FOXM1 coming of age: time for translation into clinical benefits?

A decade since the first evidence implicating the cell cycle transcription factor Forkhead Box M1 (FOXM1) in human tumorigenesis, a slew of subsequent studies revealed an oncogenic role of FOXM1 in the majority of human cancers including oral, nasopharynx, oropharynx, esophagus, breast, ovary, prostate, lung, liver, pancreas, kidney, colon, brain, cervix, thyroid, bladder, uterus, testis, stomach, skin, and blood. Its aberrant upregulation in almost all different cancer types suggests a fundamental role for FOXM1 in tumorigenesis. Its dose-dependent expression pattern correlated well with tumor progression starting from cancer predisposition and initiation, early premalignancy and progression, to metastatic invasion. In addition, emerging studies have demonstrated a causal link between FOXM1 and chemotherapeutic drug resistance. Despite the well-established multifaceted roles for FOXM1 in all stages of oncogenesis, its translation into clinical benefit is yet to materialize. In this contribution, I reviewed and discussed how our current knowledge on the oncogenic mechanisms of FOXM1 could be exploited for clinical use as biomarker for risk prediction, early cancer screening, molecular diagnostics/prognostics, and/or companion diagnostics for personalized cancer therapy

Identification of multidrug chemoresistant genes in head and neck squamous cell carcinoma cells

Multidrug resistance renders treatment failure in a large proportion of head and neck squamous cell carcinoma (HNSCC) patients that require multimodal therapy involving chemotherapy in conjunction with surgery and/or radiotherapy. Molecular events conferring chemoresistance remain unclear. Through transcriptome datamining, 28 genes were subjected to pharmacological and siRNA rescue functional assays on 12 strains of chemoresistant cell lines each against cisplatin, 5-fluorouracil (5FU), paclitaxel (PTX) and docetaxel (DTX). Ten multidrug chemoresistance genes (TOP2A, DNMT1, INHBA, CXCL8, NEK2, FOXO6, VIM, FOXM1B, NR3C1 and BIRC5) were identified. Of these, four genes (TOP2A, DNMT1, INHBA and NEK2) were upregulated in an HNSCC patient cohort (n = 221). Silencing NEK2 abrogated chemoresistance in all drug-resistant cell strains. INHBA and TOP2A were found to confer chemoresistance in majority of the drug-resistant cell strains whereas DNMT1 showed heterogeneous results. Pan-cancer Kaplan-Meier survival analysis on 21 human cancer types revealed significant prognostic values for INHBA and NEK2 in at least 16 cancer types. Drug library screens identified two compounds (Sirodesmin A and Carfilzomib) targeting both INHBA and NEK2 and re-sensitised cisplatin-resistant cells. We have provided the first evidence for NEK2 and INHBA in conferring chemoresistance in HNSCC cells and siRNA gene silencing of either gene abrogated multidrug chemoresistance. The two existing compounds could be repurposed to counteract cisplatin chemoresistance in HNSCC. This finding may lead to novel personalised biomarker-linked therapeutics that can prevent and/or abrogate chemoresistance in HNSCC and other tumour types with elevated NEK2 and INHBA expression. Further investigation is necessary to delineate their signalling mechanisms in tumour chemoresistance

Development of physical and mathematical models for the Porous Ceramic Tube Plant Nutrification System (PCTPNS)

A physical model of the Porous Ceramic Tube Plant Nutrification System (PCTPNS) was developed through microscopic observations of the tube surface under various operational conditions. In addition, a mathematical model of this system was developed which incorporated the effects of the applied suction pressure, surface tension, and gravitational forces as well as the porosity and physical dimensions of the tubes. The flow of liquid through the PCTPNS was thus characterized for non-biological situations. One of the key factors in the verification of these models is the accurate and rapid measurement of the 'wetness' or holding capacity of the ceramic tubes. This study evaluated a thermistor based moisture sensor device and recommendations for future research on alternative sensing devices are proposed. In addition, extensions of the physical and mathematical models to include the effects of plant physiology and growth are also discussed for future research

Impact of N-Terminal Tags on De Novo Vimentin Intermediate Filament Assembly

Vimentin, a type III intermediate filament protein, is found in most cells along with microfilaments and microtubules. It has been shown that the head domain folds back to associate with the rod domain and this association is essential for filament assembly. The N-terminally tagged vimentin has been widely used to label the cytoskeleton in live cell imaging. Although there is previous evidence that EGFP tagged vimentin fails to form filaments but is able to integrate into a pre-existing network, no study has systematically investigated or established a molecular basis for this observation. To determine whether a tag would affect de novo filament assembly, we used vimentin fused at the N-terminus with two different sized tags, AcGFP (239 residues, 27 kDa) and 3 × FLAG (22 residues; 2.4 kDa) to assemble into filaments in two vimentin-deficient epithelial cells, MCF-7 and A431. We showed that regardless of tag size, N-terminally tagged vimentin aggregated into globules with a significant proportion co-aligning with β-catenin at cell–cell junctions. However, the tagged vimentin aggregates could form filaments upon adding untagged vimentin at a ratio of 1:1 or when introduced into cells containing pre-existing filaments. The resultant filament network containing a mixture of tagged and untagged vimentin was less stable compared to that formed by only untagged vimentin. The data suggest that placing a tag at the N-terminus may create steric hinderance in case of a large tag (AcGFP) or electrostatic repulsion in case of highly charged tag (3 × FLAG) perhaps inducing a conformational change, which deleteriously affects the association between head and rod domains. Taken together our results shows that a free N-terminus is essential for filament assembly as N-terminally tagged vimentin is not only incapable of forming filaments, but it also destabilises when integrated into a pre-existing network

Efficacy of three antimicrobial mouthwashes in reducing SARS-CoV-2 viral load in the saliva of hospitalized patients: a randomized controlled pilot study

Abstract This study aimed to evaluate the efficacy of 3 mouthwashes in reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load in the saliva of coronavirus disease 2019 (COVID-19) patients at 30 min, 1, 2 and 3 h after rinsing. This pilot study included 40 admitted COVID-19 positive patients (10 in each group). Saliva samples were collected before rinsing and at 30 min, 1, 2 and 3 h after rinsing with: Group 1—0.2% Chlorhexidine digluconate (CHX); Group 2—1.5% Hydrogen peroxide (H2O2); Group 3—Cetylpyridinium chloride (CPC) or Group 4 (control group)—No rinsing. Viral load analysis of saliva samples was assessed by Reverse Transcription quantitative PCR. Mean log10 viral load at different time points was compared to that at baseline in all groups using a random effects linear regression analysis while for comparison between groups linear regression analysis was used. The results showed that all groups had a significantly reduced mean log10 viral load both at 2 (p = 0.036) and 3 (p = 0.041) hours compared to baseline. However, there was no difference in mean log10 viral load between any of the investigated mouthwashes and the control group (non-rinsing) at the evaluated time points. Although a reduction in the SARS-CoV-2 viral load in the saliva of COVID-19 patients was observed after rinsing with mouthwashes containing 0.2% CHX, 1.5% H2O2, or CPC, the reduction detected was similar to that achieved by the control group at the investigated time points. The findings of this study may suggest that the mechanical action of rinsing/spitting results in reduction of SARS-CoV-2 salivary load

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 201

Modelling ambitious climate mitigation pathways for Australia's built environment

Achieving net zero operational and embodied greenhouse gas (GHG) emissions in the built environment is recognised in Australia and globally as a key strategy to address climate change and achieve the United Nations Sustainable Development Goals (SDGs). However, gaps in knowledge remain regarding potential national pathways to achieve this outcome in Australia. This study further extends and applies a national-scale integrated macroeconomic simulation model to explore coherent pathways to net zero emissions in the built environment sector by 2050. The scope of the study includes residential and commercial buildings and both operational and embodied emissions. It applies scenario analysis incorporating different levels of climate ambition, including a shift to renewable energy, electrifying buildings, improving energy efficiency and replacing carbon-intensive materials. We find that a high ambition scenario (Scenario 2) delivers a 94% reduction in GHG emissions by 2050 when compared against business-as-usual, placing a net-zero target within reach. Improvements on Australia's SDGs performance are also attained. Through subsequent pathways analysis we find that achieving net zero or even net negative operational and embodied emissions is feasible with more ambitious action in key areas, including increasing the share of mass-timber buildings and reducing end-of-life losses in sequestered carbon

Land Cover Mapping Using High Spatial Resolution SPOT Data Over Penang Island Malaysia.

Satellite digital imagery has proved to be an effective tool for land cover changes studies. The objective of this study is to demonstrate the effectiveness of SPOT imageries in changes detection over Penang Island, Malaysia. An understanding of land use/land cover at local with high resolution is important to prepare the latest data and can be used in many purposes. The neural network classifier was performed to the satellite images and the results were compared with four standard supervised classification techniques, such as the maximum likelihood, minimum distance-to-mean and parallelepiped