Immunoinformatic analysis of the whole proteome for vaccine design: An application to Clostridium perfringens.

Clostridium perfringens is a dangerous bacterium and known biological warfare weapon associated with several diseases, whose lethal toxins can produce necrosis in humans. However, there is no safe and fully effective vaccine against C. perfringens for humans yet. To address this problem, we computationally screened its whole proteome, identifying highly immunogenic proteins, domains, and epitopes. First, we identified that the proteins with the highest epitope density are Collagenase A, Exo-alpha-sialidase, alpha n-acetylglucosaminidase and hyaluronoglucosaminidase, representing potential recombinant vaccine candidates. Second, we further explored the toxins, finding that the non-toxic domain of Perfringolysin O is enriched in CTL and HTL epitopes. This domain could be used as a potential sub-unit vaccine to combat gas gangrene. And third, we designed a multi-epitope protein containing 24 HTL-epitopes and 34 CTL-epitopes from extracellular regions of transmembrane proteins. Also, we analyzed the structural properties of this novel protein using molecular dynamics. Altogether, we are presenting a thorough immunoinformatic exploration of the whole proteome of C. perfringens, as well as promising whole-protein, domain-based and multi-epitope vaccine candidates. These can be evaluated in preclinical trials to assess their immunogenicity and protection against C. perfringens infection.

Leukocyte glucose index as a novel biomarker for COVID-19 severity.

The severity of coronavirus disease 2019 (COVID-19) quickly progresses with unfavorable outcomes due to the host immune response and metabolism alteration. Hence, we hypothesized that leukocyte glucose index (LGI) is a biomarker for severe COVID-19. This study involved 109 patients and the usefulness of LGI was evaluated and compared with other risk factors to predict COVID 19 severity. LGI was identified as an independent risk factor (odds ratio [OR] = 1.727, 95% confidence interval [CI]: 1.026-3.048, P = 0.041), with an area under the curve (AUC) of 0.749 (95% CI: 0.642-0.857, P < 0.0001). Interestingly, LGI was a potential risk factor (OR = 2.694, 95% CI: 1.575-5.283, Pcorrected < 0.05) for severe COVID-19 in female but not in male patients. In addition, LGI proved to be a strong predictor of the severity in patients with diabetes (AUC = 0.915 (95% CI: 0.830-1), sensitivity = 0.833, and specificity = 0.931). The AUC of LGI, together with the respiratory rate (LGI + RR), showed a considerable improvement (AUC = 0.894, 95% CI: 0.835-0.954) compared to the other biochemical and respiratory parameters analyzed. Together, these findings indicate that LGI could potentially be used as a biomarker of severity in COVID-19 patients.

Compendium of human transcription factor effector domains.

Transcription factors (TFs) regulate gene expression by binding to DNA sequences and modulating transcriptional activity through their effector domains. Despite the central role of effector domains in TF function, there is a current lack of a comprehensive resource and characterization of effector domains. Here, we provide a catalog of 924 effector domains across 594 human TFs. Using this catalog, we characterized the amino acid composition of effector domains, their conservation across species and across the human population, and their roles in human diseases. Furthermore, we provide a classification system for effector domains that constitutes a valuable resource and a blueprint for future experimental studies of TF effector domain function.

Tear biomarkers and corneal sensitivity as an indicator of neuropathy in type 2 diabetes.

AIMS: Explore potential of 31 tear biomarkers involved in screening for diabetic peripheral neuropathy (DPN). Assess the utility of aesthesiometry for measuring corneal damage in DPN and determine optimal cutoff point for detecting DPN. METHODS: Screening test pilot study recruited 90 participants from a tertiary hospital in Lima, Peru. Participants were grouped by diabetes and neuropathy status. Tears collected on Schirmer strips, and proteins measured by both ELISA and multiplex-bead assay. Corneal sensitivity was measured by aesthesiometry, and DPN by vibration perception threshold testing. RESULTS: There were 89 participants included in the analysis. The mean age was 55.7 ± 1.46, and 58.4% were female. MMP-9 and TGF-alpha concentrations were higher in participants with DPN versus diabetes alone, though not significant. Aesthesiometry was decreased in individuals with DPN when compared to participants with diabetes alone (p < 0.01) and normal controls (p < 0.01). Optimal cutoff point for aesthesiometry was found to be 5.8 cm, with 79% sensitivity and 75% specificity. CONCLUSIONS: Tears are an insufficient standalone tool for detecting DPN based on the biomarkers analyzed. Aesthesiometry is a simple, inexpensive, and accurate method to assess corneal damage associated with moderate-severe DPN, and its integration into screening practices has potential to improve detection of DPN in poor-resource settings.

Mathematical modeling and computational analysis of centrifugal microfluidic platforms: a review.

Centrifugal microfluidic platforms or lab-on-discs (LODs) have evolved into a popular technology for automating chemical and biological assays. LODs today enable scientists to implement and integrate different operational units, including fluid mixing, droplet generation, cell-sorting, gene amplification, analyte detection, and so forth. For an efficient design and cost-effective implementation of any microfluidic device, including LODs, theoretical analysis and considerations should play a more important role than they currently do. The theoretical analysis we will show is especially essential to the investigation of detailed phenomena at the small length scales and high-speed typical for LODs where a wide range of forces may be involved. Previous LOD review papers presented mostly experimental results with theory as an afterthought. Hence, a review paper focused on the theoretical aspects, and associated computational studies of LOD devices is an urgent need. In the present review paper, all previous computational studies on LOD devices are categorized as single-phase flows, two-phase flows, network simulation, and solids. For each of these categories, the governing equations and important formulas are presented and explained. Moreover, a handy scaling analysis is introduced to aid scientists when comparing different competing forces in LOD devices. We hope that by surveying and contrasting various theoretical LOD studies, we shed some light on existing controversies and reveal where additional theoretical work is needed.