Molecular survey and sequence analysis of Anaplasma spp. in cattle and ticks in a Malaysian farm

This study was conducted to determine the occurrence of Anaplasma spp. in the blood samples of cattle, goats, deer and ticks in a Malaysian farm. Using polymerase chain reaction (PCR) and sequencing approach, Anaplasma spp. was detected from 81(84.4%) of 96 cattle blood samples. All blood samples from 23 goats and 22 deer tested were negative. Based on the analysis of the Anaplasma partial 16S ribosomal RNA gene, four sequence types (genotypes 1 to 4) were identified in this study. Genotypes 1-3 showed high sequence similarity to those of Anaplasma platys/ Anaplasma phagocytophilum, whilst genotype 4 was identical to those of Anaplasma marginale/ Anaplasma centrale/ Anaplasma ovis. Anaplasma DNA was detected from six (5.5%) of 109 ticks which were identified as Rhipicephalus (formely known as Boophilus) microplus ticks collected from the cattle. This study reported for the first time the detection of four Anaplasma sequence types circulating in the cattle population in a farm in Malaysia. The detection of Anaplasma DNA in R. microplus ticks in this study provides evidence that the ticks are one of the potential vectors for transmission of anaplasmosis in the cattle

A review on cloud computing security

Cloud computing is a technology that maintain the data and application by using the central remote server with the internet connection. By utilizing cloud computing, user can reduce their costs as they no need to purchase their own hardware and software. However cloud computing still has many issues concerning securities, such as privacy issues, loss of data and stolen of data. Some security issues over cloud services including confidentiality, integrity, availability, privacy and attacks are concerned by the users. This paper reviews some of the issues and its current solutions

Precision in medicinal chemistry: Harnessing enzymes for advanced halogenation

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Antimicrobial Drug Resistance in Pathogens Causing Nosocomial Infections at a University Hospital in Taiwan, 1981-1999

To determine the distribution and antimicrobial drug resistance in bacterial pathogens causing nosocomial infections, surveillance data on nosocomial infections documented from 1981 to 1999 at National Taiwan University Hospital were analyzed. During this period, 35,580 bacterial pathogens causing nosocomial infections were identified. Candida species increased considerably, ranking first by 1999 in the incidence of pathogens causing all nosocomial infections, followed by Staphylococcus aureus and Pseudomonas aeruginosa. Candida species also increased in importance as bloodstream infection isolates, from 1.0% in 1981-1986 to 16.2% in 1999. The most frequent isolates from urinary tract infections were Candida species (23.6%), followed by Escherichia coli (18.6%) and P. aeruginosa (11.0%). P. aeruginosa remained the most frequent isolates for respiratory tract and surgical site infections in the past 13 years. A remarkable increase in incidence was found in methicillin-resistant S. aureus (from 4.3% in 1981-1986 to 58.9% in 1993-1998), cefotaxime-resistant E. coli (from 0% in 1981-1986 to 6.1% in 1993-1998), and cefotaxime-resistant Klebsiella pneumoniae (from 4.0% in 1981-1986 to 25.8% in 1993-1998). Etiologic shifts in nosocomial infections and an upsurge of antimicrobial resistance among these pathogens, particularly those isolated from intensive care units, are impressive and alarming

Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees

BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR. The collection of microarray datasets from the Gene Expression Omnibus, four breast cancer datasets were pooled for predicting five-year breast cancer relapse. After data compilation, 757 subjects, 5 clinical variables and 13,452 genetic variables were aggregated. The bootstrap method, Mann–Whitney U test and 20-fold cross-validation were performed to investigate candidate genes with 100 most-significant p-values. The predictive powers of DT, LR and ANN models were assessed using accuracy and the area under ROC curve. The associated genes were evaluated using Cox regression. RESULTS: The DT models exhibited the lowest predictive power and the poorest extrapolation when applied to the test samples. The ANN models displayed the best predictive power and showed the best extrapolation. The 21 most-associated genes, as determined by integration of each model, were analyzed using Cox regression with a 3.53-fold (95% CI: 2.24-5.58) increased risk of breast cancer five-year recurrence… CONCLUSIONS: The 21 selected genes can predict breast cancer recurrence. Among these genes, CCNB1, PLK1 and TOP2A are in the cell cycle G2/M DNA damage checkpoint pathway. Oncologists can offer the genetic information for patients when understanding the gene expression profiles on breast cancer recurrence

Diagnostic Accuracy of the Electrocardiogram for Heart Failure With Reduced or Preserved Ejection Fraction

Current heart failure (HF) guidelines recommend electrocardiography (ECG) as an essential initial investigation in a patient's workup. 1 However, these recommendations were based on studies primarily including patients with HF with reduced ejection fraction (HFrEF). 1 , 2 , 3 Guidelines do not distinguish HFrEF from HF with preserved and mid-range ejection fraction (HFpEF and HFmrEF) in their ECG recommendations. We hypothesized that a normal ECG does not exclude HFpEF and has a considerably lower sensitivity for diagnosing HFpEF than HFrEF

Associations Between Eczema and Attention Deficit Hyperactivity Disorder Symptoms in Children

Background: Epidemiological studies suggest a link between eczema and attention deficit hyperactivity disorder (ADHD), but underlying mechanisms have not been examined.Objective: We aim to investigate the association between eczema and subsequent ADHD symptoms in the Growing Up in Singapore Towards healthy Outcomes cohort and explore the role of pro-inflammatory cytokines and gut microbiome.Methods: The modified International Study of Asthma and Allergies in Childhood questionnaire and Computerized Diagnostic Interview Schedule for Children Version IV were administered to assess reported eczema within the first 18 months and presence of ADHD symptoms at 54 months, respectively. Skin prick testing at 18 months, cytokines in maternal blood during pregnancy and cord blood and the mediating role of the gut microbiome at 24 months were assessed.Results: After adjusting for confounders, eczema with or without a positive skin prick test was associated with doubling the risk of ADHD symptoms. No differences in maternal and cord blood cytokines were observed in children with and without eczema, or children with and without ADHD. Gut microbiome dysbiosis was observed in children with eczema and children with ADHD. Children with eczema also had lower gut bacterial Shannon diversity. However, the relationship between eczema and ADHD was not mediated by gut microbiome.Conclusion: Early life eczema diagnosis is associated with a higher risk of subsequent ADHD symptoms in children. We found no evidence for underlying inflammatory mechanism or mediation by gut microbiome dysbiosis. Further research should evaluate other mechanisms underlying the link between eczema and ADHD.Peer reviewe

Linear B-cell epitopes in the spike and nucleocapsid proteins as markers of SARS-CoV-2 exposure and disease severity

BACKGROUND Given the unceasing worldwide surge in COVID-19 cases, there is an imperative need to develop highly specific and sensitive serology assays to define exposure to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). METHODS Pooled plasma samples from PCR positive COVID-19 patients were used to identify linear B-cell epitopes from a SARS-CoV-2 peptide library of spike (S), envelope (E), membrane (M), and nucleocapsid (N) structural proteins by peptide-based ELISA. Hit epitopes were further validated with 79 COVID-19 patients with different disease severity status, 13 seasonal human CoV, 20 recovered SARS patients and 22 healthy donors. FINDINGS Four immunodominant epitopes, S14P5, S20P2, S21P2 and N4P5, were identified on the S and N viral proteins. IgG responses to all identified epitopes displayed a strong detection profile, with N4P5 achieving the highest level of specificity (100%) and sensitivity (>96%) against SARS-CoV-2. Furthermore, the magnitude of IgG responses to S14P5, S21P2 and N4P5 were strongly associated with disease severity. INTERPRETATION IgG responses to the peptide epitopes can serve as useful indicators for the degree of immunopathology in COVID-19 patients, and function as higly specific and sensitive sero-immunosurveillance tools for recent or past SARS-CoV-2 infections. The flexibility of these epitopes to be used alone or in combination will allow for the development of improved point-of-care-tests (POCTs)

Clinical Manifestations, Laboratory Findings, and Treatment Outcomes of SARS Patients

Clinical and laboratory data on severe acute respiratory syndrome (SARS), particularly on the temporal progression of abnormal laboratory findings, are limited. We conducted a prospective study on the clinical, radiologic, and hematologic findings of SARS patients with pneumonia, who were admitted to National Taiwan University Hospital from March 8 to June 15, 2003. Fever was the most frequent initial symptom, followed by cough, myalgia, dyspnea, and diarrhea. Twenty-four patients had various underlying diseases. Most patients had elevated C-reactive protein (CRP) levels and lymphopenia. Other common abnormal laboratory findings included leukopenia, thrombocytopenia, and elevated levels of aminotransferase, lactate dehydrogenase, and creatine kinase. These clinical and laboratory findings were exacerbated in most patients during the second week of disease. The overall case-fatality rate was 19.7%. By multivariate analysis, underlying disease and initial CRP level were predictive of death

Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer

Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-κB, and Wnt/β-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms