Identificação molecular de Bartonella henselae em paciente com SIDA soronegativo para doença da arranhadura do gato no Rio de Janeiro, Brasil

Bartonella henselae is associated with a wide spectrum of clinical manifestations, including cat scratch disease, endocarditis and meningoencephalitis, in immunocompetent and immunocompromised patients. We report the first molecularly confirmed case of B. henselae infection in an AIDS patient in state of Rio de Janeiro, Brazil. Although DNA sequence of B. henselae has been detected by polymerase chain reaction in a lymph node biopsy, acute and convalescent sera were nonreactive.Bartonella henselae está associada a um amplo espectro de manifestações clínicas, incluindo a doença da arranhadura de gato, endocardite, e meningoencefalite, em pacientes imunocompetentes e imunocomprometidos. Relatamos o primeiro caso confirmado por método molecular de B. henselae em um paciente com SIDA no estado do Rio de Janeiro, Brasil. Apesar da sequência de DNA de B. henselae ser detectada pela reação em cadeia da polimerase em uma biópsia do linfonodo, soros das fases aguda e convalescente foram não reativos

MOLECULAR IDENTIFICATION OF Bartonella henselae IN A SERONEGATIVE CAT SCRATCH DISEASE PATIENT WITH AIDS IN RIO DE JANEIRO, BRAZIL

Bartonella henselae is associated with a wide spectrum of clinical manifestations, including cat scratch disease, endocarditis and meningoencephalitis, in immunocompetent and immunocompromised patients. We report the first molecularly confirmed case of B. henselae infection in an AIDS patient in state of Rio de Janeiro, Brazil. Although DNA sequence of B. henselae has been detected by polymerase chain reaction in a lymph node biopsy, acute and convalescent sera were nonreactive

Environmental Shaping of Sponge Associated Archaeal Communities

Archaea are ubiquitous symbionts of marine sponges but their ecological roles and the influence of environmental factors on these associations are still poorly understood.We compared the diversity and composition of archaea associated with seawater and with the sponges Hymeniacidon heliophila, Paraleucilla magna and Petromica citrina in two distinct environments: Guanabara Bay, a highly impacted estuary in Rio de Janeiro, Brazil, and the nearby Cagarras Archipelago. For this we used metagenomic analyses of 16S rRNA and ammonia monooxygenase (amoA) gene libraries. Hymeniacidon heliophila was more abundant inside the bay, while P. magna was more abundant outside and P. citrina was only recorded at the Cagarras Archipelago. Principal Component Analysis plots (PCA) generated using pairwise unweighted UniFrac distances showed that the archaeal community structure of inner bay seawater and sponges was different from that of coastal Cagarras Archipelago. Rarefaction analyses showed that inner bay archaeaoplankton were more diverse than those from the Cagarras Archipelago. Only members of Crenarchaeota were found in sponge libraries, while in seawater both Crenarchaeota and Euryarchaeota were observed. Although most amoA archaeal genes detected in this study seem to be novel, some clones were affiliated to known ammonia oxidizers such as Nitrosopumilus maritimus and Cenarchaeum symbiosum.The composition and diversity of archaeal communities associated with pollution-tolerant sponge species can change in a range of few kilometers, probably influenced by eutrophication. The presence of archaeal amoA genes in Porifera suggests that Archaea are involved in the nitrogen cycle within the sponge holobiont, possibly increasing its resistance to anthropogenic impacts. The higher diversity of Crenarchaeota in the polluted area suggests that some marine sponges are able to change the composition of their associated archaeal communities, thereby improving their fitness in impacted environments

Brain clocks capture diversity and disparities in aging and dementia

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.</p

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

Peer reviewe

Utilization of mechanical power and associations with clinical outcomes in brain injured patients. a secondary analysis of the extubation strategies in neuro-intensive care unit patients and associations with outcome (ENIO) trial

BackgroundThere is insufficient evidence to guide ventilatory targets in acute brain injury (ABI). Recent studies have shown associations between mechanical power (MP) and mortality in critical care populations. We aimed to describe MP in ventilated patients with ABI, and evaluate associations between MP and clinical outcomes.MethodsIn this preplanned, secondary analysis of a prospective, multi-center, observational cohort study (ENIO, NCT03400904), we included adult patients with ABI (Glasgow Coma Scale &lt;= 12 before intubation) who required mechanical ventilation (MV) &gt;= 24 h. Using multivariable log binomial regressions, we separately assessed associations between MP on hospital day (HD)1, HD3, HD7 and clinical outcomes: hospital mortality, need for reintubation, tracheostomy placement, and development of acute respiratory distress syndrome (ARDS).ResultsWe included 1217 patients (mean age 51.2 years [SD 18.1], 66% male, mean body mass index [BMI] 26.3 [SD 5.18]) hospitalized at 62 intensive care units in 18 countries. Hospital mortality was 11% (n = 139), 44% (n = 536) were extubated by HD7 of which 20% (107/536) required reintubation, 28% (n = 340) underwent tracheostomy placement, and 9% (n = 114) developed ARDS. The median MP on HD1, HD3, and HD7 was 11.9 J/min [IQR 9.2-15.1], 13 J/min [IQR 10-17], and 14 J/min [IQR 11-20], respectively. MP was overall higher in patients with ARDS, especially those with higher ARDS severity. After controlling for same-day pressure of arterial oxygen/fraction of inspired oxygen (P/F ratio), BMI, and neurological severity, MP at HD1, HD3, and HD7 was independently associated with hospital mortality, reintubation and tracheostomy placement. The adjusted relative risk (aRR) was greater at higher MP, and strongest for: mortality on HD1 (compared to the HD1 median MP 11.9 J/min, aRR at 17 J/min was 1.22, 95% CI 1.14-1.30) and HD3 (1.38, 95% CI 1.23-1.53), reintubation on HD1 (1.64; 95% CI 1.57-1.72), and tracheostomy on HD7 (1.53; 95%CI 1.18-1.99). MP was associated with the development of moderate-severe ARDS on HD1 (2.07; 95% CI 1.56-2.78) and HD3 (1.76; 95% CI 1.41-2.22).ConclusionsExposure to high MP during the first week of MV is associated with poor clinical outcomes in ABI, independent of P/F ratio and neurological severity. Potential benefits of optimizing ventilator settings to limit MP warrant further investigation

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

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