Tianshengyuan-1 (TSY-1) regulates cellular Telomerase activity by methylation of TERT promoter.

Telomere and Telomerase have recently been explored as anti-aging and anti-cancer drug targets with only limited success. Previously we showed that the Chinese herbal medicine Tianshengyuan-1 (TSY-1), an agent used to treat bone marrow deficiency, has a profound effect on stimulating Telomerase activity in hematopoietic cells. Here, the mechanism of TSY-1 on cellular Telomerase activity was further investigated using HL60, a promyelocytic leukemia cell line, normal peripheral blood mononuclear cells, and CD34+ hematopoietic stem cells derived from umbilical cord blood. TSY-1 increases Telomerase activity in normal peripheral blood mononuclear cells and CD34+ hematopoietic stem cells with innately low Telomerase activity but decreases Telomerase activity in HL60 cells with high intrinsic Telomerase activity, both in a dose-response manner. Gene profiling analysis identified Telomerase reverse transcriptase (TERT) as the potential target gene associated with the TSY-1 effect, which was verified by both RT-PCR and western blot analysis. The β-galactosidase reporter staining assay showed that the effect of TSY-1 on Telomerase activity correlates with cell senescence. TSY-1 induced hypomethylation within TERT core promoter in HL60 cells but induced hypermethylation within TERT core promoter in normal peripheral blood mononuclear cells and CD34+ hematopoietic stem cells. TSY-1 appears to affect the Telomerase activity in different cell lines differently and the effect is associated with TERT expression, possibly via the methylation of TERT promoter

A two-base encoded DNA sequence alignment problem in computational biology

The recent introduction of instruments capable of producing millions of DNA sequence reads in a single run is rapidly changing the landscape of genetics. The primary objective of the "sequence alignment" problem is to search for a new algorithm that facilitates the use of two-base encoded data for large-scale re-sequencing projects. This algorithm should be able to perform local sequence alignment as well as error detection and correction in a reliable and systematic manner, enabling the direct comparison of encoded DNA sequence reads to a candidate reference DNA sequence. We will first briefly review two well-known sequence alignment approaches and provide a rudimentary improvement for implementation on parallel systems. Then, we carefully examin a unique sequencing technique known as the SOLiDTM System that can be implemented, and follow by the results from the global and local sequence alignment. In this report, the team presents an explanation of the algorithms for color space sequence data from the high-throughput re-sequencing technology and a theoretical parallel approach to the dynamic programming method for global and local alignment. The combination of the di-base approach and dynamic programming provides a possible viewpoint for large-scale re-sequencing projects. We anticipate the use of distributed computing to be the next-generation engine for large-scale problems like such

A Spatial-Temporal Deformable Attention based Framework for Breast Lesion Detection in Videos

Detecting breast lesion in videos is crucial for computer-aided diagnosis. Existing video-based breast lesion detection approaches typically perform temporal feature aggregation of deep backbone features based on the self-attention operation. We argue that such a strategy struggles to effectively perform deep feature aggregation and ignores the useful local information. To tackle these issues, we propose a spatial-temporal deformable attention based framework, named STNet. Our STNet introduces a spatial-temporal deformable attention module to perform local spatial-temporal feature fusion. The spatial-temporal deformable attention module enables deep feature aggregation in each stage of both encoder and decoder. To further accelerate the detection speed, we introduce an encoder feature shuffle strategy for multi-frame prediction during inference. In our encoder feature shuffle strategy, we share the backbone and encoder features, and shuffle encoder features for decoder to generate the predictions of multiple frames. The experiments on the public breast lesion ultrasound video dataset show that our STNet obtains a state-of-the-art detection performance, while operating twice as fast inference speed. The code and model are available at https://github.com/AlfredQin/STNet.Comment: Accepted by MICCAI 202

An In Vitro Comparison of the Digestibility and Gastrointestinal Fate of Scallops and Plant-Based Scallop Analogs

Concerns exist regarding the negative environmental impact and health risks associated with ocean fishing and aquaculture, such as stock depletion, pollution, biodiversity loss, and toxin presence. To address these concerns, plant-based seafood analogs are being developed. Our previous study successfully created plant-based scallop analogs using pea proteins and citrus pectin, resembling real scallops in appearance and texture. This study focuses on comparing the digestive fate of these analogs to real scallops, as it can impact their nutritional properties. Using an in vitro digestion model (INFOGEST), we simulated oral, gastric, and small intestinal conditions. The analysis revealed differences in the microstructure, physicochemical properties, and protein digestibility between the plant-based scallops and real scallops. The particle size and charge followed the following similar trends for both types of scallops: the particle size decreased from the mouth to the stomach to the small intestine; the particles were negative in the mouth, positive in the stomach, and negative in the small intestine. The protein digestibility of the plant-based scallops was considerably lower than that of real scallops. For instance, around 18.8% and 61.4% of protein was digested in the stomach and small intestine phases for the real scallop (80.2% total digestion), whereas around 8.7% and 47.7% of the protein was digested for the plant-based scallop (56.4% total digestion). The lower digestibility of the plant-based scallops may have been due to differences in the protein structure, the presence of dietary fibers (pectin), or antinutritional factors in the plant proteins. These findings are crucial for developing more sustainable next-generation plant-based seafood analogs