MATCHCLIP: locate precise breakpoints for copy number variation using CIGAR string by matching soft clipped reads

Copy number variations (CNVs) are associated with many complex diseases. Next generation sequencing data enable one to identify precise CNV breakpoints to better under the underlying molecular mechanisms and to design more efficient assays. Using the CIGAR strings of the reads, we develop a method that can identify the exact CNV breakpoints, and in cases when the breakpoints are in a repeated region, the method reports a range where the breakpoints can slide. Our method identifies the breakpoints of a CNV using both the positions and CIGAR strings of the reads that cover breakpoints of a CNV. A read with a long soft clipped part (denoted as S in CIGAR) at its 3′(right) end can be used to identify the 5′(left)-side of the breakpoints, and a read with a long S part at the 5′ end can be used to identify the breakpoint at the 3′-side. To ensure both types of reads cover the same CNV, we require the overlapped common string to include both of the soft clipped parts. When a CNV starts and ends in the same repeated regions, its breakpoints are not unique, in which case our method reports the left most positions for the breakpoints and a range within which the breakpoints can be incremented without changing the variant sequence. We have implemented the methods in a C++ package intended for the current Illumina Miseq and Hiseq platforms for both whole genome and exon-sequencing. Our simulation studies have shown that our method compares favorably with other similar methods in terms of true discovery rate, false positive rate and breakpoint accuracy. Our results from a real application have shown that the detected CNVs are consistent with zygosity and read depth information. The software package is available at http://statgene.med.upenn.edu/softprog.html

A novel approach for automatic segmentation of prostate and its lesion regions on magnetic resonance imaging

ObjectiveTo develop an accurate and automatic segmentation model based on convolution neural network to segment the prostate and its lesion regions.MethodsOf all 180 subjects, 122 healthy individuals and 58 patients with prostate cancer were included. For each subject, all slices of the prostate were comprised in the DWIs. A novel DCNN is proposed to automatically segment the prostate and its lesion regions. This model is inspired by the U-Net model with the encoding-decoding path as the backbone, importing dense block, attention mechanism techniques, and group norm-Atrous Spatial Pyramidal Pooling. Data augmentation was used to avoid overfitting in training. In the experimental phase, the data set was randomly divided into a training (70%), testing set (30%). four-fold cross-validation methods were used to obtain results for each metric.ResultsThe proposed model achieved in terms of Iou, Dice score, accuracy, sensitivity, 95% Hausdorff Distance, 86.82%,93.90%, 94.11%, 93.8%,7.84 for the prostate, 79.2%, 89.51%, 88.43%,89.31%,8.39 for lesion region in segmentation. Compared to the state-of-the-art models, FCN, U-Net, U-Net++, and ResU-Net, the segmentation model achieved more promising results.ConclusionThe proposed model yielded excellent performance in accurate and automatic segmentation of the prostate and lesion regions, revealing that the novel deep convolutional neural network could be used in clinical disease treatment and diagnosis

Residual Characteristics of Atrazine and Its Metabolites in the Liaoning Province of China

The simultaneous determination of atrazine residue and its metabolites was developed using liquid chromatography-tandem mass spectrometry in Liaoning Province, China. To ensure agricultural production and environmental safety, their contamination level was assessed. A total of 2142 samples were collected between 2014 and 2020, including 1213 soil samples, 190 surface water samples, and 739 groundwater samples. The overall pollution level and detectable level of the herbicides in Liaoning Province was found to be the highest in soil followed by surface water and groundwater. The residual level of the analytes in the collected samples decreased in the following order: atrazine > hydroxyatrazine > desethylatrazine > desisopropylatrazine. From 2014 to 2020, atrazine was detected in soil and surface water, whereas hydroxyatrazine was found in soil without the selected analytes detected in groundwater. The pollution of atrazine in soil was higher than that of hydroxyatrazine, desethylatrazine, and desisopropylatrazine. To maintain sustainable agricultural development, it is critical to pay attention to the residual determination of atrazine in the environment

Residual Characteristics of Atrazine and Its Metabolites in the Liaoning Province of China

The simultaneous determination of atrazine residue and its metabolites was developed using liquid chromatography-tandem mass spectrometry in Liaoning Province, China. To ensure agricultural production and environmental safety, their contamination level was assessed. A total of 2142 samples were collected between 2014 and 2020, including 1213 soil samples, 190 surface water samples, and 739 groundwater samples. The overall pollution level and detectable level of the herbicides in Liaoning Province was found to be the highest in soil followed by surface water and groundwater. The residual level of the analytes in the collected samples decreased in the following order: atrazine > hydroxyatrazine > desethylatrazine > desisopropylatrazine. From 2014 to 2020, atrazine was detected in soil and surface water, whereas hydroxyatrazine was found in soil without the selected analytes detected in groundwater. The pollution of atrazine in soil was higher than that of hydroxyatrazine, desethylatrazine, and desisopropylatrazine. To maintain sustainable agricultural development, it is critical to pay attention to the residual determination of atrazine in the environment

Efficacy of Topical Compound Danxiong Granules for Treatment of Dermatologic Toxicities Induced by Targeted Anticancer Therapy: A Randomized, Double-Blind, Placebo-Controlled Trial

Dermatologic toxicities resulting in dose reduction or discontinuation of treatment pose challenges for targeted anticancer therapies. We conducted this randomized, double-blind, placebo-controlled trial to investigate the efficacy of topical application of Compound Danxiong Granules (CDG) for treatment of dermatologic toxicities associated with targeted anticancer therapies. One hundred and ten patients with dermatologic toxicities induced by targeted anticancer therapies were randomly assigned to CDG or placebo group. Each crude herb (Rhizoma Chuanxiong, Paeonia suffruticosa Andr., Cortex Phellodendri, Geranium sibiricum L., and Flos Carthami) was prepared as an instant herbal powder. Application of the CDG via topical washes lasted 20 minutes, twice daily, for 10 days. The primary outcome was the total effective rate, defined as reduction in at least one grade of skin toxicity. The total effective rate was 77.61% (52/67) in the CDG group and 27.27% (9/33) in the placebo group (P<0.0001). Compared to the placebo treatment, CDG treatment achieved a higher total effective rate for hand-foot skin reaction (95.45% versus 27.27%), acneiform eruption (69.23% versus 30.78%), and paronychia (68.42% versus 22.22%). Topical application of CDG can effectively attenuate dermatologic toxicities induced by targeted anticancer therapies. The effect of CDG was more pronounced in hand-foot skin reaction

1-Pyrroline-5-carboxylate released by prostate Cancer cell inhibit T cell proliferation and function by targeting SHP1/cytochrome c oxidoreductase/ROS Axis

Abstract Background Tumor cell mediated immune-suppression remains a question of interest in tumor biology. In this study, we focused on the metabolites that are released by prostate cancer cells (PCC), which could potentially attenuate T cell immunity. Methods Prostate cancer cells (PCC) media (PCM) was used to treat T cells, and its impact on T cell signaling was evaluated. The molecular mechanism was further verified in vivo using mouse models. The clinical significance was determined using IHC in human clinical specimens. Liquid chromatography mass spectroscopy (LC/MS-MS) was used to identify the metabolites that are released by PCC, which trigger T cells inactivation. Results PCM inhibits T cells proliferation and impairs their ability to produce inflammatory cytokines. PCM decreases ATP production and increases ROS production in T cells by inhibiting complex III of the electron transport chain. We further show that SHP1 as the key molecule that is upregulated in T cells in response to PCM, inhibition of which reverses the phenotype induced by PCM. Using metabolomics analysis, we identified 1-pyrroline-5-carboxylate (P5C) as a vital molecule that is released by PCC. P5C is responsible for suppressing T cells signaling by increasing ROS and SHP1, and decreasing cytokines and ATP production. We confirmed these findings in vivo, which revealed changed proline dehydrogenase (PRODH) expression in tumor tissues, which in turn influences tumor growth and T cell infiltration. Conclusions Our study uncovered a key immunosuppressive axis, which is triggered by PRODH upregulation in PCa tissues, P5C secretion in media and subsequent SHP1-mediated impairment of T cell signaling and infiltration in PCa

Optimization of Bacillus aerius strain JS-786 cell dry mass and its antifungal activity against Botrytis cinerea using response surface methodology

The optimization of fermentation conditions is necessary for field application of biological control agents. The present study was designed to optimize the fermentation conditions for the Bacillus aerius strain, JS-786 in terms of cell dry mass and its antifungal activity against Botrytis cinerea with response surface methodology. A strain of bacteria with strong antifungal activity was isolated from the phyllosphere of tomato plant and identified as B. aerius JS-786 based on the sequence homology of its 16S rRNA gene. After the success of preliminary antifungal activity tests, response surface methodology was used to optimize the fermentation conditions (medium pH, gelatin percentage, incubation period, rotatory speed and incubation temperature) to maximize the cell dry mass and antifungal activity against B. cinerea. A 25 factorial central composite design was employed and multiple response optimization was used to determine the desirability of the operation. The results of regression analysis showed that at the individual level, all of the experimental parameters were significant for cell dry mass; significant results were obtained for antifungal activity pH, incubation period, rotatory speed and incubation temperature. The interactive effect of the incubation period, rotatory speed and incubation temperature was significant. Maximum cell dry mass (8.7 g/L) and inhibition zone (30.4 mm) were obtained at pH 6.4, gelatin 3.2%, incubation period 36.92 h, rotatory speed 163 rpm, and temperature 33.5°C. This study should help to formulate a more rational and cost-effective biological product both in terms of bacterial growth and antifungal activity