Article Info Fungus/Allergen Size (kD) Biological Activity Sequence access number Penicillium brevicompactum Pen b 13 33 Alkaline serine protease * Pen b 26 11 Ribosomal acid protein 60S AY786077 Penicillium chrysogenum Pen ch 13 34 Alkaline serine protease AF193420 Pen ch 18 32 Vacuolar serine protease AF264027 Pen ch 20 68 N-acetyl-glucosaminidase S77837 Pen ch 31 Calreticulin AY850367 Pen ch 33 16 unknown EF206657.1 Pen ch 35 36.5 Transaldolase GQ925430 Penicillium citrinum Pen c 3 18 Peroxisomal membrane protein AF144753 Pen c 13 33 Alkaline serine protease * Pen c 19 70 Heat shock protein P70 U64207 Pen c 22 46 Enolase AF254643 Pen c 24 Elongation factor 1β AY363911 Pen c 30 97 Catalase DQ288844 Pen c 32 40 Pectate lyase EF159713 Penicillium crustosum Pen cr 26 11 Acid ribosomal phosphoprotein P1 60s JN791438 Penicillium oxalicum

The involvement of miRNA in mesial temporal lobe epilepsy (MTLE) pathogenesis has increasingly become a focus of epigenetic studies. Despite advances, the number of known miRNAs with a consistent expression response during epileptogenesis is still small. Addressing this situation requires additional miRNA profiling studies coupled to detailed individual expression analyses. Here, we perform a miRNA microarray analysis of the hippocampus of Wistar rats 24 hours after intra-hippocampal pilocarpine-induced Status Epilepticus (H-PILO SE). We identified 73 miRNAs that undergo significant changes, of which 36 were up-regulated and 37 were down-regulated. To validate, we selected 5 of these (10a-5p, 128a-3p, 196b-5p, 352 and 324-3p) for RT-qPCR analysis. Our results confirmed that miR-352 and 196b-5p levels were significantly higher and miR-128a-3p levels were significantly lower in the hippocampus of H-PILO SE rats. We also evaluated whether the 3 miRNAs show a dysregulated hippocampal expression at three time periods (0h, 24h and chronic phase) after systemic pilocarpine-induced status epilepticus (S-PILO SE). We demonstrate that miR-128a-3p transcripts are significantly reduced at all time points compared to the naïve group. Moreover, miR-196b-5p was significantly higher only at 24h post-SE, while miR-352 transcripts were significantly up-regulated after 24h and in chronic phase (epileptic) rats. Finally, when we compared hippocampi of epileptic and non-epileptic humans, we observed that transcript levels of miRNAs show similar trends to the animal models. In summary, we successfully identified two novel dysregulated miRNAs (196b-5p and 352) and confirmed miR-128a-3p downregulation in SE-induced epileptogenesis. Further functional assays are required to understand the role of these miRNAs in MTLE pathogenesis.

Neuropathological studies often use autopsy brain tissue as controls to evaluate changes in protein or RNA levels in several diseases. In mesial temporal lobe epilepsy (MTLE), several genes are up or down regulated throughout the epileptogenic and chronic stages of the disease. Given that postmortem changes in several gene transcripts could impact the detection of changes in case-control studies, we evaluated the effect of using autopsy specimens with different postmortem intervals (PMI) on differential gene expression of the Pilocarpine (PILO)induced Status Epilepticus (SE) of MTLE. For this, we selected six genes (Gfap, Ppia, Gad65, Gad67, Npy, and Tnf-α) whose expression patterns in the hippocampus of PILO-injected rats are well known. Initially, we compared hippocampal expression of naïve rats whose hippocampi were harvested immediately after death (0h-PMI) with those harvested at 6h postmortem interval (6h-PMI): Npy and Ppia transcripts increased and Tnf-α transcripts decreased in the 6h-PMI group (p<0.05). We then investigated if these PMI-related changes in gene expression have the potential to adulterate or mask RT-qPCR results obtained with PILO-injected rats euthanized at acute or chronic phases. In the acute group, Npy transcript was significantly higher when compared with 0h-PMI rats, whereas Ppia transcript was lower than 6h-PMI group. When we used epileptic rats (chronic group), the RT-qPCR results showed higher Tnf-α only when compared to 6h-PMI group. In conclusion, our study demonstrates that PMI influences gene transcription and can mask changes in gene transcription seen during epileptogenesis in the PILO-SE model. Thus, to avoid erroneous conclusions, we strongly recommend that researchers account for changes in postmortem gene expression in their experimental design.

Real-time quantitative RT-PCR (qPCR) is one of the most powerful techniques for analyzing miRNA expression because of its sensitivity and specificity. However, in this type of analysis, a suitable normalizer is required to ensure that gene expression is unaffected by the experimental condition. To the best of our knowledge, there are no reported studies that performed a detailed identification and validation of suitable reference genes for miRNA qPCR during the epileptogenic process. Here, using a pilocarpine (PILO) model of mesial temporal lobe epilepsy (MTLE), we investigated five potential reference genes, performing a stability expression analysis using geNorm and NormFinder softwares. As a validation strategy, we used each one of the candidate reference genes to measure PILO-induced changes in microRNA-146a levels, a gene whose expression pattern variation in the PILO injected model is known. Our results indicated U6SnRNA and SnoRNA as the most stable candidate reference genes. By geNorm analysis, the normalization factor should preferably contain at least two of the best candidate reference genes (snoRNA and U6SnRNA). In fact, when normalized using the best combination of reference genes, microRNA-146a transcripts were found to be significantly increased in chronic stage, which is consistent with the pattern reported in different models. Conversely, when reference genes were individually employed for normalization, we failed to detect up-regulation of the microRNA-146a gene in the hippocampus of epileptic rats. The data presented here support that the combination of snoRNA and U6SnRNA was the minimum necessary for an accurate normalization of gene expression at the different stages of epileptogenesis that we tested.

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Monitoring the microbiological quality of indoor air in hospital environments is a matter of comprehensive discussion due to its influence on the transmission and spread of pathogenic microorganisms. Among the artificially air-conditioned environments, hospitals are noteworthy for being specific places for the treatment and recovery of patients. In addition to problems related to patients health and professionals health, immunocompromised patients are more exposed to microorganisms present in the air currents of the refrigeration system in these environments, which can lead to consequences such as the occurrence of outbreaks. The objective of this work was to evaluate the indoor air quality in critical hospital environments of a teaching hospital in the city of Maceió, the state of Alagoas. In addition, we sought to identify the anemophilous fungal microbiota present. Air collections were taken in the rainy season, totaling, following recommendations indicated by Resolution No. 9 of the Brazilian National Health Surveillance Agency. The study was based on determining the concentration parameter of bioaerosols in indoor and outdoor air. The fungal microbiota identification was carried out by analyzing macro and microscopic characteristics for filamentous fungi and the use of molecular tools for yeasts. The most frequent species in hospital critical environments were Cladosporium cladosporioides, Penicillium piceum, Penicillium aurantiogriseum, Cladosporium herbarum and Aspergillus oryzae. In outdoor air, the most frequently found fungi were Penicillium sp., Aspergillus sp., and Cladosporium species. Candida tropicalis, C. krusei, and C. parapsilosis were identified among the yeasts in indoor and outdoor air samples. Identifying potentially pathogenic fungi in the evaluated environments points to the need for continuous monitoring of indoor air quality. Furthermore, to avoid the widespread fungal pathogens and the consequent occurrence of outbreaks, the adoption of indoor air microbiological quality analysis programs is suggested as an essential tool in developing infection control standards. In our study, airborne fungi are reported as indoor air contaminants in critical hospital environments. This finding is noteworthy because, in general, individuals present in these environments have an immunological impairment.

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Background: Fungi are ubiquitous microorganisms that are easily dispersed through the air. In healthcare environments, indoor air can favor the spread of healthcare-associated fungal infections, compromising mainly immunocompromised hospitalized individuals. Thus, this study aimed to evaluate the indoor air contamination in healthcare environments, investigating mainly the presence of potentially pathogenic yeasts. Methods: Indoor air samples were collected from twelve healthcare environments (hospital and medical clinics). After the growth, isolation, and purification of the yeast colonies, the isolates were identified by polymerase chain reaction using species-specific primers for yeasts of the genus Candida and sequencing of D1/D2 domains of the large ribosomal subunit (LSU rRNA). Results: Fourteen yeast species were identified, including emerging pathogens. Species of clinical importance such as Candida parapsilosis, Candida orthopsilosis, Candida glabrata, Rhodotorula mucilaginosa, and Trichosporon mucoides were present. C. Parapsilosis was the most prevalent species, followed by Rodothorula mucilaginosa. Conclusions: The present study shows that potentially fungal pathogens were present in air samples from healthcare environments, proving the role of indoor air in spreading infections. Thus, monitoring air quality in healthcare environments is a fundamental approach in developing infection control measures, especially those related to invasive fungal infections.