On Negabent Functions and Nega-Hadamard Transform

The Boolean function which has equal absolute spectral values under the nega-Hadamard transform is called negabent function. In this paper, the special Boolean functions by concatenation are presented. We investigate their nega-Hadamard transforms, nega-autocorrelation coefficients, sum-of-squares indicators, and so on. We establish a new equivalent statement on f1∥f2 which is negabent function. Based on them, the construction for generating the negabent functions by concatenation is given. Finally, the function expressed as f(Ax⊕a)⊕b·x⊕c is discussed. The nega-Hadamard transform and nega-autocorrelation coefficient of this function are derived. By applying these results, some properties are obtained

Serum Protein KNG1, APOC3, and PON1 as Potential Biomarkers for Yin-Deficiency-Heat Syndrome

Yin-deficiency-heat (YDH) syndrome is a concept in Traditional Chinese Medicine (TCM) for describing subhealth status. However, there are few efficient diagnostic methods available for confirming YDH syndrome. To explore the novel method for diagnosing YDH syndrome, we applied iTRAQ to observe the serum protein profiles in YDH syndrome rats and confirmed protein levels by ELISA. A total of 92 differentially expressed proteins (63 upregulated proteins and 29 downregulated proteins), which were mainly involved in complement and coagulation cascades and glucose metabolism pathway, were identified by the proteomic experiments. Kininogen 1 (KNG1) was significantly increased (p<0.0001), while apolipoprotein C-III (APOC3, p<0.005) and paraoxonase 1 (PON1, p<0.001) were significantly decreased in the serum of YDH syndrome rats. The combination of KNG1, APOC3, and PON1 constituted a diagnostic model with 100.0% sensitivity and 85.0% specificity. The results indicated that KNG1, APOC3, and PON1 may act as potential biomarkers for diagnosing YDH syndrome. KNG1 may regulate cytokines and chemokines release in YDH syndrome, and the low levels of PON1 and APOC3 may increase oxidative stress and lipolysis in YDH syndrome, respectively. Our work provides a novel method for YDH syndrome diagnosis and also provides valuable experimental basis to understand the molecular mechanism of YDH syndrome

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Screening and Identification of Six Serum microRNAs as Novel Potential Combination Biomarkers for Pulmonary Tuberculosis Diagnosis

<div><p>Background</p><p>It is very difficult to prevent pulmonary tuberculosis (TB) due to the lack of specific and diagnostic markers, which could lead to a high incidence of pulmonary TB. We screened the differentially expressed serum microRNAs (miRNAs) as potential biomarkers for the diagnosis of pulmonary TB.</p><p>Methods</p><p>In this study, serum miRNAs were screened using the Solexa sequencing method as the potential biomarkers for the diagnosis of pulmonary TB. The stem-loop quantitative reverse-transcription polymerase chain reaction (qRT-PCR) assay was used to verify differentially expressed serum miRNAs. The receiver operating characteristic (ROC) curve and logistic regression model were used to analyze the sensitivity and specificity of the single miRNA and a combination of miRNAs for diagnosis, respectively. Using the predicted target genes, we constructed the regulatory networks of miRNAs and genes that were related to pulmonary TB.</p><p>Results</p><p>The Solexa sequencing data showed that 91 serum miRNAs were differentially expressed in pulmonary TB patients, compared to healthy controls. Following qRT-PCR confirmation, six serum miRNAs (hsa-miR-378, hsa-miR-483-5p, hsa-miR-22, hsa-miR-29c, hsa-miR-101 and hsa-miR-320b) showed significant difference among pulmonary TB patients, healthy controls (<i>P</i><0.001) and differential diagnosis groups (including patients with pneumonia, lung cancer and chronic obstructive pulmonary disease) (<i>P</i><0.05). The logistic regression analysis of a combination of six serum miRNAs revealed that the sensitivity and the specificity of TB diagnosis were 95.0% and 91.8% respectively. The miRNAs-gene regulatory networks revealed that several miRNAs may regulate some target genes involved in immune pathways and participate in the pathogenesis of pulmonary TB.</p><p>Conclusion</p><p>Our study suggests that a combination of six serum miRNAs have great potential to serve as non-invasive biomarkers of pulmonary TB.</p></div

Differentially expressed serum miRNAs in pulmonary TB compared to the healthy controls in both the training set and the validation set.

***<p><i>P</i><0.001,</p>**<p><i>P<</i>0.01,</p>*<p><i>P</i><0.05.</p

The categories of small RNAs in pooled serum samples from pulmonary TB patients and healthy controls by Solexa sequencing analysis.

<p>The categories of small RNAs in pooled serum samples from pulmonary TB patients and healthy controls by Solexa sequencing analysis.</p

Detection of pulmonary TB patients with six serum miRNAs by qRT-PCR assay.

<p>Serum miRNA expression of six miRNAs was measured in 128 pulmonary TB patients and 108 healthy controls (in both the training and validation set). We analyzed the expression of six miRNAs (hsa-miR-378, hsa-miR-483-5p, hsa-miR-22, hsa-miR-29c, hsa-miR-320b and hsa-miR-101) selected from the Solexa sequencing data by using qRT-PCR. The 2^−ΔΔCT method was used to normalize the relative gene expression data in the qRT-PCR assay. hsa-miR-16 was set as the reference gene. The miRNA expression value in one subject with healthy controls was normalized to 1. Statistical analysis was performed using the nonparametric Mann-Whitney test. ***<i>P</i><0.001, **<i>P<</i>0.01, *<i>P</i><0.05. TB, tuberculosis.</p

The qRT-PCR assay validation of miRNA expression levels in samples from pulmonary TB patients versus pneumonia, COPD or lung cancer patients.

<p>We analyzed the expression of six serum miRNAs (hsa-miR-378, hsa-miR-483-5p, hsa-miR-22, hsa-miR-29c, hsa-miR-320b and hsa-miR-101) in 128 pulmonary TB patients versus 30 pneumonia, 30 COPD or 30 lung cancer patients, respectively. The 2^−ΔΔCT method was used to normalize the relative gene expression data in the qRT-PCR assay. Hsa-miR-16 was set as the reference gene. The miRNA expression value in one subject with pulmonary TB was normalized to 1. Statistical analysis was performed using the nonparametric Mann-Whitney test. ***<i>P</i><0.001, **<i>P</i><0.01, *<i>P</i><0.05. TB, tuberculosis; COPD, chronic obstructive pulmonary disease.</p

The number of miRNAs in pooled serum samples from pulmonary TB and healthy controls by Solexa sequencing analysis.

*<p>the opposite arm of the precursor.</p