Teaching Elementary Linear Algebra Using Matlab: An Initial Investigation

Xiaoxu Han teaches linear algebra. In his quest to innovate his class, he has explored using a computer software package to do the calculations for students and remove some of the tedious algebra and arithmetic that often lead to minor math errors when working with matrices. Moreover, the software packages become necessary when matrices become too large to be solved by hand. Xiaoxu’s project involved incorporating MATLAB, his software of choice, into his course and examining the students’ perceptions of how much using this program helped them to learn the course material. His first-stage analysis focused largely on student reports of their satisfaction with this curricular innovation. Xiaoxu discovered that, by and large, his students were pleased with MATLAB. However, upon more closely examining the data, he found that his stronger students (those who earned A’s in the class) tended to like this program less that did students who earned lower grades. Xiaoxu uses the students’ own words to explore the determinants of their satisfaction (or dissatisfaction) with MATLAB and from there attempts to explore grade-based disparity. This discussion leads him to some interesting ideas about next stages in his teaching this course and, hopefully, in continuing this scholarly project

WDM transmission over 320 km EDFA-amplified SSMF using 30 Gb/s return-to-zero optical differential 8-level phase-shift keying (OD8PSK)

Fiber transmission of optical differential 8- level phase- shift keying ( OD8PSK) signals is demonstrated for the first time. Co- polarized 8 WDM channels of 10 Giga- symbol/ s or 30 Gb/ s return- to- zero ( RZ) OD8PSK signals with a channel spacing of 50 GHz were transmitted over 320 km of standard single mode fiber ( SSMF) with an EDFA spacing of 80 km. The BER of the worst WDM channel after transmission of 320 km was 2.3 x 10(-5)

Cross-Continental Dispersal of Major HIV-1 CRF01_AE Clusters in China.

Since the 1990s, several distinct clusters of human immunodeficiency virus-type 1 (HIV-1) CRF01_AE related to a large epidemic in China have been identified, but it is yet poorly understood whether its transmission has dispersed globally. We aimed to characterize and quantify the genetic relationship of HIV-1 CRF01_AEs circulating in China and other countries. Using representative sequences of Chinese clusters as queries, all relevant CRF01_AE pol sequences in two large databases (the Los Alamos HIV sequence database and the UK HIV Drug Resistance Database) were selected with the online basic local alignment search (BLAST) tool. Phylogenetic and phylogeographic analyses were then carried out to characterize possible linkage of CRF01_AE strains between China and the rest of the world. We identified that 269 strains isolated in other parts of the world were associated with five major Chinese CRF01_AE clusters. 80.7% were located within CN.01AE.HST/IDU-2, most of which were born in Southeast Asia. 17.8% were clustered with CN.01AE.MSM-4 and -5. Two distinct sub-clusters associated with Chinese men who have sex with men (MSM) emerged in HK-United Kingdom and Japan after 2000. Our analysis suggests that HIV-1 CRF01_AE strains related to viral transmission in China were initially brought to the United Kingdom or other countries during the 1990s by Asian immigrants or returning international tourists from Southeast Asia, and then after having circulated among MSM in China for several years, these Chinese strains dispersed outside again, possibly through MSM network. This study provided evidence of regional and global dispersal of Chinese CRF01_AE strains. It would also help understand the global landscape of HIV epidemic associated with CRF01_AE transmission and highlight the need for further international collaborative study in this field

EXTRACT OF PERILLA FRUTESCENS INHIBITS TUMOR PROLIFERATION OF HCC VIA PI3K/AKT SIGNAL PATHWAY

In this study, isoegomaketone(IK) was isolated from Perilla frutescens(L.), a Chinese herbal. The effects of IK were examined by cell viability assay, colony formation assay, xenograft tumor assay and western blotting in HCC cells. We found that IK inhibited cell viability, and its administration decreased tumor volume and weight profoundly. The presence of IK(10nmol/l) produced a dramatic decrease of pAkt, while total Akt level was not affected. The data suggested that IK from perilla suppressed HCC tumor growth via blocking PI3K/Akt signaling pathway

Observation of unconventional van der Waals multiferroics near room temperature

The search for two-dimensional (2D) van der Waals (vdW) multiferroics is an exciting yet challenging endeavor. Room-temperature 2D vdW few-layer multiferroic is a much bigger insurmountable obstacle. Here we report the discovery of an unconventional 2D vdW multiferroic with out-of-plane ferroelectric polarization and long-range magnetic orders in trilayer NiI2 device from 10 K to 295 K. The evolutions of magnetic domains with magnetic field, and the evolutions between ferroelectric and antiferroelectric phase have been unambiguously observed. More significantly, we realize a robust mutual control of magnetism and ferroelectricity at room temperature. The magnetic domains are manipulated by a small voltage ranging from 1 V to 6 V at 0 T and 295 K. This work opens opportunities for exploring multiferroic physics at the limit of few atomic layers.Comment: 4 figure

Optimization of genetic distance threshold for inferring the CRF01_AE molecular network based on next-generation sequencing

IntroductionHIV molecular network based on genetic distance (GD) has been extensively utilized. However, the GD threshold for the non-B subtype differs from that of subtype B. This study aimed to optimize the GD threshold for inferring the CRF01_AE molecular network.MethodsNext-generation sequencing data of partial CRF01_AE pol sequences were obtained for 59 samples from 12 transmission pairs enrolled from a high-risk cohort during 2009 and 2014. The paired GD was calculated using the Tamura-Nei 93 model to infer a GD threshold range for HIV molecular networks.Results2,019 CRF01_AE pol sequences and information on recent HIV infection (RHI) from newly diagnosed individuals in Shenyang from 2016 to 2019 were collected to construct molecular networks to assess the ability of the inferred GD thresholds to predict recent transmission events. When HIV transmission occurs within a span of 1-4 years, the mean paired GD between the sequences of the donor and recipient within the same transmission pair were as follow: 0.008, 0.011, 0.013, and 0.023 substitutions/site. Using these four GD thresholds, it was found that 98.9%, 96.0%, 88.2%, and 40.4% of all randomly paired GD values from 12 transmission pairs were correctly identified as originating from the same transmission pairs. In the real world, as the GD threshold increased from 0.001 to 0.02 substitutions/site, the proportion of RHI within the molecular network gradually increased from 16.6% to 92.3%. Meanwhile, the proportion of links with RHI gradually decreased from 87.0% to 48.2%. The two curves intersected at a GD of 0.008 substitutions/site.DiscussionA suitable range of GD thresholds, 0.008-0.013 substitutions/site, was identified to infer the CRF01_AE molecular transmission network and identify HIV transmission events that occurred within the past three years. This finding provides valuable data for selecting an appropriate GD thresholds in constructing molecular networks for non-B subtypes

Low-level viremia episodes appear to affect the provirus composition of the circulating cellular HIV reservoir during antiretroviral therapy

Low-level viremia (LLV) ranging from 50 to 1,000 copies/ml is common in most HIV-1-infected patients receiving antiretroviral therapy (ART). However, the source of LLV and the impact of LLV on the HIV-1 reservoir during ART remain uncertain. We hypothesized that LLV may arise from the HIV reservoir and its occurrence affect the composition of the reservoir after LLV episodes. Accordingly, we investigated the genetic linkage of sequences obtained from plasma at LLV and pre-ART time points and from peripheral blood mononuclear cells (PBMCs) at pre-ART, pre-LLV, LLV, and post-LLV time points. We found that LLV sequences were populated with a predominant viral quasispecies that accounted for 67.29%∼100% of all sequences. Two episodes of LLV in subject 1, spaced 6 months apart, appeared to have originated from the stochastic reactivation of latently HIV-1-infected cells. Moreover, 3.77% of pre-ART plasma sequences were identical to 67.29% of LLV-3 plasma sequences in subject 1, suggesting that LLV may have arisen from a subset of cells that were infected before ART was initiated. No direct evidence of sequence linkage was found between LLV viruses and circulating cellular reservoirs in all subjects. The reservoir size, diversity, and divergence of the PBMC DNA did not differ significantly between the pre- and post-LLV sampling points (P > 0.05), but the composition of viral reservoir quasispecies shifted markedly before and after LLV episodes. Indeed, subjects with LLV had a higher total PBMC DNA level, greater viral diversity, a lower proportion of variants with identical sequences detected at two or more time points, and a shorter variant duration during ART compared with subjects without LLV. Overall, our findings suggested that LLV viruses may stem from an unidentified source other than circulating cellular reservoirs. LLV episodes may introduce great complexity into the HIV reservoir, which brings challenges to the development of treatment strategies

Niclosamide Induces Cell Cycle Arrest in G1 Phase in Head and Neck Squamous Cell Carcinoma Through Let-7d/CDC34 Axis

Niclosamide is a traditional anti-tapeworm drug that exhibits potent anti-cancer activity. Our previous study showed that niclosamide induces cell cycle arrest in G1 phase. Nevertheless, the underlying mechanism remains unknown. The following study investigated the molecular mechanism through which niclosamide induced G1 arrest in head and neck squamous cell carcinoma (HNSCC) cell lines. The effect of niclosamide on human HNSCC cell line WSU-HN6 and CNE-2Z were analyzed using IncuCyte ZOOMTM assay, flow cytometry (FCM), real-time PCR and western blot. Luciferase assay was conducted to demonstrate the interaction between let-7d (a let-7 family member which functions as a tumor suppressor by regulating cell cycle) and 3′UTR of CDC34 mRNA. Xenografts tumor model was established to evaluate the niclosamide treatment efficacy in vivo. Briefly, an exposure to niclosamide treatment led to an increased let-7d expression and a decreased expression of cell cycle regulator CDC34, finally leading to G1 phase arrest. Moreover, an overexpression of let-7d induced G1 phase arrest and downregulated CDC34, while the knockdown of let-7d partially rescued the niclosamide-induced G1 phase arrest. Luciferase assay confirmed the direct inhibition of CDC34 through the targeting of let-7d. Furthermore, niclosamide markedly inhibited the xenografts growth through up-regulation of let-7d and down-regulation of CDC34. To sum up, our findings suggest that niclosamide induces cell cycle arrest in G1 phase in HNSCC through let-7d/CDC34 axis, which enriches the anti-cancer mechanism of niclosamide

Advances in molecular biological research of Angelica sinensis

Angelica sinensis (Oliv.) Diels belongs to the Apiaceae family. The root of A. sinensis, is used in traditional Chinese medicine for its antioxidant and immune regulation properties. The main active compounds in A. sinensis include organic acids, phthalides and coumarins, and their biosynthetic pathways are the focus of international attention. A. sinensis is prone to early flowering and bolting, which negatively impacts production for several reasons, including germplasm degradation and quality instability in artificial cultivation. The identification of top-geoherbalism of A. sinensis has also become the focus of recent research, as it would allow selection for breeds with excellent medicinal quality and remarkable curative effects. Advances in sequencing technology and bioinformatic methodologies have enabled extensive molecular and genetic studies in A. sinensis. In this review, we summarize the latest molecular research advances related to A. sinensis, including biosynthetic pathways and regulation of active compounds, and molecular underpinnings of early bolting and flowering and top-geoherbalism. We discuss limitations of the current research and propose prospective topics in need of further exploration

Single-image based deep learning for precise atomic defects identification

Defect engineering has been profoundly employed to confer desirable functionality to materials that pristine lattices inherently lack. Although single atomic-resolution scanning transmission electron microscopy (STEM) images are widely accessible for defect engineering, harnessing atomic-scale images containing various defects through traditional image analysis methods is hindered by random noise and human bias. Yet the rise of deep learning (DL) offering an alternative approach, its widespread application is primarily restricted by the need for large amounts of training data with labeled ground truth. In this study, we propose a two-stage method to address the problems of high annotation cost and image noise in the detection of atomic defects in monolayer 2D materials. In the first stage, to tackle the issue of data scarcity, we employ a two-state transformation network based on U-GAT-IT for adding realistic noise to simulated images with pre-located ground truth labels, thereby infinitely expanding the training dataset. In the second stage, atomic defects in monolayer 2D materials are effectively detected with high accuracy using U-Net models trained with the data generated in the first stage, avoiding random noise and human bias issues. In both stages, we utilize segmented unit-cell-level images to simplify the model's task and enhance its accuracy. Our results demonstrate that not only sulfur vacancies, we are also able to visualize oxygen dopants in monolayer MoS2, which are usually overwhelmed by random background noise. As the training was based on a few segmented unit-cell-level realistic images, this method can be readily extended to other 2D materials. Therefore, our results outline novel ways to train the model with minimized datasets, offering great opportunities to fully exploit the power of machine learning (ML) applicable to a broad materials science community