Yang Jiang

Comparative to conventional 2D interaction methods, virtual reality (VR) demonstrates an opportunity for unique interface and interaction design decisions. Currently, this poses a challenge when developing an accessible VR experience as existing interaction techniques may not be usable by all users. It was discovered that many traditional 2D interface interaction methods have been directly converted to work in a VR space with little alteration to the input mechanism, such as the use of a laser pointer designed to that of a traditional cursor. It is recognized that distanceindependent millimetres can support designers in developing interfaces that scale in virtual worlds. Relevantly, Fitts law states that as distance increases, user movements are increasingly slower and performed less accurately. In this paper we propose the use of a low pass filter, to normalize user input noise, alleviating fine motor requirements during ray-based interaction. A development study was conducted to understand the feasibility of implementing such a filter and explore its effects on end users experience. It demonstrates how an algorithm can provide an opportunity for a more accurate and consequently less frustrating experience by filtering and reducing involuntary hand tremors. Further discussion on existing VR design philosophies is also conducted, analysing evidence that supports multisensory feedback and psychological models. The completed study can be downloaded from GitHub.

Fashion industry emissions, resource use, and waste are attracting increasing consumer and government attention, with broad agreement that a new approach is required along the supply chain. Following the COVID-19 pandemic, a move to digitalisation facilitated an accelerating interest in digital applications, including immersive technologies such as augmented and virtual reality. This systematic literature review explores the intersecting topics of fashion, immersive technologies, and sustainability to determine the trends, examine the solutions offered, and discuss the implications of immersive technologies for sustainability. Four resources were consulted (Scholar, SCOPUS, WOS, and ProQuest), resulting in 74 articles for the review. Grey literature was included due to the currency of the topic and gaps in the available academic literature. The findings highlight immersive technology uses in the fashion industry, which are part of a move towards sustainability. These technologies are used to reduce online returns, educate consumers, reduce waste in design and manufacture, and remove the need for physical items. However, issues include high energy costs, consumer reluctance, and skill shortages. Results suggest future research and industry discussions should focus on empirical studies to measure the sustainability impact of immersive technologies, monitor technology diffusion and uptake, and measure the industry skills gap.

Fast and effectively disposable fashion has seen clothing reduced to transient items, worn for a short period of time then discarded. This has pushed down prices, moving textile and clothing production to low-cost labour countries and decimating the traditional Scottish textile economy. Fast fashion drives consumer demand for newness and uses finite resources that are damaging to the environment. In 2019, the pressure to move towards a more sustainable fashion and textile industry is intense. Traditional textile manufacture using natural, renewable sources that are inherently long-lasting offers a slow fashion alternative, epitomized by the Harris Tweed handweaver community in Scotland. Fashion has embraced digital, with growing online sales and increasing focus on digital content. This presents an opportunity to redress the balance by using technology to shape a sustainable future for traditional textiles. Utilizing an interpretive paradigm and inductive approach, an Arts and Humanities Research Council (AHRC) funded networking grant is presented as a qualitative case study, investigating how immersive technologies can be used to safeguard the future of traditional textile products, to educate contemporary, global audiences on the provenance and human hand behind manufacturing processes and to encourage consumption of products with longevity. This explanatory case study finds that fashion brands are using immersive technologies for virtual changing rooms or creative customer experiences but are not exploiting the possibilities of immersive technologies in engendering a sense of place or people behind the product. Findings also reveal that the Harris Tweed Authority and Harris Tweed Hebrides brand successfully use landscape to convey a sense of place, but are under-utilizing the handwoven value and sustainable, slow fashion credentials of Harris Tweed. China is identified as a potential place for Harris Tweed to gain valuable market share, with increasingly wealthy Chinese Generation Z consumers seeking individual exclusivity and sustainability in their clothing purchases, criteria that embody Harris Tweed.

As a pathological condition, epilepsy is caused by abnormal neuronal discharge in brain which will temporarily disrupt the cerebral functions. Epilepsy is a chronic disease which occurs in all ages and would seriously affect patients’ personal lives. Thus, it is highly required to develop effective medicines or instruments to treat the disease. Identifying epilepsy-related genes is essential in order to understand and treat the disease because the corresponding proteins encoded by the epilepsy-related genes are candidates of the potential drug targets. In this study, a pioneering computational workflow was proposed to predict novel epilepsy-related genes using the random walk with restart (RWR) algorithm. As reported in the literature RWR algorithm often produces a number of false positive genes, and in this study a permutation test and functional association tests were implemented to filter the genes identified by RWR algorithm, which greatly reduce the number of suspected genes and result in only thirty-three novel epilepsy genes. Finally, these novel genes were analyzed based upon some recently published literatures. Our findings implicate that all novel genes were closely related to epilepsy. It is believed that the proposed workflow can also be applied to identify genes related to other diseases and deepen our understanding of the mechanisms of these diseases.

Non-small cell lung cancer (NSCLC) is a potentially fatal disease and the incidence is increasing annually. In order to diagnose and treat NSCLC effectively, greater understanding of its molecular mechanism is required. In the present study, 36 NSCLC tissues and 10 normal tissues were selected. Reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) was used to analyze the CD44 mRNA expression level in NSCLC tissue and DNA sequencing was performed to further verify the CD44 expression level. Differentially expressed genes between tumor tissues and controls were determined by DNA sequencing and the Gene_act_net between CD44 and its associated genes was constructed. Gene Ontology (GO) term enrichment analysis of the differentially expressed genes was performed by the Biological Networks Gene Ontology tool. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed based on the Expression Analysis Systematic Explorer test applied in the Database for Annotation, Visualization and Integrated Discovery. RT‑qPCR results showed that CD34 was overexpressed in 21 of the 36 NSCLC tissues (58.3%). The Gene_act_net indicated that there were 20 differentially expressed genes with 17 upregulated and 3 downregulated. Among them, CD44, MET, ERBB2, EGFR, AKT1, IQGAP1 and STAT3 were associated with the occurrence and migration of NSCLC. In KEGG pathway analysis, extracellular matrix‑receptor interaction and hematopoietic cell lineage pathways were the most affected by overexpressed CD44; and thus may be important in the development and migration of NSCLC. In conclusion, CD44 was overexpressed in NSCLC and the overexpression was associated with the occurrence of NSCLC and migration of NSCLC cells.

Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of “cancer drivers” connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels.

Astrocytomas is one of the most common central nervous system (CNS) tumors with high mortality rate. Kinase insert domain receptor (KDR) is involved in the regulation of tumor angiogenesis, migration, and vascular permeability. The aim of the study was to explore the relationship between KDR polymorphisms and risk of astrocytomas. Blood samples were collected from 157 astrocytomas patients and 160 healthy controls. Three tag-SNPs (rs2071559C/T, rs2305948T/C, and rs1870377A/T) were identified from the International HapMap Project Databases and genotyped using the method of polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). We evaluated the astrocytomas risk caused by individual SNPs and haplotype using odds ratios (ORs) and their 95 % confidence intervals (CIs). In the overall individual SNP analysis, the C allele of rs2071559 was correlated with an increased risk of astrocytomas. However, individuals with mutant allele A and genotype TA + AA of rs1870377 showed a protective effect against astrocytomas. Subgroup analysis based on WHO tumor grade revealed that the C allele of rs2071559 had more influence with the risk of astrocytomas in the grade III–IV (OR = 1.91) subgroup than the grade I–II (OR = 1.47) group. Genotype TT of rs2305948 was found to be significantly associated with susceptibility of astrocytomas only in the grade III–IV subgroup. The protective effect of rs1870377 did not reveal significant difference between the grade III–IV and grade I–II subgroups. Meanwhile, stratified analysis demonstrated that mutation of rs2071559 and rs2305948 could elevate the risk of astrocytomas more significantly in the subgroup of smokers than the nonsmokers. Interestingly, the protective effect of rs1870377 was more obvious in the nonsmokers than the smokers. Additionally, haplotype-specific analysis showed that haplotype CCT and CTT were related with an increased risk of astrocytomas. We found that individual with variants of rs2071559*C and rs2305948*T might significantly elevate the risk of astrocytomas, while mutants of rs1870377*A was associated with the decreased risk of astrocytomas. Further studies about ethnically diverse populations with larger sample size should be performed to confirm the correlation between KDR gene polymorphisms and risk of astrocytomas.

Cancer is a serious disease responsible for many deaths every year in both developed and developing countries. One reason is that the mechanisms underlying most types of cancer are still mysterious, creating a great block for the design of effective treatments. In this study, we attempted to clarify the mechanism underlying esophageal cancer by searching for novel genes and chemicals. To this end, we constructed a hybrid network containing both proteins and chemicals, and generalized an existing computational method previously used to identify disease genes to identify new candidate genes and chemicals simultaneously. Based on jackknife test, our generalized method outperforms or at least performs at the same level as those obtained by a widely used method - the Random Walk with Restart (RWR). The analysis results of the final obtained genes and chemicals demonstrated that they highly shared gene ontology (GO) terms and KEGG pathways with direct and indirect associations with esophageal cancer. In addition, we also discussed the likelihood of selected candidate genes and chemicals being novel genes and chemicals related to esophageal cancer.

The aim of this study was to identify critical gene pathways that are associated with lung cancer metastasis to the brain. The RNA-Seq approach was used to establish the expression profiles of a primary lung cancer, adjacent benign tissue, and metastatic brain tumor from a single patient. The expression profiles of these three types of tissues were compared to define differentially expressed genes, followed by serial-cluster analysis, gene ontology analysis, pathway analysis, and knowledge-driven network analysis. Reverse transcription–polymerase chain reaction (RT-PCR) was used to validate the expression of essential candidate genes in tissues from ten additional patients. Differential gene expression among these three types of tissues was classified into multiple clusters according to the patterns of their alterations. Further bioinformatic analysis of these expression profile data showed that the network of the signal transduction pathways related to actin cytoskeleton reorganization, cell migration, and adhesion was associated with lung cancer metastasis to the brain. The expression of ACTN4 (actinin, alpha 4), a cytoskeleton protein gene essential for cytoskeleton organization and cell motility, was significantly elevated in the metastatic brain tumor but not in the primary lung cancer tissue. The signaling pathways involved in the regulation of cytoskeleton reorganization, cell motility, and focal adhesion play a role in the process of lung cancer metastasis to the brain. The contribution of ACTN4 to the process of lung cancer metastasis to the brain could be mainly through regulation of actin cytoskeleton reorganization, cell motility, and focal adhesion.