The function of long non-coding RNA SNHG11 and its working mechanism in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) seriously affects woman's health. The present work is to study the working mechanism of lncRNA SNHG11 in TNBC. The expressions of SNHG11, microRNA (miR)- 7-5p, specificity protein 2 (SP2) and mucin 1 (MUC-1) in TNBC tissues and cells were detected. SNHG11, miR-7-5p and SP2 expressions were then evaluated for TNBC cell malignant behaviors. The relationships among SNHG11, miR-7-5p and SP2 were predicted and verified. Finally, the binding of the transcription factor SP2 to MUC-1 promoter was detected. Abnormally elevated SNHG11, SP2 and MUC-1 expressions were observed in cultured TNBC cells and tumor tissues. SNHG11 knockdown in TNBC cells. Silencing SP2 weakened the promoting effect of SNHG11 on TNBC progression. SNHG11 negatively regulated miR-7-5p expression and positively regulated SP2 expression. SP2 bound to the P2 site of MUC-1 promoter, and SP2 knockdown suppressed MUC-1 expression. It was demonstrated that lncRNA SNHG11 promoted TNBC cell malignant behaviors to facilitate TNBC progression. The study is first of its kinds to unravel the potential of lncRNA SNHG11 in relation to TNBC.

Detecting STR profiles from degrading menstrual blood samples and their use as possible evidence in forensic investigations.

This research explores DNA consistency and attempts to detect STR profiles from the degrading menstrual blood samples (MBS) as reliable forensic evidence. Peripheral (PBS) and MBS of 30 healthy fertile females were taken on the menstrual cycle's second day. They were obtained at different time periods (0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 24, and 48 h) at 25 °C. DNA evaluation was fulfilled to analyze DNA profiles. A considerable elevation in the median concentrations of DNA between 0 and 14-h intervals were documented, whereas decreased extents were registered between 16 and 48 h. Moreover, complete STR profiles (24/24) for DNA were discovered in all the intervals (0, 2, and 48 h). Periods of 0-8 h demonstrated the maximum extents of DNA materials. Full STR were discovered in all the intervals (0, 2, and 48 h). Eventually, MBS can be utilized as forensic evidence.

Deep Learning Approaches for Detecting COVID-19 From Chest X-Ray Images: A Survey.

Chest X-ray (CXR) imaging is a standard and crucial examination method used for suspected cases of coronavirus disease (COVID-19). In profoundly affected or limited resource areas, CXR imaging is preferable owing to its availability, low cost, and rapid results. However, given the rapidly spreading nature of COVID-19, such tests could limit the efficiency of pandemic control and prevention. In response to this issue, artificial intelligence methods such as deep learning are promising options for automatic diagnosis because they have achieved state-of-the-art performance in the analysis of visual information and a wide range of medical images. This paper reviews and critically assesses the preprint and published reports between March and May 2020 for the diagnosis of COVID-19 via CXR images using convolutional neural networks and other deep learning architectures. Despite the encouraging results, there is an urgent need for public, comprehensive, and diverse datasets. Further investigations in terms of explainable and justifiable decisions are also required for more robust, transparent, and accurate predictions.