Exploring indoor and outdoor dust as a potential tool for detection and monitoring of COVID-19 transmission

This study investigated the potential of using SARS-CoV-2 viral concentrations in dust as an additional surveillance tool for early detection and monitoring of COVID-19 transmission. Dust samples were collected from 8 public locations in 16 districts of Bangkok, Thailand, from June to August 2021. SARS-CoV-2 RNA concentrations in dust were quantified, and their correlation with community case incidence was assessed. Our findings revealed a positive correlation between viral concentrations detected in dust and the relative risk of COVID-19. The highest risk was observed with no delay (0-day lag), and this risk gradually decreased as the lag time increased. We observed an overall decline in viral concentrations in public places during lockdown, closely associated with reduced human mobility. The effective reproduction number for COVID-19 transmission remained above one throughout the study period, suggesting that transmission may persist in locations beyond public areas even after the lockdown measures were in place.

Wastewater-based epidemiological surveillance of SARS-CoV-2 new variants BA.2.86 and offspring JN.1 in south and Southeast Asia

Discover the shifting landscape of SARS-CoV-2 variants from October to December 2023, with JN.1 dominating South and Southeast Asia wastewater samples, increasing from < 10% to over 90%. Experience the dynamic evolution of viral strains in this period.

Tracing the transmission of mpox through wastewater surveillance in Southeast Asia

High population density and tourism in Southeast Asia increase the risk of mpox due to frequent interpersonal contacts. Our wastewater surveillance in six Southeast Asian countries revealed positive signals for Monkeypox virus (MPXV) DNA, indicating local transmission. This alerts clinicians and helps allocate resources like testing, vaccines and therapeutics in resource-limited countries.

Ca-EDTA restores the activity of ceftazidime-avibactam or aztreonam against carbapenemase-producing Klebsiellapneumoniae infections

Developing an effective therapy to overcome carbapenemase-positive Klebsiella pneumoniae (CPKp) is an important therapeutic challenge that must be addressed urgently. Here, we explored a Ca-EDTA combination with aztreonam or ceftazidime-avibactam in vitro and in vivo against diverse CPKp clinical isolates. The synergy testing of this study demonstrated that novel aztreonam-Ca-EDTA or ceftazidime-avibactam-Ca-EDTA combination was significantly effective in eliminating planktonic and mature biofilms in vitro, as well as eradicating CPKp infections in vivo. Both combinations revealed significant therapeutic efficacies in reducing bacterial load in internal organs and protecting treated mice from mortality. Conclusively, this is the first in vitro and in vivo study to demonstrate that novel aztreonam-Ca-EDTA or ceftazidime-avibactam-Ca-EDTA combinations provide favorable efficacy and safety for successful eradication of carbapenemase-producing Klebsiella pneumoniae planktonic and biofilm infections.

COVID-19 monitoring with sparse sampling of sewered and non-sewered wastewater in urban and rural communities

Equitable SARS-CoV-2 surveillance in low-resource communities lacking centralized sewers is critical as wastewater-based epidemiology (WBE) progresses. However, large-scale studies on SARS-CoV-2 detection in wastewater from low-and middle-income countries is limited because of economic and technical reasons. In this study, wastewater samples were collected twice a month from 186 urban and rural subdistricts in nine provinces of Thailand mostly having decentralized and non-sewered sanitation infrastructure and analyzed for SARS-CoV-2 RNA variants using allele-specific RT-qPCR. Wastewater SARS-CoV-2 RNA concentration was used to estimate the real-time incidence and time-varying effective reproduction number (Re). Results showed an increase in SARS-CoV-2 RNA concentrations in wastewater from urban and rural areas 14-20 days earlier than infected individuals were officially reported. It also showed that community/food markets were "hot spots" for infected people. This approach offers an opportunity for early detection of transmission surges, allowing preparedness and potentially mitigating significant outbreaks at both spatial and temporal scales.

Antimicrobial peptides recognition using weighted physicochemical property encoding

Antimicrobial resistance is a major public health concern. Antimicrobial peptides (AMPs) are one of the host defense mechanisms responding efficiently against multidrug-resistant microbes. Since the process of screening AMPs from a large number of peptides is still high-priced and time-consuming, the development of a precise and rapid computer-aided tool is essential for preliminary AMPs selection ahead of laboratory experiments. In this study, we proposed AMPs recognition models using a new peptide encoding method called amino acid index weight (AAIW). Four AMPs recognition models including antimicrobial, antibacterial, antiviral, and antifungal were trained based on datasets combined from the DRAMP and other published databases. These models achieved high performance compared to the preceding AMPs recognition models when evaluated on two independent test sets. All four models yielded over 93% in accuracy and 0.87 in Matthew's correlation coefficient (MCC). An online AMPs recognition server is accessible at https://amppred-aaiw.com.

Multiple traces of monkeypox detected in non-sewered wastewater with sparse sampling from a densely populated metropolitan area in Asia

The monkeypox virus is excreted in the feces of infected individuals. Therefore, there is an interest in using viral load detection in wastewater for sentinel early surveillance at a community level and as a complementary approach to syndromic surveillance. We collected wastewater from 63 sewered and non-sewered locations in Bangkok city center between May and August 2022. Monkeypox viral DNA copy numbers were quantified using real-time polymerase chain reaction (PCR) and confirmed positive by Sanger sequencing. Monkeypox viral DNA was first detected in wastewater from the second week of June 2022, with a mean copy number of 16.4 copies/ml (n = 3). From the first week of July, the number of viral DNA copies increased to a mean copy number of 45.92 copies/ml. Positive samples were Sanger sequenced and confirmed the presence of the monkeypox virus. Our study is the first to detect monkeypox viral DNA in wastewater from various locations within Thailand. Results suggest that this could be a complementary source for detecting viral DNA and predicting upcoming outbreaks.

1355. Cluster of Multi-drug Resistance Neisseria gonorrhoeae Isolates with Reduce Ceftriaxone Susceptibility, First Report in Thailand

Background

Rapid emergence of global azithromycin resistance, with ceftriaxone reduce susceptibility/resistant strains, threatens the current recommends dual therapy with ceftriaxone and azithromycin for gonorrhea to ensure effective treatment. Thailand is a major risk area for gonorrhea because it as a key destination for sex tourism industry, where antibiotic resistance gonorrhea can spread easily and quickly across the region. Here, we identified a first cluster of Neisseria gonorrhoeae isolates with decreased ceftriaxone susceptibility in Thailand.

Methods

A 134 N. gonorrhoeae isolates collected from Thai Red Cross Anonymous Clinic, Bangkok, during 2016–2018 were studied. Broth micro-dilution and plate dilution methods to define resistance or decreased susceptibilityaccording to CLSI guidelines. Select isolates were subjected to whole genome sequencing with an Illumina MiSeq V2 instrument and analysis using CLCBio Genomics Workbench v6.5. Molecular docking studies were carried out to understand binding mode analysis and orientation of ceftriaxone in the active site of PBP2. Biofilm formation measured by confocal laser scanning microscopy.

Results

Among the N. gonorrhoeae clinical isolates, two isolates had significant reduced susceptibility to ceftriaxone (MICs of 0.125 mg/L), which were isolated from urethral swab in male heterosexual patients. Both were multidrug resistance and strong biofilm producers with ceftriaxone tolerance (MBEC > 128 mg/L). One isolate was resistant to azithromycin (MIC of 1 mg/L), and other one remained susceptible (MIC of 0.5 mg/L). Reduced susceptibility to ceftriaxone associated with alterations in PBP2, PBP1, PorB, MtrR, and mtrR promoter region with one belonged to ST7235 and second one had new allele number of tbpB with new sequence type (ST). Ceftriaxone weakly occupy the active site of mosaic XXXIV penicillin-binding protein 2 (PBP2) variant in both. Molecular epidemiology results reviled that both isolates display similarities with isolates from UK, USA, and Netherlands.

Conclusion

This first cluster of genetically related gonococcal isolates with decreased ceftriaxone susceptibility may bring threat of treatment failure in Thailand. Also highlighted the importance of maintaining surveillance for antimicrobial resistance.

Disclosures

All Authors: No reported disclosures

Novel colistin-EDTA combination for successful eradication of colistin-resistant Klebsiella pneumoniae catheter-related biofilm infections

Development of an effective therapy to overcome colistin resistance in Klebsiella pneumoniae, a common pathogen causing catheter-related biofilm infections in vascular catheters, has become a serious therapeutic challenge that must be addressed urgently. Although colistin and EDTA have successful roles for eradicating biofilms, no in vitro and in vivo studies have investigated their efficacy in catheter-related biofilm infections of colistin-resistant K. pneumoniae. In this study, colistin resistance was significantly reversed in both planktonic and mature biofilms of colistin-resistant K. pneumoniae by a combination of colistin (0.25-1 µg/ml) with EDTA (12 mg/ml). This novel colistin-EDTA combination was also demonstrated to have potent efficacy in eradicating colistin-resistant K. pneumoniae catheter-related biofilm infections, and eliminating the risk of recurrence in vivo. Furthermore, this study revealed significant therapeutic efficacy of colistin-EDTA combination in reducing bacterial load in internal organs, lowering serum creatinine, and protecting treated mice from mortality. Altered in vivo expression of different virulence genes indicate bacterial adaptive responses to survive in hostile environments under different treatments. According to these data discovered in this study, a novel colistin-EDTA combination provides favorable efficacy and safety for successful eradication of colistin-resistant K. pneumonia catheter-related biofilm infections.

Multidrug-resistant Neisseria gonorrhoeae infection in heterosexual men with reduced susceptibility to ceftriaxone, first report in Thailand

The global rapid emergence of azithromycin/ceftriaxone resistant Neisseria gonorrhoeae threatens current recommend azithromycin/ceftriaxone dual therapy for gonorrhea to ensure effective treatment. Here, we identified the first two N. gonorrhoeae isolates with decreased ceftriaxone susceptibility in Thailand. Among 134 N. gonorrhoeae isolates collected from Thai Red Cross Anonymous Clinic, Bangkok, two isolates (NG-083 and NG-091) from urethral swab in male heterosexual patients had reduced susceptibility to ceftriaxone (MICs of 0.125 mg/L). Both were multidrug resistant and strong biofilm producers with ceftriaxone tolerance (MBEC > 128 mg/L). NG-083 and NG-091 remained susceptible to azithromycin (MIC of 1 mg/L and 0.5 mg/L, respectively). Reduced susceptibility to ceftriaxone was associated with alterations in PBP2, PBP1, PorB, MtrR, and mtrR promoter region. NG-083 belonged to sequence type (ST) 7235 and NG-091 has new allele number of tbpB with new ST. Molecular docking revealed ceftriaxone weakly occupied the active site of mosaic XXXIV penicillin-binding protein 2 variant in both isolates. Molecular epidemiology results revealed that both isolates display similarities with isolates from UK, USA, and The Netherlands. These first two genetically related gonococcal isolates with decreased ceftriaxone susceptibility heralds the threat of treatment failure in Thailand, and importance of careful surveillance.

Tracking COVID-19 with wastewater to understand asymptomatic transmission

INTRODUCTION

SARS-CoV-2 RNA is excreted in feces of most patients, therefore viral load in wastewater can be used as a surveillance tool to develop an early warning system to help and manage future pandemics.

METHODS

We collected wastewater from 24 random locations at Bangkok city center and 26 nearby suburbs from July to December 2020. SARS-CoV-2 RNA copy numbers were measured using real-time polymerase chain reaction (PCR).

RESULTS

SARS-CoV-2 RNA was detected in wastewater from both the city center and suburbs. Except for July, there were no significant differences in copy numbers between the city center and suburbs. Between October and November, a sharp rise in copy number was observed in both places followed by two to three times increase in December, related to SARS-CoV-2 cases reported for same month.

CONCLUSIONS

Our study provided the first dataset related to SARS-CoV-2 viral RNA in the wastewater of Bangkok. Our results suggest that wastewater could be used as a complementary source for detecting viral RNA and predicting upcoming outbreaks and waves.

Erratum: STING Mediates Lupus via the Activation of Conventional Dendritic Cell Maturation and Plasmacytoid Dendritic Cell Differentiation

[This corrects the article DOI: 10.1016/j.isci.2020.101530.].

STING Mediates Lupus via the Activation of Conventional Dendritic Cell Maturation and Plasmacytoid Dendritic Cell Differentiation

Signaling through stimulator of interferon genes (STING) leads to the production of type I interferons (IFN-Is) and inflammatory cytokines. A gain-of-function mutation in STING was identified in an autoinflammatory disease (STING-associated vasculopathy with onset in infancy; SAVI). The expression of cyclic GMP-AMP, DNA-activated cGAS-STING pathway, increased in a proportion of patients with SLE. The STING signaling pathway may be a candidate for targeted therapy in SLE. Here, we demonstrated that disruption of STING signaling ameliorated lupus development in Fcgr2b-deficient mice. Activation of STING promoted maturation of conventional dendritic cells and differentiation of plasmacytoid dendritic cells via LYN interaction and phosphorylation. The inhibition of LYN decreased the differentiation of STING-activated dendritic cells. Adoptive transfer of STING-activated bone marrow-derived dendritic cells into the FCGR2B and STING double-deficiency mice restored lupus phenotypes. These findings provide evidence that the inhibition of STING signaling may be a candidate targeted treatment for a subset of patients with SLE.

Deficiency of STING Promotes Collagen-Specific Antibody Production and B Cell Survival in Collagen-Induced Arthritis

The levels of interferon-alpha are high in the serum and synovial fluid of rheumatoid arthritis (RA) patients. Activation of the stimulator of type I interferon genes (STING) mediates the productions of type I interferon and promotes chronic inflammation. STING plays a significant role in autoimmune lupus mice. However, the function of STING in collagen-induced arthritis (CIA) model has never been described. This study aimed to test the function of STING in CIA. The Sting-deficient mice developed arthritis comparable to WT mice. The levels of anti-collagen antibody from Sting-deficient mice were significantly higher than the WT mice. The B cells derived from Sting-deficient mice showed better survival than WT mice in response to the B cell receptor (BCR) stimulation. Activation of STING also induced B cell death, especially in activated B cells. This study demonstrated that the inhibition of STING promotes anti-collagen antibodies and B cell survival, which suggested that STING acts as a negative regulator of B cell function in the CIA model.

A rapid and simple method for routine determination of antibiotic sensitivity to biofilm populations of Pseudomonas aeruginosa

Treatment of infections by Pseudomonas aeruginosa forming biofilms after antimicrobial testing on planktonic bacteria can result in substantial failure. Therefore, we offer a robust and simple experimental platform to test the impact of antimicrobials on biofilms. Antibiotic response patterns varied uniquely within biofilm formation capacity and minimal biofilm eradication concentrations (MBECs) has a significantly better discriminatory power than minimum inhibitory concentrations (MICs) to differentiate the overall efficiency of antibiotics to eradicate biofilm. Our resazurin-based 96-well-plate platform is able to emulate bacterial responses to antibiotics under biofilm conditions in a fast, simple, and cost-effective screening method adaptable to automation, and warrants trials in the clinic.

PTM-Logo: a program for generation of sequence logos based on position-specific background amino-acid probabilities

SUMMARY

Identification of the amino-acid motifs in proteins that are targeted for post-translational modifications (PTMs) is of great importance in understanding regulatory networks. Information about targeted motifs can be derived from mass spectrometry data that identify peptides containing specific PTMs such as phosphorylation, ubiquitylation and acetylation. Comparison of input data against a standardized 'background' set allows identification of over- and under-represented amino acids surrounding the modified site. Conventionally, calculation of targeted motifs assumes a random background distribution of amino acids surrounding the modified position. However, we show that probabilities of amino acids depend on (i) the type of the modification and (ii) their positions relative to the modified site. Thus, software that identifies such over- and under-represented amino acids should make appropriate adjustments for these effects. Here we present a new program, PTM-Logo, that generates representations of these amino acid preferences ('logos') based on position-specific amino-acid probability backgrounds calculated either from user-input data or curated databases.

AVAILABILITY AND IMPLEMENTATION

PTM-Logo is freely available online at http://sysbio.chula.ac.th/PTMLogo/ or https://hpcwebapps.cit.nih.gov/PTMLogo/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Simple fluorometric-based assay of antibiotic effectiveness for Acinetobacter baumannii biofilms

Despite strengthened antimicrobial therapy, biofilm infections of Acinetobacter baumannii are associated with poor prognosis and limited therapeutic options. Assessing antibiotics on planktonic bacteria can result in failure against biofilm infections. Currently, antibiotics to treat biofilm infections are administered empirically, usually without considering the susceptibility of the biofilm objectively before beginning treatment. For effective therapy to resolve biofilm infections it is essential to assess the efficacy of commonly used antibiotics against biofilms. Here, we offer a robust and simple assay to assess the efficacy of antibiotics against biofilms. In the present work, we carefully optimized the incubation time, detection range, and fluorescence reading mode for resazurin-based viability staining of biofilms in 96-well-plates and determined minimal biofilm eradication concentrations (MBECs) for A. baumannii isolates from patients with chronic infection. By applying this assay, we demonstrated that antibiotic response patterns varied uniquely within the biofilm formation of various clinical samples. MBEC-50 and 75 have significant discriminatory power over minimum inhibitory concentrations for planktonic suspensions to differentiate the overall efficiency of an antibiotic to eradicate a biofilm. The present assay is an ideal platform on which to assess the efficacy of antibiotics against biofilms in vitro to pave the way for more effective therapy.

Proteomic identification of predictive biomarkers for malignant transformation in complete hydatidiform moles

INTRODUCTION

Protein expression in cells are associated with oncogenesis. This study aims to explore proteomic profiles and discover potential biomarkers that can predict malignant transformation of hydatidiform mole.

METHODS

Retrospective analysis was done in 14 cases of remission hydatidiform mole and 14 cases of hydatidiform mole who later developed malignancy (GTN group). Molar tissues were retrieved from -70 °C frozen tissue. Subsequently, a large-scale proteomic analysis was performed to identify proteins and compare their abundance levels in the preserved molar tissues from these two groups using a dimethyl-labeling technique coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

A total of 2,153 proteins were identified from all samples. 22 and 10 proteins were significantly up-regulated and down-regulated, respectively, in the GTN group compared with the mole group. These altered proteins were found in several biological groups such as cell-cell adhesion, secreted proteins, and ribonucleoproteins. Several hormone-related proteins were among the most up-regulated proteins in the GTN group including choriogonadotropin subunit beta (β-hCG) and alpha (α-hCG), growth/differentiation factor 15, as well as both pregnancy-specific beta-1-glycoproteins 2 and 3. In contrast, protein S100-A11 and l-lactate dehydrogenase A chain, were down-regulated in molar tissue from most patients in the GTN group.

DISCUSSION

This study identified a set of differentially expressed proteins in molar tissues that could potentially be further examined as predictive biomarkers for the malignant transformation of CHMs. A molar proteome database was constructed and can be accessible online at http://sysbio.chula.ac.th/Database/GTD_DB/Supplementary_Data.xlsx.

AbDesigner3D: a structure-guided tool for peptide-based antibody production

Summary

We present AbDesigner3D, a new tool for identification of optimal immunizing peptides for antibody production using a peptide-based strategy. AbDesigner3D integrates 3D structural data from the Protein Data Bank (PDB) with UniProt data, which includes basic sequence data, post-translational modification sites, SNP occurrences and more. Other features, such as uniqueness and conservation scores, are calculated based on sequences from UniProt. The 3D visualization capabilities allow an intuitive interface, while an abundance of quantitative output simplifies the process of comparing immunogen peptides. Important quantitative features added in this tool include calculation and display of accessible surface area (ASA) and protein-protein interacting residues (PPIR). The specialized data visualization features of AbDesigner3D will greatly assist users to optimize their choice of immunizing peptides.

Availability and implementation

AbDesigner3D is freely available at http://sysbio.chula.ac.th/AbDesigner3D or https://hpcwebapps.cit.nih.gov/AbDesigner3D/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Regulatory landscape of AGE-RAGE-oxidative stress axis and its modulation by PPARγ activation in high fructose diet-induced metabolic syndrome

Background

The AGE-RAGE-oxidative stress (AROS) axis is involved in the onset and progression of metabolic syndrome induced by a high-fructose diet (HFD). PPARγ activation is known to modulate metabolic syndrome; however a systems-level investigation looking at the protective effects of PPARγ activation as related to the AROS axis has not been performed.

The aim of this work is to simultaneously characterize multiple molecular parameters within the AROS axis, using samples taken from different body fluids and tissues of a rat model of HFD-induced metabolic syndrome, in the presence or absence of a PPARγ agonist, Rosiglitazone (RGZ).

Methods

Rats were fed with 60% HFD for the first half of the treatment duration (21 days) then continued with either HFD alone or HFD plus RGZ for the second half.

Results

Rats receiving HFD alone showed metabolic syndrome manifestations including hypertension, dyslipidemia, increased glucose levels and insulin resistance, as well as abnormal kidney and inflammatory parameters. Systolic blood pressure, plasma triglyceride and glucose levels, plasma creatinine, and albuminuria were significantly improved in the presence of RGZ. The following molecular parameters of the AROS axis were significantly upregulated in our rat model: carboxymethyl lysine (CML) in urine and liver; carboxyethyl lysine (CEL) in urine; advanced glycation end products (AGEs) in plasma; receptor for advanced glycation end products (RAGE) in liver and kidney; advanced oxidation protein products (AOPP) in plasma; and 4-hydroxynonenal (HNE) in plasma, liver, and kidney. Conversely, with RGZ administration, the upregulation of AOPP and AGEs in plasma, CML and CEL in urine, RAGE in liver as well as HNE in plasma and liver was significantly counteracted/prevented.

Conclusions

Our data demonstrate (i) the systems-level regulatory landscape of HFD-induced metabolic syndrome involving multiple molecular parameters, including HNE, AGEs and their receptor RAGE, and (ii) attenuation of metabolic syndrome by PPARγ modulation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12986-016-0149-z) contains supplementary material, which is available to authorized users.

A machine learning strategy for predicting localization of post-translational modification sites in protein-protein interacting regions

Background

One very important functional domain of proteins is the protein-protein interacting region (PPIR), which forms the binding interface between interacting polypeptide chains. Post-translational modifications (PTMs) that occur in the PPIR can either interfere with or facilitate the interaction between proteins. The ability to predict whether sites of protein modifications are inside or outside of PPIRs would be useful in further elucidating the regulatory mechanisms by which modifications of specific proteins regulate their cellular functions.

Results

Using two of the comprehensive databases for protein-protein interaction and protein modification site data (PDB and PhosphoSitePlus, respectively), we created new databases that map PTMs to their locations inside or outside of PPIRs. The mapped PTMs represented only 5 % of all known PTMs. Thus, in order to predict localization within or outside of PPIRs for the vast majority of PTMs, a machine learning strategy was used to generate predictive models from these mapped databases. For the three mapped PTM databases which had sufficient numbers of modification sites for generating models (acetylation, phosphorylation, and ubiquitylation), the resulting models yielded high overall predictive performance as judged by a combined performance score (CPS). Among the multiple properties of amino acids that were used in the classification tasks, hydrophobicity was found to contribute substantially to the performance of the final predictive models. Compared to the other classifiers we also evaluated, the SVM provided the best performance overall.

Conclusions

These models are the first to predict whether PTMs are located inside or outside of PPIRs, as demonstrated by their high predictive performance. The models and data presented here should be useful in prioritizing both known and newly identified PTMs for further studies to determine the functional relationship between specific PTMs and protein-protein interactions. The implemented R package is available online (http://sysbio.chula.ac.th/PtmPPIR).

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1165-8) contains supplementary material, which is available to authorized users.

EpicCapo: epitope prediction using combined information of amino acid pairwise contact potentials and HLA-peptide contact site information

Background

Epitope identification is an essential step toward synthetic vaccine development since epitopes play an important role in activating immune response. Classical experimental approaches are laborious and time-consuming, and therefore computational methods for generating epitope candidates have been actively studied. Most of these methods, however, are based on sophisticated nonlinear techniques for achieving higher predictive performance. The use of these techniques tend to diminish their interpretability with respect to binding potential: that is, they do not provide much insight into binding mechanisms.

Results

We have developed a novel epitope prediction method named EpicCapo and its variants, EpicCapo⁺ and EpicCapo^+REF. Nonapeptides were encoded numerically using a novel peptide-encoding scheme for machine learning algorithms by utilizing 40 amino acid pairwise contact potentials (referred to as AAPPs throughout this paper). The predictive performances of EpicCapo⁺ and EpicCapo^+REF outperformed other state-of-the-art methods without losing interpretability. Interestingly, the most informative AAPPs estimated by our study were those developed by Micheletti and Simons while previous studies utilized two AAPPs developed by Miyazawa & Jernigan and Betancourt & Thirumalai. In addition, we found that all amino acid positions in nonapeptides could effect on performances of the predictive models including non-anchor positions. Finally, EpicCapo^+REF was applied to identify candidates of promiscuous epitopes. As a result, 67.1% of the predicted nonapeptides epitopes were consistent with preceding studies based on immunological experiments.

Conclusions

Our method achieved high performance in testing with benchmark datasets. In addition, our study identified a number of candidates of promiscuous CTL epitopes consistent with previously reported immunological experiments. We speculate that our techniques may be useful in the development of new vaccines. The R implementation of EpicCapo^+REF is available at http://pirun.ku.ac.th/~fsciiok/EpicCapoREF.zip. Datasets are available at http://pirun.ku.ac.th/~fsciiok/Datasets.zip.

PAAQD: Predicting immunogenicity of MHC class I binding peptides using amino acid pairwise contact potentials and quantum topological molecular similarity descriptors

Prediction of peptide immunogenicity is a promising approach for novel vaccine discovery. Conventionally, epitope prediction methods have been developed to accelerate the process of vaccine production by searching for candidate peptides from pathogenic proteins. However, recent studies revealed that peptides with high binding affinity to major histocompatibility complex molecules (MHCs) do not always result in high immunogenicity. Therefore, it is promising to predict the peptide immunogenicity rather than epitopes in order to discover new vaccines more effectively. To this end, we developed a novel T-cell reactivity predictor which we call PAAQD. Nonapeptides were encoded numerically, using combining information of amino acid pairwise contact potentials (AAPPs) and quantum topological molecular similarity (QTMS) descriptors. Encoded data were used in the construction of our classification model. Our numerical experiments suggested that the predictive performance of PAAQD is at least comparable with POPISK, one of the pioneering techniques for T-cell reactivity prediction. Also, our experiment suggested that the first and eighth positions of nonapeptides are the most important for immunogenicity and most of the anchor residues in epitope prediction were not important in T-cell reactivity prediction. The R implementation of PAAQD is available at http://pirun.ku.ac.th/~fsciiok/PAAQD.rar.

A Gaming Strategy for Teaching the Use of Critical Cardiovascular Drugs

This article reports the use of a successful strategy for teaching non-critical care nurses how to safely administer critical cardiovascular drugs. The use of a gaming technique to accomplish this, accompanied by a caricature case study, is described in detail. Participants' evaluations evidenced a high degree of satisfaction and enjoyment in learning the pharmacological content. Readers can adapt this game to other learning topics for rapid and effective learning of material specific to their institutions.