoline and diesel engines to meet both the emerging NOx and GHG regulations. HD engines are demonstrating more than 50% brake thermal efficiency using methods that can reasonably be commercialized. Next, NOx control technologies are summarized, including SCR (selective catalytic reduction), lean NOx traps, and combination systems. Emphasis is on durability and control. Diesel PM (particulate matter) reduction findings are evolving around the behavior of the soot cake and PM sensors. Gasoline particulates are further described and gasoline particulate filter regeneration is now better understood. Oxidation catalysts mainly involve developments towards stubborn problems, like sulfur tolerance, low-temperature performance with exhaust with high hydrocarbon and CO, and methane oxidation. Finally, the paper discusses some key developments in gasoline gaseous emission control, focusing on meeting new regulatory requirements in the US, durability, and on lean burn gasoline emissions control.

With increasing pressures to reduce or eliminate the use of antimicrobials for growth promotion purposes in production animals, there is a growing need to better understand the effects elicited by these agents in order to identify alternative approaches that might be used to maintain animal health. Antibiotic usage at subtherapeutic levels is postulated to confer a number of modulations in the microbes within the gut that ultimately result in growth promotion and reduced occurrence of disease. This study examined the effects of the coccidiostat monensin and the growth promoters virginiamycin and tylosin on the broiler chicken cecal microbiome and metagenome. Using a longitudinal design, cecal contents of commercial chickens were extracted and examined using 16S rRNA and total DNA shotgun metagenomic pyrosequencing. A number of genus-level enrichments and depletions were observed in response to monensin alone, or monensin in combination with virginiamycin or tylosin. Of note, monensin effects included depletions of Roseburia, Lactobacillus and Enterococcus, and enrichments in Coprococcus and Anaerofilum. The most notable effect observed in the monensin/virginiamycin and monensin/tylosin treatments, but not in the monensin-alone treatments, was enrichments in Escherichia coli. Analysis of the metagenomic dataset identified enrichments in transport system genes, type I fimbrial genes, and type IV conjugative secretion system genes. No significant differences were observed with regard to antimicrobial resistance gene counts. Overall, this study provides a more comprehensive glimpse of the chicken cecum microbial community, the modulations of this community in response to growth promoters, and targets for future efforts to mimic these effects using alternative approaches.

This review paper summarizes major developments in vehicular emissions regulations and technologies (light-duty, heavy-duty, gasoline, diesel) in 2012. First, the paper covers the key regulatory developments in the field, including finalized criteria pollutant tightening in California; and in Europe, the development of real-world driving emissions (RDE) standards. The US finalized LD (light-duty) greenhouse gas (GHG) regulation for 2017-25. The paper then gives a brief, high-level overview of key developments in LD and HD engine technology, covering both gasoline and diesel. Marked improvements in engine efficiency are summarized for gasoline and diesel engines to meet both the emerging NOx and GHG regulations. HD engines are just starting to demonstrate 50% brake thermal efficiency. NOx control technologies are then summarized, including SCR (selective catalytic reduction) with ammonia, and hydrocarbon-based approaches. Emphasis is on low-temperature deNOx, durability, and cost reduction. PM (particulate matter) reduction technologies are evolving around SCR integration and the behavior of soot and ash deposits. Next, DOC (diesel oxidation catalyst) developments are summarized. They mainly involve better understanding of aging and substitution of base metals oxides for precious metal. The paper then discusses some key developments in gasoline emission controls, focusing on new coated GPF (gasoline particulate filter) understanding. Advanced three-way catalysts improve with layered coating technology, and with improved understanding on engine calibration.

Understanding emotion is critical for a science of healthy and disordered brain function, but the neurophysiological basis of emotional experience is still poorly understood. We analyzed human brain activity patterns from 148 studies of emotion categories (2159 total participants) using a novel hierarchical Bayesian model. The model allowed us to classify which of five categories--fear, anger, disgust, sadness, or happiness--is engaged by a study with 66% accuracy (43-86% across categories). Analyses of the activity patterns encoded in the model revealed that each emotion category is associated with unique, prototypical patterns of activity across multiple brain systems including the cortex, thalamus, amygdala, and other structures. The results indicate that emotion categories are not contained within any one region or system, but are represented as configurations across multiple brain networks. The model provides a precise summary of the prototypical patterns for each emotion category, and demonstrates that a sufficient characterization of emotion categories relies on (a) differential patterns of involvement in neocortical systems that differ between humans and other species, and (b) distinctive patterns of cortical-subcortical interactions. Thus, these findings are incompatible with several contemporary theories of emotion, including those that emphasize emotion-dedicated brain systems and those that propose emotion is localized primarily in subcortical activity. They are consistent with componential and constructionist views, which propose that emotions are differentiated by a combination of perceptual, mnemonic, prospective, and motivational elements. Such brain-based models of emotion provide a foundation for new translational and clinical approaches.

The integration of generative Artificial Intelligence (AI) into academia has sparked interest and debate among academic scientists. This paper explores the early adoption and perceptions of US academic scientists regarding the use of generative AI in teaching and research activities. To do so, this analysis focuses exclusively on STEM fields due to their high exposure to rapid technological advancements. Drawing from a nationally representative survey of 232 respondents, we examine academic scientists’ attitudes, experiences, and intentions regarding AI adoption. Results indicate that 65% of respondents have utilized generative AI in teaching or research activities, with 20% applying it in both areas. Among those currently using AI, 84% intend to continue its application, indicating a high level of confidence in its perceived benefits. AI is most frequently used in teaching to develop pedagogical materials (51%) and in research for writing, reviewing, and editing tasks (40%). Despite concerns about misinformation, with 78% of respondents indicating it as their top concern regarding AI, there is broad recognition of AI’s potential impact on society. Most academic scientists have already integrated AI into their academic activities, demonstrating cautious yet optimistic adoption due to perceived risks. Furthermore, there is strong support for academic-led regulation of AI, highlighting the need for responsible governance to maximize benefits while minimizing risks in educational and research settings.

Background The first consensus Merkel cell carcinoma (MCC) staging system was published in 2010. New information on the clinical course prompts review of MCC staging. Methods A total of 9387 MCC cases from the National Cancer Data Base Participant User File with follow-up and staging data (1998–2012) were analyzed. Prognostic differences based on clinical and pathological staging were evaluated. Survival estimates were compared by disease extent. Results Sixty-five percent of cases presented with local disease, whereas 26 and 8 % presented with nodal and distant disease. Disease extent at presentation was predictive of 5-year overall survival (OS) with estimates of 51, 35, and 14 % for local, nodal, and distant disease. Tumor burden at the regional nodal basin was predictive of 5-year OS with estimates of 40 and 27 % for clinically occult and clinically detected nodal disease. For local disease, we confirm improved prognosis when the regional nodal basin was negative by pathological compared with clinical staging. We identified 336 cases with clinically detected nodal disease and unknown primary tumor and showed improved prognosis over cases presenting with concurrent primary tumor (OS estimates of 42 vs. 27 %). Conclusions Analysis of a national dataset of MCC cases validates the predictive value of disease extent at presentation. Separation of clinical and pathological stage groups and regrouping of unknown primary tumors are supported by the analysis. The revised staging system provides more accurate prognostication and has been formally accepted by the AJCC staging committee for inclusion in the 8th edition.

Renal clinical chemistry only detects kidney dysfunction after considerable damage has occurred and is imperfect in predicting long term outcomes. Consequently, more sensitive markers of early damage and better predictors of progression are being urgently sought, to better support clinical decisions and support shorter clinical trials. Transglutaminase 2 (TG2) is strongly implicated in the fibrotic remodeling that drives chronic kidney disease (CKD). We hypothesized that urinary TG2 and its ε-(γ-glutamyl)-lysine crosslink product could be useful biomarkers of kidney fibrosis and progression. Animal models: a rat 4-month 5/6 th subtotal nephrectomy model of CKD and a rat 8-month streptozotocin model of diabetic kidney disease had 24-hour collection of urine, made using a metabolic cage, at regular periods throughout disease development. Patients: Urine samples from patients with CKD ( n = 290) and healthy volunteers ( n = 33) were collected prospectively, and progression tracked for 3 years. An estimated glomerular filtration rate (eGFR) loss of 2–5 mL/min/year was considered progressive, with rapid progression defined as > 5 mL/min/year. Assays: TG2 was measured in human and rat urine samples by enzyme-linked immunosorbent assay (ELISA) and ε-(γ-glutamyl)-lysine by exhaustive proteolytic digestion and amino acid analysis. Urinary TG2 and ε-(γ-glutamyl)-lysine increased with the development of fibrosis in both animal model systems. Urinary TG2 was 41-fold higher in patients with CKD than HVs, with levels elevated 17-fold by CKD stage 2. The urinary TG2:creatinine ratio (UTCR) was 9 ng/mmol in HV compared with 114 ng/mmol in non-progressive CKD, 1244 ng/mmol in progressive CKD and 1898 ng/mmol in rapidly progressive CKD. Both urinary TG2 and ε-(γ-glutamyl)-lysine were significantly associated with speed of progression in univariate logistic regression models. In a multivariate model adjusted for urinary TG2, ε-(γ-glutamyl)-lysine, age, sex, urinary albumin:creatinine ratio (UACR), urinary protein:creatinine ratio (UPCR), and CKD stage, only TG2 remained statistically significant. Receiver operating characteristic (ROC) curve analysis determined an 86.4% accuracy of prediction of progression for UTCR compared with 73.5% for UACR. Urinary TG2 and ε-(γ-glutamyl)-lysine are increased in CKD. In this pilot investigation, UTCR was a better predictor of progression in patients with CKD than UACR. Larger studies are now warranted to fully evaluate UTCR value in predicting patient outcomes.