Direct and indirect immunofluorescence

A imunofluorescência é um valioso instrumento auxiliar no diagnóstico das dermatoses bolhosas autoimunes e desordens inflamatórias, uma vez que seus achados clínicos e histopatológicos podem não ser determinantes. Consiste em um método laboratorial factível, que requer profissionais técnicos experientes, e detecta imunocomplexos in situ e/ou circulantes, que podem estar envolvidos na patogênese de tais enfermidades cutâneas.Immunofluorescence is a valuable auxiliary diagnostic tool for autoimmune bullous diseases and inflammatory disorders, since their clinical and histopathologic findings may be inconclusive. It is a feasible laboratory method that requires experienced technicians and detects in situ and circulating immune deposits that may be involved in the pathogenesis of such skin diseases.CNP

Influence of migration on the thought process of individuals at ultra-high risk for psychosis

OBJECTIVE To assess the influence of migration on the psychopathological presentation of individuals at ultra-high risk for psychosis (UHR) in São Paulo, Brazil. METHODS This study is part of the Subclinical Symptoms and Prodromal Psychosis (SSAPP) project, a cohort study in São Paulo, Brazil, designed to follow individuals at UHR. After screening with the Prodromal Questionnaire (PQ) and a clinical interview, the Global Assessment of Functioning (GAF) was administered, a neuropsychological assessment was performed, sociodemographic and migration data were obtained. We then analyzed UHR individuals who had migration data to see if migration had any effect on their cognition and psychopathology. Chi-square tests were used for categorical variables, and Student's t test or analysis of variance (ANOVA) were used for nonparametric and parametric distributions, respectively. RESULTS The sample was composed of 42 at-risk subjects, of whom 5 had a migration history in the past two generations. Those with migration history showed significantly more formal thought disturbances (p = 0.012) and sleeping problems (p = 0.033) compared to those without. CONCLUSIONS Our data reinforce migration as a risk factor for psychosis in developing countries as well, and highlights the importance of studying the specific effect of this factor in UHR psychopathology

Balancing repair and tolerance of DNA damage caused by alkylating agents

Alkylating agents constitute a major class of frontline chemotherapeutic drugs that inflict cytotoxic DNA damage as their main mode of action, in addition to collateral mutagenic damage. Numerous cellular pathways, including direct DNA damage reversal, base excision repair (BER) and mismatch repair (MMR), respond to alkylation damage to defend against alkylation-induced cell death or mutation. However, maintaining a proper balance of activity both within and between these pathways is crucial for a favourable response of an organism to alkylating agents. Furthermore, the response of an individual to alkylating agents can vary considerably from tissue to tissue and from person to person, pointing to genetic and epigenetic mechanisms that modulate alkylating agent toxicity

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio