Internação em unidade de terapia intensiva: percepção de pacientes

Estudo com abordagem qualitativa que objetivou compreender, a partir da perspectiva do paciente adulto, a experiênciade se vivenciar uma internação em Unidade de Terapia Intensiva (UTI), de modo a contribuir para melhoriana qualidade da assistência e facilitar a adaptação em um ambiente tão estigmatizado. Os dados foram coletadosna UTI de um hospital do sudoeste de São Paulo, Brasil. Foram entrevistados dez pacientes, e identificadastemáticas relacionadas à percepção prévia da UTI; diferenciação com a assistência nos setores de internamento;tecnologia e assistência especializada; alterações ambientais e de hábitos em UTI. Inicialmente, os informantesrelacionavam a UTI com a terminalidade e passaram a retratar o setor como local para o tratamento erecuperação, passando a ter uma visão positiva do ambiente de terapia intensiva.

Olfactory Enrichment Influences Adult Neurogenesis Modulating GAD67 and Plasticity-Related Molecules Expression in Newborn Cells of the Olfactory Bulb

The olfactory bulb (OB) is a highly plastic region of the adult mammalian brain characterized by continuous integration of inhibitory interneurons of the granule (GC) and periglomerular cell (PGC) types. Adult-generated OB interneurons are selected to survive in an experience-dependent way but the mechanisms that mediate the effects of experience on OB neurogenesis are unknown. Here we focus on the new-generated PGC population which is composed by multiple subtypes. Using paradigms of olfactory enrichment and/or deprivation combined to BrdU injections and quantitative confocal immunohistochemical analyses, we studied the effects of olfactory experience on adult-generated PGCs at different survival time and compared PGC to GC modulation. We show that olfactory enrichment similarly influences PGCs and GCs, increasing survival of newborn cells and transiently modulating GAD67 and plasticity-related molecules expression. However, PGC maturation appears to be delayed compared to GCs, reflecting a different temporal dynamic of adult generated olfactory interneuron integration. Moreover, olfactory enrichment or deprivation do not selectively modulate the survival of specific PGC phenotypes, supporting the idea that the integration rate of distinct PGC subtypes is independent from olfactory experience

Methanogens, sulphate and heavy metals: a complex system

Anaerobic digestion (AD) is a well-established technology used for the treatment of wastes and wastewaters with high organic content. During AD organic matter is converted stepwise to methane-containing biogasa renewable energy carrier. Methane production occurs in the last AD step and relies on methanogens, which are rather sensitive to some contaminants commonly found in wastewaters (e.g. heavy metals), or easily outcompeted by other groups of microorganisms (e.g. sulphate reducing bacteria, SRB). This review gives an overview of previous research and pilot-scale studies that shed some light on the effects of sulphate and heavy metals on methanogenesis. Despite the numerous studies on this subject, comparison is not always possible due to differences in the experimental conditions used and parameters explained. An overview of the possible benefits of methanogens and SRB co-habitation is also covered. Small amounts of sulphide produced by SRB can precipitate with metals, neutralising the negative effects of sulphide accumulation and free heavy metals on methanogenesis. Knowledge on how to untangle and balance sulphate reduction and methanogenesis is crucial to take advantage of the potential for the utilisation of biogenic sulphide as a metal detoxification agent with minimal loss in methane production in anaerobic digesters.The research was financially supported by the People Program (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007-2013 under REA agreement 289193

Traditional use of the Andean flicker (Colaptes rupicola) as a galactagogue in the Peruvian Andes

This paper explores the use of the dried meat and feathers of the Andean Flicker (Colaptes rupicola) to increase the milk supply of nursing women and domestic animals in the Andes. The treatment is of preColumbian origin, but continues to be used in some areas, including the village in the southern Peruvian highlands where I do ethnographic research. I explore the factors giving rise to and sustaining the practice, relate it to other galactagogues used in the Andes and to the use of birds in ethnomedical and ethnoveterinary treatments in general, and situate it within the general tendency in the Andes and elsewhere to replicate human relations in the treatment of valuable livestock. The bird's use as a galactagogue appears to be motivated by both metaphorical associations and its perceived efficacy, and conceptually blends human and animal healthcare domains

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

Predicting probable Alzheimer's disease using linguistic deficits and biomarkers

BackgroundThe manual diagnosis of neurodegenerative disorders such as Alzheimer’s disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic criteria and neuropsychological examinations. The use of several Machine Learning algorithms to build automated diagnostic models using low-level linguistic features resulting from verbal utterances could aid diagnosis of patients with probable AD from a large population. For this purpose, we developed different Machine Learning models on the DementiaBank language transcript clinical dataset, consisting of 99 patients with probable AD and 99 healthy controls.ResultsOur models learned several syntactic, lexical, and n-gram linguistic biomarkers to distinguish the probable AD group from the healthy group. In contrast to the healthy group, we found that the probable AD patients had significantly less usage of syntactic components and significantly higher usage of lexical components in their language. Also, we observed a significant difference in the use of n-grams as the healthy group were able to identify and make sense of more objects in their n-grams than the probable AD group. As such, our best diagnostic model significantly distinguished the probable AD group from the healthy elderly group with a better Area Under the Receiving Operating Characteristics Curve (AUC) using the Support Vector Machines (SVM).ConclusionsExperimental and statistical evaluations suggest that using ML algorithms for learning linguistic biomarkers from the verbal utterances of elderly individuals could help the clinical diagnosis of probable AD. We emphasise that the best ML model for predicting the disease group combines significant syntactic, lexical and top n-gram features. However, there is a need to train the diagnostic models on larger datasets, which could lead to a better AUC and clinical diagnosis of probable AD