Computational Approach to Identify Enzymes That Are Potential Therapeutic Candidates for Psoriasis

Psoriasis is well known as a chronic inflammatory dermatosis. The disease affects persons of all ages and is a burden worldwide. Psoriasis is associated with various diseases such as arthritis. The disease is characterized by well-demarcated lesions on the skin of the elbows and knees. Various genetic and environmental factors are related to the pathogenesis of psoriasis. In order to identify enzymes that are potential therapeutic targets for psoriasis, we utilized a computational approach, combining microarray analysis and protein interaction prediction. We found 6,437 genes (3,264 upregulated and 3,173 downregulated) that have significant differences in expression between regions with and without lesions in psoriasis patients. We identified potential candidates through protein-protein interaction predictions made using various protein interaction resources. By analyzing the hub protein of the networks with metrics such as degree and centrality, we detected 32 potential therapeutic candidates. After filtering these candidates through the ENZYME nomenclature database, we selected 5 enzymes: DNA helicase (RUVBL2), proteasome endopeptidase complex (PSMA2), nonspecific protein-tyrosine kinase (ZAP70), I-kappa-B kinase (IKBKE), and receptor protein-tyrosine kinase (EGFR). We adopted a computational approach to detect potential therapeutic targets; this approach may become an effective strategy for the discovery of new drug targets for psoriasis

Identification of protein functions using a machine-learning approach based on sequence-derived properties

<p>Abstract</p> <p>Background</p> <p>Predicting the function of an unknown protein is an essential goal in bioinformatics. Sequence similarity-based approaches are widely used for function prediction; however, they are often inadequate in the absence of similar sequences or when the sequence similarity among known protein sequences is statistically weak. This study aimed to develop an accurate prediction method for identifying protein function, irrespective of sequence and structural similarities.</p> <p>Results</p> <p>A highly accurate prediction method capable of identifying protein function, based solely on protein sequence properties, is described. This method analyses and identifies specific features of the protein sequence that are highly correlated with certain protein functions and determines the combination of protein sequence features that best characterises protein function. Thirty-three features that represent subtle differences in local regions and full regions of the protein sequences were introduced. On the basis of 484 features extracted solely from the protein sequence, models were built to predict the functions of 11 different proteins from a broad range of cellular components, molecular functions, and biological processes. The accuracy of protein function prediction using random forests with feature selection ranged from 94.23% to 100%. The local sequence information was found to have a broad range of applicability in predicting protein function.</p> <p>Conclusion</p> <p>We present an accurate prediction method using a machine-learning approach based solely on protein sequence properties. The primary contribution of this paper is to propose new <it>PNPRD </it>features representing global and/or local differences in sequences, based on positively and/or negatively charged residues, to assist in predicting protein function. In addition, we identified a compact and useful feature subset for predicting the function of various proteins. Our results indicate that sequence-based classifiers can provide good results among a broad range of proteins, that the proposed features are useful in predicting several functions, and that the combination of our and traditional features may support the creation of a discriminative feature set for specific protein functions.</p

Structural dynamics and divergence of the polygalacturonase gene family in land plants

A distinct feature of eukaryotic genomes is the presence of gene families. The polygalacturonase (PG) (EC3.2.1.15) gene family is one of the largest gene families in plants. PG is a pectin-digesting enzyme with a glycoside hydrolase 28 domain. It is involved in numerous plant developmental processes. The evolutionary processes accounting for the functional divergence and the specialized functions of PGs in land plants are unclear. Here, phylogenetic and gene structure analysis of PG genes in algae and land plants revealed that land plant PG genes resulted from differential intron gain and loss, with the latter event predominating. PG genes in land plants contained 15 homologous intron blocks and 13 novel intron blocks. Intron position and phase were not conserved between PGs of algae and land plants but conserved among PG genes of land plants from moss to vascular plants, indicating that the current introns in the PGs in land plants appeared after the split between unicellular algae and multicelluar land plants. These findings demonstrate that the functional divergence and differentiation of PGs in land plants is attributable to intronic loss. Moreover, they underscore the importance of intron gain and loss in genomic adaptation to selective pressure

Cost-effectiveness of a medication event monitoring system for tuberculosis management in Morocco

BACKGROUND: Digital health technologies have been used to enhance adherence to TB medication, but the cost-effectiveness remains unclear. METHODS: We used the real data from the study conducted from April 2014 to December 2020 in Morocco using a smart pillbox with a web-based medication monitoring system, called Medication Event Monitoring Systems (MEMS). Cost-effectiveness was evaluated using a decision analysis model including Markov model for Multi-drug resistant (MDR) TB from the health system perspective. The primary outcome was the incremental cost-effectiveness ratio (ICER) per disability adjusted life-year (DALY) averted. Two-way sensitive analysis was done for the treatment success rate between MEMS and standard of care. RESULTS: The average total per-patient health system costs for treating a new TB patient under MEMS versus standard of care were $398.70 and$155.70, respectively. The MEMS strategy would reduce the number of drug-susceptible TB cases by 0.17 and MDR-TB cases by 0.01 per patient over five years. The ICER of MEMS was $434/DALY averted relative to standard of care, and was most susceptible to the TB treatment success rate of both strategies followed by the managing cost of MEMS. CONCLUSION: MEMS is considered cost-effective for managing infectious active TB in Morocco

Electrical current suppression in Pd-doped vanadium pentoxide nanowires caused by reduction in PdO due to hydrogen exposure

Pd nanoparticle-doped vanadium pentoxide nanowires (Pd-VONs) were synthesized. Electrical current suppression was observed when the Pd-VON was exposed to hydrogen gas, which cannot be explained by the work function changes mentioned in previous report such as Pd-doped carbon nanotubes and SnO 2 nanowires. Using the x-ray photoelectron spectroscopy, we found that the reduction in PdO due to hydrogen exposure plays an important role in the current suppression of the Pd-VON.open4

Vasoactive-inotropic score as a predictor of in-hospital mortality in out-of-hospital cardiac arrest

Background: The Vasoactive-Inotropic Score (VIS) is an objective clinical tool used to quantify the need for cardiovascular support in children and adolescents after surgery and to predict prognosis of pediatric septic shock. Considering the post-cardiac arrest syndrome (PCAS) is a sepsis-like syndrome, we aimed to investigate the correlation between VIS and in-hospital mortality in out-of-hospital cardiac arrest (OHCA) patients who achieved a sustained return of spontaneous circulation (ROSC) and admitted to the intensive care unit (ICU). Methods: A retrospective chart review of 504 OHCA patients who were admitted to the emergency room with OHCA from Jan 2015 to Dec 2016 was done. VIS was calculated with the recorded administration rate of the drugs on electronic medical record at the same time during the first 24 hours in ICU. The highest value of VIS in 24 hours (24hr-peak VIS) was used for investigating the correlation between VIS and in-hospital mortality. Results: Among 504 OHCA patients, 166 patients were admitted to the intensive care unit and 116 patients died during hospital stay. The probability of in-hospital mortality was significantly higher when 24hr-peak VIS was higher than 33.3 [Odds ratio (OR) = 3.18, 95% CI = 1.22 – 8.29, p value = 0.018]. Conclusion: 24hr-Peak VIS could be a good scoring system for predicting in-hospital mortality in OHCA patients who admitted to ICU. The AUC was 0.762 (95% CI = 0.690 to 0.825) and the optimal cut-off values were 33.3 (sensitivity 0.764, specificity 0.610)

Characteristics of Mechanical Ventilation Employed in Intensive Care Units: A Multicenter Survey of Hospitals

A 1D point-prevalence study was performed to describe the characteristics of conventional mechanical ventilation in intensive care units (ICUs). In addition, a survey was conducted to determine the characteristics of ICUs. A prospective, multicenter study was performed in ICUs at 24 university hospitals. The study population consisted of 223 patients who were receiving mechanical ventilation or had been weaned off mechanical ventilation within the past 24 hr. Common indications for the initiation of mechanical ventilation included acute respiratory failure (66%), acute exacerbation of chronic respiratory failure (15%) (including tuberculosis-destroyed lung [5%]), coma (13%), and neuromuscular disorders (6%). Mechanical ventilation was delivered via an endotracheal tube in 68% of the patients, tracheostomy in 28% and facial mask with noninvasive ventilation (NIV) in 4%. NIV was used in 2 centers. In patients who had undergone tracheostomy, the procedure had been performed 16.9±8.1 days after intubation. Intensivists treated 29% of the patients. A need for additional educational programs regarding clinical practice in the ICU was expressed by 62% of the staff and 42% of the nurses. Tuberculosis-destroyed lung is a common indication for mechanical ventilation in acute exacerbation of chronic respiratory failure, and noninvasive ventilation was used in a limited number of ICUs

Case study on high-resolution monitoring network of groundwater heat pump system

With the increasing installation of shallow geothermal energy, the importance of thermal impact prediction also increases in the system design stage. In nature, it is general that heterogeneity exists and it can affect the groundwater flow as well as the transport along to the flow. When predicting heat transport under the groundwater heat pump (GWHP) operation, however, impacts of heterogeneity have rarely been considered. In this study, to detect the hydraulic and thermal feedback to the two months of GWHP operation, a dense monitoring network was constructed with 12 monitoring wells at Eumseong-gun, Republic of Korea. The temperature was monitored in high resolution via fiber-optic distributed temperature sensing. During the GWHP operation, a very dynamic flow condition was generated with the hydraulic gradient between 0.005 and 0.07. The maximum temperature change at the nearest monitoring well was 2 ?. Observed hydraulic and thermal responses showed spatially heterogeneous results. While the heterogeneous responses of hydraulic change were stronger near the geothermal wells, those of temperature change were higher near the center of the thermal plume