Uncovering Spatiotemporal Patterns of Travel Flows Under Extreme Weather Events by Tensor Decomposition (Short Paper)

Extreme weather events have caused dramatic damage to human society. Human mobility is one of the important aspects that are impacted significantly by extreme weather. Currently, focus on human mobility research during extreme weather is often limited to the transport infrastructure and emergency management perspectives, lacking a systematic understanding of the spatiotemporal patterns of human travel behavior. In this research, we examine the structural changes in human mobility under the severe rainstorm that occurred on July 20th, 2021 in Zhengzhou, Henan Province, China. Innovatively applying a tensor decomposition approach to analyzing spatiotemporal flows of human movements represented by the mobile phone big data, we extract the characteristic components of human travel behaviors from the spatial and temporal dimensions, which help discover and understand the latent spatiotemporal patterns hidden in human mobility data. This study provides a new methodological perspective and demonstrates that it can be useful for uncovering latent patterns of human mobility and identifying its structural changes during extreme weather events. This is of great importance to a better understanding of the behavioral side of human mobility and its response to external shocks and has significant implications for human-focused policies in urban risk mitigation and emergency response

Lovastatin enhances adenovirus-mediated TRAIL induced apoptosis by depleting cholesterol of lipid rafts and affecting CAR and death receptor expression of prostate cancer cells

Oncolytic adenovirus and apoptosis inducer TRAIL are promising cancer therapies. Their antitumor efficacy, when used as single agents, is limited. Oncolytic adenoviruses have low infection activity, and cancer cells develop resistance to TRAIL-induced apoptosis. Here, we explored combining prostate-restricted replication competent adenovirus-mediated TRAIL (PRRA-TRAIL) with lovastatin, a commonly used cholesterol-lowering drug, as a potential therapy for advanced prostate cancer (PCa). Lovastatin significantly enhanced the efficacy of PRRA-TRAIL by promoting the in vivo tumor suppression, and the in vitro cell killing and apoptosis induction, via integration of multiple molecular mechanisms. Lovastatin enhanced PRRA replication and virus-delivered transgene expression by increasing the expression levels of CAR and integrins, which are critical for adenovirus 5 binding and internalization. Lovastatin enhanced TRAIL-induced apoptosis by increasing death receptor DR4 expression. These multiple effects of lovastatin on CAR, integrins and DR4 expression were closely associated with cholesterol-depletion in lipid rafts. These studies, for the first time, show correlations between cholesterol/lipid rafts, oncolytic adenovirus infection efficiency and the antitumor efficacy of TRAIL at the cellular level. This work enhances our understanding of the molecular mechanisms that support use of lovastatin, in combination with PRRA-TRAIL, as a candidate strategy to treat human refractory prostate cancer in the future

The Antitumor Activities of Marsdenia tenacissima

Marsdenia tenacissima (MT), a traditional Chinese herbal medicine, has long been used for thousands of years to treat asthma, tracheitis, rheumatism, etc. An increasing number of recent studies have focused on the antitumor effects of MT. The effects of MT on cancer are the result of various activated signaling pathways and inhibiting factors and the high expression levels of regulatory proteins. MT can inhibit different cancer types including non-small cell lung cancer (NSCLC), malignant tumors, hepatic carcinoma, and so on. This article mainly focuses on the activities and mechanisms of MT. In addition, the efficacy and toxicity of MT are also discussed. Further studies of MT are required for improved medicinal utilization

Cassava genome from a wild ancestor to cultivated varieties

Cassava is a major tropical food crop in the Euphorbiaceae family that has high carbohydrate production potential and adaptability to diverse environments. Here we present the draft genome sequences of a wild ancestor and a domesticated variety of cassava and comparative analyses with a partial inbred line. We identify 1,584 and 1,678 gene models specific to the wild and domesticated varieties, respectively, and discover high heterozygosity and millions of single-nucleotide variations. Our analyses reveal that genes involved in photosynthesis, starch accumulation and abiotic stresses have been positively selected, whereas those involved in cell wall biosynthesis and secondary metabolism, including cyanogenic glucoside formation, have been negatively selected in the cultivated varieties, reflecting the result of natural selection and domestication. Differences in microRNA genes and retrotransposon regulation could partly explain an increased carbon flux towards starch accumulation and reduced cyanogenic glucoside accumulation in domesticated cassava. These results may contribute to genetic improvement of cassava through better understanding of its biology

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Commentary: Lico A causes ER stress and apoptosis via up-regulating miR-144-3p in human lung cancer cell line H292

Natural compound licochalcone A (lico A), a main constituent of flavonoids, has been proved to induce ER stress and apoptosis in cancer cells. However, the underlying anti-tumor mechanism of lico A remains to be clarified in detail. A recently-published report from the journal Frontiers in Pharmacology evaluated the miRNA-based mechanism for lico A on its anti-cancer effect. They found that lico A significantly promoted the tumor-suppressor miR-144-3p expression, so as to up-regulate ER stress-response protein CHOP (CCAAT/-enhancer-binding protein homologous protein) by down-regulating nuclear factor E2-related factor 2 (Nrf2), finally inducing apoptotic cell death in lung cancer. Their findings pave the path toward a more understanding of miRNA-based drugs for cancer treatment in the future. Keywords: Lico A, ER stress, Apoptosis, miR-144-3p, Lung cancer, Anti-cancer therapeutic

AHY-SLAM: Toward Faster and More Accurate Visual SLAM in Dynamic Scenes Using Homogenized Feature Extraction and Object Detection Method

At present, SLAM is widely used in all kinds of dynamic scenes. It is difficult to distinguish dynamic targets in scenes using traditional visual SLAM. In the matching process, dynamic points are incorrectly added to the pose calculation with the camera, resulting in low precision and poor robustness in the pose estimation. This paper proposes a new dynamic scene visual SLAM algorithm based on adaptive threshold homogenized feature extraction and YOLOv5 object detection, named AHY-SLAM. This new method adds three new modules based on ORB-SLAM2: a keyframe selection module, a threshold calculation module, and an object detection module. The optical flow method is used to screen keyframes for each frame input in AHY-SLAM. An adaptive threshold is used to extract feature points for keyframes, and dynamic points are eliminated with YOLOv5. Compared with ORB-SLAM2, AHY-SLAM has significantly improved pose estimation accuracy over multiple dynamic scene sequences in the TUM open dataset, and the absolute pose estimation accuracy can be increased by up to 97%. Compared with other dynamic scene SLAM algorithms, the speed of AHY-SLAM is also significantly improved under a guarantee of acceptable accuracy

Genetic, Functional, and Immunological Study of ZnT8 in Diabetes

Zinc level in the body is finely regulated to maintain cellular function. Dysregulation of zinc metabolism may induce a variety of diseases, e.g., diabetes. Zinc participates in insulin synthesis, storage, and secretion by functioning as a “cellular second messenger” in the insulin signaling pathway and glucose homeostasis. The highest zinc concentration is in the pancreas islets. Zinc accumulation in cell granules is manipulated by ZnT8, a zinc transporter expressed predominately in pancreatic α and β cells. A common ZnT8 gene (SLC30A8) polymorphism increases the risk of type 2 diabetes mellitus (T2DM), and rare mutations may present protective effects. In type 1 diabetes mellitus (T1DM), autoantibodies show specificity for binding two variants of ZnT8 (R or W at amino acid 325) dictated by a polymorphism in SLC30A8. In this review, we summarize the structure, feature, functions, and polymorphisms of ZnT8 along with its association with diabetes and explore future study directions