Potentiometric detection of low-levels of sulfamethazine in milk and pharmaceutical formulations using novel plastic membrane sensors

Novel potentiometric sensors for selective screening of sulfamethazine (SMZ) in pharmaceutical preparations and milk samples are reported. The sensor membranes were made from PVC matrix doped with magnesium(II)-, manganese(II)- and dichlorotin (IV)-phthalocyanines as ionophores and aliquat-336 and nitron/SMZ ion-pair complex as ion exchangers. These sensors revealed fast, stable and near-Nernstian anionic response for the singly charged sulfamethazine anion over the concentration range 10-2 - 10-5 M. The sensors exhibited good selectivity towards SMZ over most known anions, excipients and diluents commonly added in drug preparations. Validation of the proposed methods was demonstrated via evaluating the detection limit, linear response range, accuracy, precision (within-day repeatability) and between-day-variability. The sensors are easily interfaced with a double channel flow injection system and used for continuous monitoring of SMZ in drug formulations, spiked milk samples and biological tissues. The method offers the advantages of design simplicity, results accuracy, and automation feasibility

Dexmedetomidine- or Clonidine-Based Sedation Compared With Propofol in Critically Ill Patients

Importance Whether α2-adrenergic receptor agonist–based sedation, compared with propofol-based sedation, reduces time to extubation in patients receiving mechanical ventilation in the intensive care unit (ICU) is uncertain. Objective To evaluate whether dexmedetomidine- or clonidine-based sedation reduces duration of mechanical ventilation compared with propofol-based sedation (usual care). Design, Setting, and Participants Pragmatic, open-label randomized clinical trial conducted at 41 ICUs in the UK including adults who were within 48 hours of starting mechanical ventilation, were receiving propofol plus an opioid for sedation and analgesia, and were expected to require mechanical ventilation for 48 hours or longer. The median time from intubation to randomization was 21.0 (IQR, 13.2-31.3) hours. Recruitment occurred from December 2018 to October 2023; the last follow-up occurred on December 10, 2023. Interventions The bedside algorithms used targeted a Richmond Agitation-Sedation Scale score of −2 to 1 (unless clinicians requested deeper sedation). The algorithms supported uptitration in the dexmedetomidine- and clonidine-based sedation intervention groups and supported downtitration for propofol-based sedation followed by sedation primarily with the allocated sedation (dexmedetomidine or clonidine). If required, supplemental use of propofol was permitted. Main Outcomes and Measures The primary outcome was time from randomization to successful extubation. The secondary outcomes included mortality, sedation quality, rates of delirium, and cardiovascular adverse events. Results Among the 1404 patients in the analysis population (mean age, 59.2 [SD, 14.9] years; 901 [64%] were male; and the mean APACHE II score was 20.3 [SD, 8.2]), the subdistribution hazard ratio (HR) for time to successful extubation was 1.09 (95% CI, 0.96-1.25; P = .20) for dexmedetomidine (n = 457) vs propofol (n = 471) and was 1.05 (95% CI, 0.95-1.17; P = .34) for clonidine (n = 476) vs propofol (n = 471). The median time from randomization to successful extubation was 136 (95% CI, 117-150) hours for dexmedetomidine, 146 (95% CI, 124-168) hours for clonidine, and 162 (95% CI, 136-170) hours for propofol. In the predefined subgroup analyses, there were no interactions with age, sepsis status, median Sequential Organ Failure Assessment score, or median delirium risk score. Among the secondary outcomes, agitation occurred at a higher rate with dexmedetomidine vs propofol (risk ratio [RR], 1.54 [95% CI, 1.21-1.97]) and with clonidine vs propofol (RR, 1.55 [95% CI, 1.22-1.97]). Compared with propofol, the rates of severe bradycardia (heart rate <50/min) were higher with dexmedetomidine (RR, 1.62 [95% CI, 1.36-1.93]) and clonidine (RR, 1.58 [95% CI, 1.33-1.88]). Compared with propofol, mortality was similar over 180 days for dexmedetomidine (HR, 0.98 [95% CI, 0.77-1.24]) and clonidine (HR, 1.04 [95% CI, 0.82-1.31]). Conclusions and Relevance In critically ill patients, neither dexmedetomidine nor clonidine was superior to propofol in reducing time to successful extubation. Trial Registration ClinicalTrials.gov Identifier: NCT0365383

VirNet: Deep attention model for viral reads identification.

Metagenomics shows a promising understanding of function and diversity of the microbial communities due to the difficulty of studying microorganism with pure culture isolation. Moreover, the viral identification is considered one of the essential steps in studying microbial communities. Several studies show different methods to identify viruses in mixed metagenomic data using homology and statistical techniques. These techniques have many limitations due to viral genome diversity. In this work, we propose a deep attention model for viral identification of metagenomic data. For testing purpose, we generated fragments of viruses and bacteria from RefSeq genomes with different lengths to find the best hyperparameters for our model. Then, we simulated both microbiome and virome high throughput data from our test dataset with aim of validating our approach. We compared our tool to the state-of-the-art statistical tool for viral identification and found the performance of VirNet much better regarding accuracy on the same testing data

Intralesional Mitomycin C Injection in Management of Caustic Esophageal Stricture in Children

Abstract Background Corrosive ingestion is a devastating event that induces significant burdens on modern health systems worldwide. The management of resulting esophageal strictures is challenging where endoscopic dilatation is the first line of management with varying rate of success. Aim of the Work We aimed at this work to study the feasibility and safety of intralesional Mitomycin C injection in patients with caustic localized esophageal stricture. Patients and Methods This study has been conducted at Pediatric Surgery Department, Pediatric Hospital, Ain Shams University Hospitals on eight pediatric patients with caustic esophageal stricture with variable degrees of dysphagia. We evaluated the clinical improvement of the dysphagia, as well as the intra and postoperative complications of Mitomycin C injection. Results Eight patients with short caustic esophageal stricture were managed with intralesional Mitomycin C injection adjuvant to endoscopic dilatation. Seven patients were completely cured from dysphagia with at least 6 months dysphagia free period. No intraoperative complications were documented while there were two cases who reported GIT side effect postoperative in the form of colics and non-bilious vomiting that resolved by medical treatment. Conclusion Intralesional Mitomycin C injection could be a good adjuvant therapy with endoscopic dilatation for caustic esophageal stricture. However, long-term observations are mandatory on a large scale of patients. </jats:sec

Viral Sequence Identification in Metagenomes using Natural Language Processing Techniques

ABSTRACTViral reads identification is one of the important steps in metagenomic data analysis. It shows up the diversity of the microbial communities and the functional characteristics of microorganisms. There are various tools that can identify viral reads in mixed metagenomic data using similarity and statistical tools. However, the lack of available genome diversity is a serious limitation to the existing techniques. In this work, we applied natural language processing approaches for document classification in analyzing metagenomic sequences. Text featurization is presented by treating DNA similar to natural language. These techniques reveal the importance of using the text feature extraction pipeline in sequence identification by transforming DNA base pairs into a set of characters with a term frequency and inverse document frequency techniques. Various machine learning classification algorithms are applied to viral identification tasks such as logistic regression and multi-layer perceptron. Moreover, we compared classical machine learning algorithms with VirFinder and VirNet, our deep attention model for viral reads identification on generated fragments of viruses and bacteria for benchmarking viral reads identification tools. Then, as a verification of our tool, It was applied to a simulated microbiome and virome data for tool verification and real metagenomic data of Roche 454 and Illumina for a case study.</jats:p

MetaMap: An atlas of metatranscriptomic reads in human disease-related RNA-seq data

AbstractBackgroundWith the advent of the age of big data in bioinformatics, large volumes of data and high performance computing power enable researchers to perform re-analyses of publicly available datasets at an unprecedented scale. Ever more studies imply the microbiome in both normal human physiology and a wide range of diseases. RNA sequencing technology (RNA-seq) is commonly used to infer global eukaryotic gene expression patterns under defined conditions, including human disease-related contexts, but its generic nature also enables the detection of microbial and viral transcripts.FindingsWe developed a bioinformatic pipeline to screen existing human RNA-seq datasets for the presence of microbial and viral reads by re-inspecting the non-human-mapping read fraction. We validated this approach by recapitulating outcomes from 6 independent controlled infection experiments of cell line models and comparison with an alternative metatranscriptomic mapping strategy. We then applied the pipeline to close to 150 terabytes of publicly available raw RNA-seq data from &gt;17,000 samples from &gt;400 studies relevant to human disease using state-of-the-art high performance computing systems. The resulting data of this large-scale re-analysis are made available in the presented MetaMap resource.ConclusionsOur results demonstrate that common human RNA-seq data, including those archived in public repositories, might contain valuable information to correlate microbial and viral detection patterns with diverse diseases. The presented MetaMap database thus provides a rich resource for hypothesis generation towards the role of the microbiome in human disease.</jats:sec