The Neutrophil-to-Lymphocyte ratio as a marker of recovery status in patients with severe dental infection

The aim of the study was to assess the value of pretreatment neutrophil/lymphocyte (N/L) ratio and mean platelet volume (MPV) and the correlation between these markers with progression in patients with severe odontogenic infection. A cohort of 100 patients with severe odontogenic infection were divided into 2 groups according to their length of hospital stay. The N/L ratio and MPV was measured in all patients. The correlation in all patients between preoperative fever, preoperative antibiotic doses, postoperative antibiotic doses, total antibiotic doses and hospital stay with N/L ratio and MPV were analyzed. The Youden index was used to identify the optimal cut-off value. There were positive and statistically significant correlations between N/L ratio and prolonged hospital stay and postoperative antibiotic doses and total antibiotic doses. The optimum cut ?off level of N/L ratio was 5.19 according to ROC analysis. However, there was no correlation between MPV and any of these parameters. N/L ratio may be used as a prognostic marker for patients with odontogenic infections. These patients may need a higher dose of antibiotics and stay more than 1 day in hospital for the treatment of odontogenic infection when the N/L ratio is detected to be more than 5.19

Transcriptome Analysis for Non-Model Organism: Current Status and Best-Practices

Since transcriptome analysis provides genome-wide sequence and gene expression information, transcript reconstruction using RNA-Seq sequence reads has become popular during recent years. For non-model organism, as distinct from the reference genome-based mapping, sequence reads are processed via de novo transcriptome assembly approaches to produce large numbers of contigs corresponding to coding or non-coding, but expressed, part of genome. In spite of immense potential of RNA-Seq–based methods, particularly in recovering full-length transcripts and spliced isoforms from short-reads, the accurate results can be only obtained by the procedures to be taken in a step-by-step manner. In this chapter, we aim to provide an overview of the state-of-the-art methods including (i) quality check and pre-processing of raw reads, (ii) the pros and cons of de novo transcriptome assemblers, (iii) generating non-redundant transcript data, (iv) current quality assessment tools for de novo transcriptome assemblies, (v) approaches for transcript abundance and differential expression estimations and finally (vi) further mining of transcriptomic data for particular biological questions. Our intention is to provide an overview and practical guidance for choosing the appropriate approaches to best meet the needs of researchers in this area and also outline the strategies to improve on-going projects

Bagging Support Vector Machines for Leukemia Classification

Abstract Leukemia is one of the most common cancer type, and its diagnosis and classification is becoming increasingly complex and important. Here, we used a gene expression dataset and adapted bagging support vector machines (bSVM) for leukemia classification. bSVM trains each SVM seperately using bootstrap technique, then aggregates the performances of each SVM by majority voting. bSVM showed accuracy between 87.5% -92.5%, area under ROC curve between 98.0% -99.2%, F-measure between 90.5% -92.7% and outperformed single SVM and other classification methods. We also compared our results with other study results which used the same dataset for leukemia classification. Experimental results revealed that bSVM showed the best performance and can be used as a biomarker for the diagnose of leukemia disease

Uptake of Ba2+ ions by natural bentonite and CaCO3: A radiotracer, EDXRF and PXRD study

Ba2+ uptake by natural bentonite, CaCO3 in addition to a number of bentonite-CaCO3 mixtures with variable compositions as a function of pH and Ba2+ concentration was studied. Radiotracer method, EDXRF, and PXRD were used. The results of radiotracer experiments showed that the uptake of Ba2+ by CaCO3 was larger than its uptake by natural bentonite samples, particularly at low initial concentrations of Ba2+ and higher pH values. This finding was supported by the EDXRF results, According to the sorption data, the apparent ΔG° values of sorption were in the range -9±1 to -13±3 kJ/mol. The PXRD studies revealed the formation of BaCO3 upon sorption of Ba2+ on pure CaCO3 and on some of the bentonite-CaCO3 mixtures

Wellesley College 1875-1975: A Century of Women

https://repository.wellesley.edu/wellesleyhistories/1000/thumbnail.jp

Cognitive Assessment in Patients with Acute COVID-19: A Cross-Sectional Study

Purpose: Many reports have revealed a high percentage of patients suffering from cognitive impairment due to COVID-19. We investigated cognitive functions using the Montreal Cognitive Assessment (MoCA) in mild COVID-19 patients compared with non-COVID-19 patients within 5 days after the initial respiratory symptoms of infection. Materials and Methods: 113 patients with mild COVID-19 and 109 age- and sex-matched controls were enrolled in this prospective cross-sectional study. Cognitive functions were evaluated using the MoCA. Results: We found that the MoCA scores were significantly lower in the COVID-19 patients than in the controls (P<0.001). Compared to the controls, we found point deficits within some MoCA items such as visuospatial (P<0.001), memory (P=0.017), and attention (P<0.048) domains. In the multivariate model, female sex (2.06 [1.02–4.16], P=0.044), low education level (150.05 [5.16–43.90], P<0.001), high fasting blood glucose level (0.98 [0.96–1.00], P=0.043), and the presence of COVID-19 (24.24 [9.52–61.72], P<0.001) were independently associated with cognitive impairment (OR, 95% CI). Conclusion: We detected cognitive dysfunction, involving the visuospatial domain, memory, and attention, during the acute phase in patients with mild COVID-19

Global Transcriptome Analysis Reveals Differences in Gene Expression Patterns Between Nonhyperhydric and Hyperhydric Peach Leaves

Hyperhydricity is a morphophysiological disorder of plants in tissue culture characterized morphologically by the presence of translucent, thick, curled, and fragile leaves as a result of excessive water intake. Since clonal propagation is a major in vitro technique for multiplying plants vegetatively, the emergence of hyperhydricity-related symptoms causes significant economic losses to agriculture and horticulture. Although numerous efforts have been hitherto devoted to the morphological and anatomical responses of plants to hyperhydricity, the underlying molecular mechanism remains largely unknown. Here, a genome-wide transcriptome analysis was performed to identify differentially expressed genes in hyperhydric and nonhyperhydric leaves of peach [ (L.) Batsch]. The RNA sequencing (RNA-Seq) analysis showed that the expression of >300 transcripts was altered between control and hyperhydric leaf cells. The top 30 differentially expressed transcripts (DETs) were related to the posttranscriptional regulators of organelle gene expression and photosynthesis, cellular elimination, plant cuticle development, and abiotic stress response processes. The expression of 10 DETs was also conformed by quantitative real-time polymerase chain reaction (RT-qPCR) in hyperhydric and nonhyperhydric leaves. As a complex biological process, hyperhydricity alters the expression of various transcripts including transcription factor (), RNA binding protein (pentatricopeptide, ), transporter protein (), and . Thus, this genome-wide transcriptome profiling study may help elucidate the molecular mechanism of hyperhydricity