Microbiological profile and infection potential of different cryopreserved skull flaps after decompressive hemicraniectomy. Is cryopreservation at - 80℃ better?

Agrawal R, Rompf C, Pranada AB, et al. Microbiological profile and infection potential of different cryopreserved skull flaps after decompressive hemicraniectomy. Is cryopreservation at - 80℃ better? BMC Research Notes . 2022;15(1): 167.OBJECTIVE: Patterns of cryopreservation of explanted skull bone flaps have long been a matter of debate, in particular the appropriate temperature of storage. To the best of our knowledge no study to date has compared the microbiological profile and the infection potential of skull bone flaps cryostored at the same institution at disparate degrees for neurosurgical purposes. In the context of our clinical trial DRKS00023283, we performed a bacterial culture of explanted skull bone flaps, which were cryopreserved lege artis at a temperature of either - 23°C or - 80°C after a decompressive hemicraniectomy. In a further step, we contaminated the bone fragments in a s uspension with specific pathogens (S. aureus, S. epidermidis and C. acnes, Colony forming unit CFU 103/ml) over 24h and conducted a second culture.; RESULTS: A total of 17 cryopreserved skull flaps (8: - 23°C; 9: - 80°C) explanted during decompressive hemicraniectomies performed between 2019 and 2020 as well as 2 computer-aided-designed skulls (1 vancomycin-soaked) were analyzed. Median duration of cryopreservation was 10.5months (2-17months). No microorganisms were detected at the normal bacterial culture. After active contamination of our skull flaps, all samples showed similar bacterial growth of above-mentioned pathogens; thus, our study did not reveal an influence of the storage temperature upon infectious dynamic of the skulls. © 2022. The Author(s)

Level of adherence to home-based exercise program among patients with mechanical low back pain in selected affiliated rehabilitation centers of De La Salle Health Sciences Institute in Cavite

The study used a descriptive-survey type of questionnaire that was published in English and was translated to Filipino. Preset of 19 patients were chosen by purposive sampling and met the inclusion criteria. The data collected from the survey questionnaire was tallied into frequency distribution table and analyzed descriptively. Based on the results of this study, the most adherent to HBEP as to socio-demographic profile were as follows: within 21-25 age groups, female, married and post graduates. As to clinical profile, the most adherent were patients with LBP for seven (7) to eight (8) months, pain scale of 8/10, had access to equipment and received support from health care provider. As to components of HBEP, the most adherent were prescribed with low intensity exercises with duration of 31-45 minutes, frequency of 5x a week and received written instructions for the home exercises. Overall, the result of the study proved that patients with mechanical LBP have a moderate level of adherence to their HBEP with a mean score of 2.35. This study recommends HBEP composed of low intensity exercises for 31-45 minutes, 5x a week with appropriate written instructions

The angiogenesis suppressor gene AKAP12 is under the epigenetic control of HDAC7 in endothelial cells.

Histone deacetylases (HDACs) are a family of 18 enzymes that deacetylate lysine residues of both histone and nonhistone proteins and to a large extent govern the process of angiogenesis. Previous studies have shown that specific inhibition of HDAC7 blocks angiogenesis both in vitro and in vivo. However, the underlying molecular mechanisms are not fully understood and hence preclude any meaningful development of suitable therapeutic modalities. The goal of the present study was to further the understanding of HDAC7 epigenetic control of angiogenesis in human endothelial cells using the proteomic approach. The underlying problem was approached through siRNA-mediated gene-expression silencing of HDAC7 in human umbilical vein endothelial cells (HUVECs). To this end, HUVEC proteins were extracted and proteomically analyzed. The emphasis was placed on up-regulated proteins, as these may represent potential direct epigenetic targets of HDAC7. Among several proteins, A-kinase anchor protein 12 (AKAP12) was the most reproducibly up-regulated protein following HDAC7 depletion. This overexpression of AKAP12 was responsible for the inhibition of migration and tube formation in HDAC7-depleted HUVEC. Mechanistically, H3 histones associated with AKAP12 promoter were acetylated following the removal of HDAC7, leading to an increase in its mRNA and protein levels. AKAP12 is responsible for protein kinase C mediated phosphorylation of signal transducer and activator of transcription 3 (STAT3). Phosphorylated STAT3 increasingly binds to the chromatin and AKAP12 promoter and is necessary for maintaining the elevated levels of AKAP12 following HDAC7 knockdown. We demonstrated for the first time that AKAP12 tumor/angiogenesis suppressor gene is an epigenetic target of HDAC7, whose elevated levels lead to a negative regulation of HUVEC migration and inhibit formation of tube-like structures

Multicentre study on the reproducibility of MALDI-TOF MS for nontuberculous mycobacteria identification.

The ability of MALDI-TOF for the identification of nontuberculous mycobacteria (NTM) has improved recently thanks to updated databases and optimized protein extraction procedures. Few multicentre studies on the reproducibility of MALDI-TOF have been performed so far, none on mycobacteria. The aim of this study was to evaluate the reproducibility of MALDI-TOF for the identification of NTM in 15 laboratories in 9 European countries. A total of 98 NTM clinical isolates were grown on Löwenstein-Jensen. Biomass was collected in tubes with water and ethanol, anonymized and sent out to the 15 participating laboratories. Isolates were identified using MALDI Biotyper (Bruker Daltonics). Up to 1330 MALDI-TOF identifications were collected in the study. A score ≥ 1.6 was obtained for 100% of isolates in 5 laboratories (68.2-98.6% in the other). Species-level identification provided by MALDI-TOF was 100% correct in 8 centres and 100% correct to complex-level in 12 laboratories. In most cases, the misidentifications obtained were associated with closely related species. The variability observed for a few isolates could be due to variations in the protein extraction procedure or to MALDI-TOF system status in each centre. In conclusion, MALDI-TOF showed to be a highly reproducible method and suitable for its implementation for NTM&nbsp;identification.</p

How to: identify non-tuberculous Mycobacterium species using MALDI-TOF mass spectrometry.

The implementation of MALDI-TOF MS for microorganism identification has changed the routine of the microbiology laboratories as we knew it. Most microorganisms can now be reliably identified within minutes using this inexpensive, user-friendly methodology. However, its application in the identification of mycobacteria isolates has been hampered by the structure of their cell wall. Improvements in the sample processing method and in the available database have proved key factors for the rapid and reliable identification of non-tuberculous mycobacteria isolates using MALDI-TOF MS. The main objective is to provide information about the proceedings for the identification of non-tuberculous isolates using MALDI-TOF MS and to review different sample processing methods, available databases, and the interpretation of the results. Results from relevant studies on the use of the available MALDI-TOF MS instruments, the implementation of innovative sample processing methods, or the implementation of improved databases are discussed. Insight about the methodology required for reliable identification of non-tuberculous mycobacteria and its implementation in the microbiology laboratory routine is provided. Microbiology laboratories where MALDI-TOF MS is available can benefit from its capacity to identify most clinically interesting non-tuberculous mycobacteria in a rapid, reliable, and inexpensive manner

Machine learning-based typing of Salmonella enterica O-serogroups by the Fourier-Transform Infrared (FTIR) Spectroscopy-based IR Biotyper system

Background: Salmonella enterica is among the major burdens for public health at global level. Typing of salmonellae below the species level is fundamental for different purposes, but traditional methods are expensive, technically demanding, and time-consuming, and therefore limited to reference centers. Fourier transform infrared (FTIR) spectroscopy is an alternative method for bacterial typing, successfully applied for classification at different infra-species levels. Aim: This study aimed to address the challenge of subtyping Salmonella enterica at O-serogroup level by using FTIR spectroscopy. We applied machine learning to develop a novel approach for S. enterica typing, using the FTIR-based IR Biotyper® system (IRBT; Bruker Daltonics GmbH & Co. KG, Germany). We investigated a multicentric collection of isolates, and we compared the novel approach with classical serotyping-based and molecular methods. Methods: A total of 958 well characterized Salmonella isolates (25 serogroups, 138 serovars), collected in 11 different centers (in Europe and Japan), from clinical, environmental and food samples were included in this study and analyzed by IRBT. Infrared absorption spectra were acquired from water-ethanol bacterial suspensions, from culture isolates grown on seven different agar media. In the first part of the study, the discriminatory potential of the IRBT system was evaluated by comparison with reference typing method/s. In the second part of the study, the artificial intelligence capabilities of the IRBT software were applied to develop a classifier for Salmonella isolates at serogroup level. Different machine learning algorithms were investigated (artificial neural networks and support vector machine). A subset of 88 pre-characterized isolates (corresponding to 25 serogroups and 53 serovars) were included in the training set. The remaining 870 samples were used as validation set. The classifiers were evaluated in terms of accuracy, error rate and failed classification rate. Results: The classifier that provided the highest accuracy in the cross-validation was selected to be tested with four external testing sets. Considering all the testing sites, accuracy ranged from 97.0% to 99.2% for non-selective media, and from 94.7% to 96.4% for selective media. Conclusions: The IRBT system proved to be a very promising, user-friendly, and cost-effective tool for Salmonella typing at serogroup level. The application of machine learning algorithms proved to enable a novel approach for typing, which relies on automated analysis and result interpretation, and it is therefore free of potential human biases. The system demonstrated a high robustness and adaptability to routine workflows, without the need of highly trained personnel, and proving to be suitable to be applied with isolates grown on different agar media, both selective and unselective. Further tests with currently circulating clinical, food and environmental isolates would be necessary before implementing it as a potentially stand-alone standard method for routine use

How To: Identify Non-Tuberculous Mycobacterium Species By Using Maldi-Tof Mass Spectrometry.

&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;The implementation of MALDI-TOF MS for microorganism identification has changed the routine of the microbiology laboratories as we knew it. Most microorganisms can now be reliably identified within minutes using this inexpensive, user-friendly methodology. However, its application on the identification of mycobacteria isolates has been hampered by the structure of their cell wall. Improvements in the sample processing method and in the available database have proved key factors for the rapid and reliable identification of non-tuberculous mycobacteria isolates using MALDI-TOF MS AIMS: The main objective is to provide information about the proceedings for the identification of non-tuberculous isolates using MALDI-TOF MS and to review different sample processing methods, available databases and the interpretation of the results.&lt;/p&gt; &lt;p&gt;&lt;b&gt;SOURCES: &lt;/b&gt;Results from relevant studies on the use of the available MALDI-TOF MS instruments, the implementation of innovative sample processing methods or the implementation of improved databases are discussed.&lt;/p&gt; &lt;p&gt;&lt;b&gt;CONTENT: &lt;/b&gt;Insight about the methodology required for reliable identification of non-tuberculous mycobacteria and its implementation in the microbiology laboratory routine is provided.&lt;/p&gt; &lt;p&gt;&lt;b&gt;IMPLICATIONS: &lt;/b&gt;Microbiology laboratories where MALDI-TOF MS is available can benefit from its capacity to identify most clinically interesting non-tuberculous mycobacteria in a rapid, reliable and inexpensive manner.&lt;/p&gt;</p

Machine learning-based typing of Salmonella enterica O-serogroups by the Fourier-Transform Infrared (FTIR) Spectroscopy-based IR Biotyper system

Background: Salmonella enterica is among the major burdens for public health at global level. Typing of salmonellae below the species level is fundamental for different purposes, but traditional methods are expensive, technically demanding, and time-consuming, and therefore limited to reference centers. Fourier transform infrared (FTIR) spectroscopy is an alternative method for bacterial typing, successfully applied for classification at different infra-species levels. Aim: This study aimed to address the challenge of subtyping Salmonella enterica at O-serogroup level by using FTIR spectroscopy. We applied machine learning to develop a novel approach for S. enterica typing, using the FTIR-based IR Biotyper® system (IRBT; Bruker Daltonics GmbH & Co. KG, Germany). We investigated a multicentric collection of isolates, and we compared the novel approach with classical serotyping-based and molecular methods. Methods: A total of 958 well characterized Salmonella isolates (25 serogroups, 138 serovars), collected in 11 different centers (in Europe and Japan), from clinical, environmental and food samples were included in this study and analyzed by IRBT. Infrared absorption spectra were acquired from water-ethanol bacterial suspensions, from culture isolates grown on seven different agar media. In the first part of the study, the discriminatory potential of the IRBT system was evaluated by comparison with reference typing method/s. In the second part of the study, the artificial intelligence capabilities of the IRBT software were applied to develop a classifier for Salmonella isolates at serogroup level. Different machine learning algorithms were investigated (artificial neural networks and support vector machine). A subset of 88 pre-characterized isolates (corresponding to 25 serogroups and 53 serovars) were included in the training set. The remaining 870 samples were used as validation set. The classifiers were evaluated in terms of accuracy, error rate and failed classification rate. Results: The classifier that provided the highest accuracy in the cross-validation was selected to be tested with four external testing sets. Considering all the testing sites, accuracy ranged from 97.0% to 99.2% for non-selective media, and from 94.7% to 96.4% for selective media. Conclusions: The IRBT system proved to be a very promising, user-friendly, and cost-effective tool for Salmonella typing at serogroup level. The application of machine learning algorithms proved to enable a novel approach for typing, which relies on automated analysis and result interpretation, and it is therefore free of potential human biases. The system demonstrated a high robustness and adaptability to routine workflows, without the need of highly trained personnel, and proving to be suitable to be applied with isolates grown on different agar media, both selective and unselective. Further tests with currently circulating clinical, food and environmental isolates would be necessary before implementing it as a potentially stand-alone standard method for routine use