Home nursing and self-administered outpatient parenteral antimicrobial treatment: a comparison of demographics and outcomes from a large regional hospital in Queensland, Australia.

BACKGROUND: Outpatient parenteral antimicrobial treatment (OPAT) is a safe and effective therapy used in several settings across Australia. As OPAT services expand their inclusion criteria to include complex patient populations, there is an increased need for selecting appropriate patients to receive either healthcare-administered OPAT (H-OPAT) or self-administered OPAT (S-OPAT). AIMS: To describe patient demographics, diagnosis, microbiology and outcomes of patients treated by H-OPAT and S-OPAT within the Sunshine Coast Hospital and Health Service, Australia. METHODS: Data on demographics, diagnoses, treatment and outcomes on all patients treated by H-OPAT and S-OPAT from March 2017 to December 2019 were collected retrospectively. RESULTS: One hundred and sixty-five patients (62.26%) were enrolled in H-OPAT and 100 patients (37.74%) in S-OPAT. S-OPAT patients were significantly younger. H-OPAT patients were more comorbid. Bone and joint infections were the most treated infections and were more likely to be treated by S-OPAT. There was no difference in treatment duration, cure and complication rates between S-OPAT and H-OPAT. Longer duration of therapy was associated with more complications. Treatment failure was associated with infections due to multiple organisms, number of comorbidities and treatment of surgical site, skin and soft tissue infections. CONCLUSIONS: There were significant differences in demographics between H-OPAT and S-OPAT without any difference in outcomes. Overall failure and complication rates were low. Higher rates of treatment failure were predicted by the diagnosis, number of comorbidities and number of organisms treated.

Multi-omic and spatial dissection of immunotherapy response groups in non-small cell lung cancer.

The composition and activation status of the cellular milieu contained within the tumour microenvironment (TME) is becoming increasingly recognized as a driving factor for immunotherapy response. Here, we employed multiplex immunohistochemistry (mIHC), and digital spatial profiling (DSP) to capture the targeted immune proteome and transcriptome of tumour and TME compartments from an immune checkpoint inhibitor (ICI)-treated (n = 41) non-small cell lung cancer (NSCLC) patient cohort. We demonstrate by mIHC that the interaction of CD68+ macrophages with PD1+ , FoxP3+ cells is enriched in ICI refractory tumours (p = 0.012). Patients responsive to ICI therapy expressed higher levels of IL2 receptor alpha (CD25, p = 0.028) within their tumour compartments, which corresponded with increased IL2 mRNA (p = 0.001) within their stroma. In addition, stromal IL2 mRNA levels positively correlated with the expression of pro-apoptotic markers cleaved caspase 9 (p = 2e-5 ) and BAD (p = 5.5e-4 ) and negatively with levels of memory marker, CD45RO (p = 7e-4 ). Immuno-inhibitory markers CTLA-4 (p = 0.021) and IDO-1 (p = 0.023) were suppressed in ICI-responsive patients. Tumour expression of CD44 was depleted in the responsive patients (p = 0.02), while higher stromal expression of one of its ligands, SPP1 (p = 0.008), was observed. Cox survival analysis also indicated tumour CD44 expression was associated with poorer prognosis (hazard ratio [HR] = 1.61, p = 0.01), consistent with its depletion in ICI-responsive patients. Through multi-modal approaches, we have dissected the characteristics of NSCLC immunotherapy treatment groups and provide evidence for the role of several markers including IL2, CD25, CD44 and SPP1 in the efficacy of current generations of ICI therapy.

Genetically encoded Runx3 and CD4+ intestinal epithelial lymphocyte deficiencies link SKG mouse and human predisposition to spondyloarthropathy.

Disturbances in immune regulation, intestinal dysbiosis and inflammation characterize ankylosing spondylitis (AS), which is associated with RUNX3 loss-of-function variants. ZAP70W163C mutant (SKG) mice have reduced ZAP70 signaling, spondyloarthritis and ileitis. In small intestine, Foxp3+ regulatory T cells (Treg) and CD4+CD8αα+TCRαß+ intraepithelial lymphocytes (CD4-IEL) control inflammation. TGF-ß and retinoic acid (RA)-producing dendritic cells and MHC-class II+ intestinal epithelial cells (IEC) are required for Treg and CD4-IEL differentiation from CD4+ conventional or Treg precursors, with upregulation of Runx3 and suppression of ThPOK. We show in SKG mouse ileum, that ZAP70W163C or ZAP70 inhibition prevented CD4-IEL but not Treg differentiation, dysregulating Runx3 and ThPOK. TGF-ß/RA-mediated CD4-IEL development, T-cell IFN-γ production, MHC class-II+ IEC, tissue-resident memory T-cell and Runx3-regulated genes were reduced. In AS intestine, CD4-IEL were decreased, while in AS blood CD4+CD8+ T cells were reduced and Treg increased. Thus, genetically-encoded TCR signaling dysfunction links intestinal T-cell immunodeficiency in mouse and human spondyloarthropathy.

Florid Lymphoid Hyperplasia or Lymphoma-like Lesion of the Lower Genital Tract: A 35-Year Literature Review in View of the New WHO Classification.

Florid lymphoid hyperplasias of the lower female genital tract, also known as pseudolymphoma or lymphoma-like lesions, are benign lesions displaying histologic features which mimic aggressive B-cell lymphomas. Initially described by Young and colleagues in 1985, fewer than 100 cases have been published, making this lesion rather uncommon and subject to misdiagnoses. However, given that this entity has now been included in the World Health Organization's most recent classification, greater clarity would be beneficial for pathologists and physicians. Thus, our report aims to review these entities and provide all available data. We reviewed the available literature according to PRISMA guidelines. We found that lymphoma-like lesions, regardless of their localization, display numerous superficial lymphoid B cells admixed with a polymorphic small lymphocytic and plasmocytic background and, sometimes, superficial ulceration. Large lymphoid cells show prominent nucleoli and mitotic figures. Immunohistochemistry can usually exclude large cell lymphomas, such as high-grade follicular lymphoma and Burkitt lymphoma, when a starry sky pattern is found, as well as Hodgkin Lymphoma; however, the exclusion of diffuse large B-cell lymphoma or marginal zone lymphoma is more difficult. Explorations seeking infectious agents may show Epstein-Barr virus or, rarely, Borrelia burgdorferi involvement. Molecular study occasionally finds a monoclonal B-cell population, but without the subsequent follow-up which would otherwise be worrisome. Despite its somewhat aggressive histologic features, the benignity of this entity must be highlighted to avoid misdiagnosis and complications due to overtreating.

Rheumatoid arthritis is a preventable disease: 11 ways to reduce your patients' risk.

New evidence shows that up to 40% of rheumatoid arthritis (RA) cases are attributable to exposure to potentially modifiable factors. We can now identify people at higher risk of RA (pre-RA) through their family history, risk factors, autoantibodies and symptoms. Counselling these patients to act to modify factors known to be associated with RA risk could prevent the development of RA, and evidence shows that informing individuals of their risk and of ways to reduce it leads to positive behavioural change and is not harmful. This consumer-focussed narrative review is targeted at primary care providers and physicians to describe 11 changes that can be made, based on current evidence linking potentially modifiable factors to RA risk. These evidence-based recommendations are: (i) cease smoking; (ii) reduce exposure to inhaled silica, dusts and occupational risks; (iii) maintain a healthy weight; (iv) increase leisure time physical activity; (v) maintain good dental hygiene; (vi) maximise breastfeeding if able; (vii) maximise dietary quality and avoid high-salt diets; (viii) consume high levels of omega-3 fatty acids and fish; (ix) reduce consumption of sugar-sweetened soft drinks; (x) consume moderate levels of alcohol; and (xi) remain vitamin D replete.

Prevalence of neoplasia in solitary and multiple esophago-gastrointestinal polyps: 5 years retrospective histopathological study.

The increasing use of endoscopy has led to more discernable abnormalities in the stomach, including polyps. Gastric polyps encompass a spectrum of pathologic conditions that can vary in histology, neoplastic potential, and management. Despite their high prevalence, there is a paucity of literature to support management and treatment decisions for endoscopists. The goal of this review is to summarize clinical, endoscopic, and histopathologic features of various polyps, review syndromes associated with such polyps and provide management recommendations. The present study was carried out for analyzing and comparing the prevalence of neoplasia in polyps (Solitary and multiple) removed endoscopically from the esophagus, stomach, and bowel undergoing screening. Five years retrospective study was done on patients who underwent endoscopy procedures including Oesophagogastroduodenoscopy (OGD) and colonoscopy between June 2015 and March 2019 in Faruk Medical City Hospital, Sulaimani City. Age and sex of patients, site of occurrence, number of polyps (solitary or multiple), and polyps' histologic type of 369 cases were analyzed in this study. Regarding solitary polyps, out of 279 polyps, 155 were neoplastic (55%) and 124 were non-neoplastic polyps, while multiple polyps, out of a total of 90 cases, 68 were neoplastic (75%) and 22 were non-neoplastic. More than 78% of patients were above the age of 40 years. Tubular adenoma was the most commonly diagnosed polyp. Large bowel was the most commonly involved site and left-sided polyps outnumbered right-sided ones with the sigmoid colon being the most commonly involved site. Screening programs including endoscopy, especially the colon for detecting polyps and particularly the colorectal region can be helpful to reduce morbidity and mortality of patients.

Exploring the association between BMI and mortality in Australian women and men with and without diabetes: the AusDiab study.

AIMS/HYPOTHESIS: There is conflicting evidence about the obesity paradox-the counterintuitive survival advantage of obesity among certain subpopulations of individuals with chronic conditions. It is believed that results supporting the obesity paradox are due to methodological flaws, such as collider bias. The aim of this study was to examine the association between obesity and mortality in Australian men and women. In addition, we explored whether obesity would appear to be protective if the analysis was restricted to a subpopulation with disease, and to discuss the potential role of collider bias in producing such a result. METHODS: The examined cohort included 10,575 Australian adults (4844 men and 5731 women) aged 25-91 years who were recruited for the AusDiab baseline survey in 1999 and followed-up through 2014. The main predictor variable was BMI categorised as normal weight (18.5 to <25 kg/m2), overweight (25 to <30 kg/m2) and obese (≥30 kg/m2), and the outcome of interest was all-cause mortality. Hazard ratios were estimated from Cox proportional hazards regression models in the entire cohort and then in subpopulations with and without diabetes. RESULTS: A total of 1477 deaths occurred during 145,384 person-years (median 14.6 years) of follow-up. Mortality was higher in obese than in normal-weight individuals for the full population (HR 1.18; 95% CI 1.05, 1.32). When an interaction between diabetes status and BMI category was added to the model, there was no evidence of an interaction between BMI and diabetes status (p = 0.92). When participants with and without diabetes were analysed separately, there was no evidence of an association between obesity and mortality in those with diabetes (HR 0.91; 95% CI 0.62, 1.33). CONCLUSIONS/INTERPRETATION: In the entire AusDiab cohort, we found a significantly higher mortality among obese participants as compared with their normal-weight counterparts. We found no difference in the obesity-mortality association between individuals with and without diabetes.

IL-23 favours outgrowth of spondyloarthritis-associated pathobionts and suppresses host support for homeostatic microbiota.

OBJECTIVES: Certain gut bacterial families, including Bacteroidaceae, Porphyromonadaceae and Prevotellaceae, are increased in people suffering from spondyloarthropathy (SpA), a disease group associated with IL23R signalling variants. To understand the relationship between host interleukin (IL)-23 signalling and gut bacterial dysbiosis in SpA, we inhibited IL-23 in dysbiotic ZAP-70-mutant SKG mice that develop IL-23-dependent SpA-like arthritis, psoriasis-like skin inflammation and Crohn's-like ileitis in response to microbial beta 1,3-glucan (curdlan). METHODS: We treated SKG mice weekly with anti-IL-23 or isotype mAb for 3 weeks, rested them for 3 weeks, then administered curdlan or saline. We collected faecal samples longitudinally, assessed arthritis, spondylitis, psoriasis and ileitis histologically, and analysed the microbiota community profiles using next-generation sequencing. We used multivariate sparse partial least squares discriminant analysis to identify operational taxonomic unit (OTU) signatures best classifying treatment groups and linear regression to develop a predictive model of disease severity. RESULTS: IL-23p19 inhibition in naïve SKG mice decreased Bacteroidaceae, Porphyromonadaceae and Prevotellaceae. Abundance of Clostridiaceae and Lachnospiraceae families concomitantly increased, and curdlan-mediated SpA development decreased. Abundance of Enterobacteriaceae and Porphyromonadaceae family and reduction in Lachnospiraceae Dorea genus OTUs early in disease course were associated with disease severity in affected tissues. CONCLUSIONS: Dysbiosis in SKG mice reflects human SpA and is IL-23p19 dependent. In genetically susceptible hosts, IL-23p19 favours outgrowth of SpA-associated pathobionts and reduces support for homeostatic-inducing microbiota. The relative abundance of specific pathobionts is associated with disease severity.

An improved clinical model to predict stimulated C-peptide in children with recent-onset type 1 diabetes.

BACKGROUND: Stimulated C-peptide measurement after a mixed meal tolerance test (MMTT) is the accepted gold standard for assessing residual beta-cell function in type 1 diabetes (T1D); however, this approach is impractical outside of clinical trials. OBJECTIVE: To develop an improved estimate of residual beta-cell function in children with T1D using commonly measured clinical variables. SUBJECTS/METHODS: A clinical model to predict 90-minute MMTT stimulated C-peptide in children with recent-onset T1D was developed from the combined AbATE, START, and TIDAL placebo subjects (n = 46) 6 months post-recruitment using multiple linear regression. This model was then validated in a clinical cohort (Hvidoere study group, n = 262). RESULTS: A model of estimated C-peptide at 6 months post-diagnosis, which included age, gender, body mass index (BMI), hemoglobin A1c (HbA1c), and insulin dose predicted 90-minute stimulated C-peptide measurements (adjusted R2 = 0.63, P < 0.0001). The predictive value of insulin dose and HbA1c alone (IDAA1c) for 90-minute stimulated C-peptide was significantly lower (R2 = 0.37, P < 0.0001). The slopes of linear regression lines of the estimated and stimulated 90-minute C-peptide levels obtained at 6 and 12 months post diagnosis in the Hvidoere clinical cohort were R2 = 0.36, P < 0.0001 at 6 months and R2 = 0.37, P < 0.0001 at 12 months. CONCLUSIONS: A clinical model including age, gender, BMI, HbA1c, and insulin dose predicts stimulated C-peptide levels in children with recent-onset T1D. Estimated C-peptide is an improved surrogate to monitor residual beta-cell function outside clinical trial settings.

Treatment delays for patients with new-onset rheumatoid arthritis presenting to an Australian early arthritis clinic.

BACKGROUND: Early treatment ensures optimal outcomes in rheumatoid arthritis (RA) yet there are limited data in Australia quantifying treatment delays in clinical practice. AIMS: To quantify treatment delays in new RA patients and to explore factors influencing delay and resultant patient outcomes. METHODS: Data were obtained for 88 patients presenting with a new diagnosis of RA to an early arthritis clinic (EAC) in Australia between 2008 and 2015. Date and details of symptom onset, initial general practitioner (GP) presentation, GP referral and review at EAC were collected. Patient demographics and clinical features were analysed for outcomes and features predictive of delay. RESULTS: Median overall delay from symptom onset to rheumatology review was 26.4 weeks. Patient delay (8.7 weeks) was the longest delay and predicted overall delay. Delays in GP referral and time to EAC review were 4 and 8.4 weeks respectively. Increased overall delay was predicted by lower fatigue and disease activity scores (DAS28) and increased tender joint counts (TJC). Patient delay was increased by socioeconomic disadvantage. Increased GP delay was associated with lower DAS28 and higher TJC and ESR. Patients seen within 16 weeks had greater improvement in DAS28 and probability of remission at 6 months. CONCLUSIONS: In this Australian EAC setting, patient delay was the greatest contributor to RA treatment delay. Delays in treatment were associated with lower disease severity and socioeconomic disadvantage. Remission was more likely after prompt initiation of treatment.

RAZA: A Rapid 3D z-crossings algorithm to segment electron tomograms and extract organelles and macromolecules.

Resolving the 3D architecture of cells to atomic resolution is one of the most ambitious challenges of cellular and structural biology. Central to this process is the ability to automate tomogram segmentation to identify sub-cellular components, facilitate molecular docking and annotate detected objects with associated metadata. Here we demonstrate that RAZA (Rapid 3D z-crossings algorithm) provides a robust, accurate, intuitive, fast, and generally applicable segmentation algorithm capable of detecting organelles, membranes, macromolecular assemblies and extrinsic membrane protein domains. RAZA defines each continuous contour within a tomogram as a discrete object and extracts a set of 3D structural fingerprints (major, middle and minor axes, surface area and volume), enabling selective, semi-automated segmentation and object extraction. RAZA takes advantage of the fact that the underlying algorithm is a true 3D edge detector, allowing the axes of a detected object to be defined, independent of its random orientation within a cellular tomogram. The selectivity of object segmentation and extraction can be controlled by specifying a user-defined detection tolerance threshold for each fingerprint parameter, within which segmented objects must fall and/or by altering the number of search parameters, to define morphologically similar structures. We demonstrate the capability of RAZA to selectively extract subgroups of organelles (mitochondria) and macromolecular assemblies (ribosomes) from cellular tomograms. Furthermore, the ability of RAZA to define objects and their contours, provides a basis for molecular docking and rapid tomogram annotation.

Predicting the dynamics of protein abundance.

Protein synthesis is finely regulated across all organisms, from bacteria to humans, and its integrity underpins many important processes. Emerging evidence suggests that the dynamic range of protein abundance is greater than that observed at the transcript level. Technological breakthroughs now mean that sequencing-based measurement of mRNA levels is routine, but protocols for measuring protein abundance remain both complex and expensive. This paper introduces a Bayesian network that integrates transcriptomic and proteomic data to predict protein abundance and to model the effects of its determinants. We aim to use this model to follow a molecular response over time, from condition-specific data, in order to understand adaptation during processes such as the cell cycle. With microarray data now available for many conditions, the general utility of a protein abundance predictor is broad. Whereas most quantitative proteomics studies have focused on higher organisms, we developed a predictive model of protein abundance for both Saccharomyces cerevisiae and Schizosaccharomyces pombe to explore the latitude at the protein level. Our predictor primarily relies on mRNA level, mRNA-protein interaction, mRNA folding energy and half-life, and tRNA adaptation. The combination of key features, allowing for the low certainty and uneven coverage of experimental observations, gives comparatively minor but robust prediction accuracy. The model substantially improved the analysis of protein regulation during the cell cycle: predicted protein abundance identified twice as many cell-cycle-associated proteins as experimental mRNA levels. Predicted protein abundance was more dynamic than observed mRNA expression, agreeing with experimental protein abundance from a human cell line. We illustrate how the same model can be used to predict the folding energy of mRNA when protein abundance is available, lending credence to the emerging view that mRNA folding affects translation efficiency. The software and data used in this research are available at http://bioinf.scmb.uq.edu.au/proteinabundance/.

DLocalMotif: a discriminative approach for discovering local motifs in protein sequences.

MOTIVATION: Local motifs are patterns of DNA or protein sequences that occur within a sequence interval relative to a biologically defined anchor or landmark. Current protein motif discovery methods do not adequately consider such constraints to identify biologically significant motifs that are only weakly over-represented but spatially confined. Using negatives, i.e. sequences known to not contain a local motif, can further increase the specificity of their discovery. RESULTS: This article introduces the method DLocalMotif that makes use of positional information and negative data for local motif discovery in protein sequences. DLocalMotif combines three scoring functions, measuring degrees of motif over-representation, entropy and spatial confinement, specifically designed to discriminatively exploit the availability of negative data. The method is shown to outperform current methods that use only a subset of these motif characteristics. We apply the method to several biological datasets. The analysis of peroxisomal targeting signals uncovers several novel motifs that occur immediately upstream of the dominant peroxisomal targeting signal-1 signal. The analysis of proline-tyrosine nuclear localization signals uncovers multiple novel motifs that overlap with C2H2 zinc finger domains. We also evaluate the method on classical nuclear localization signals and endoplasmic reticulum retention signals and find that DLocalMotif successfully recovers biologically relevant sequence properties. AVAILABILITY: http://bioinf.scmb.uq.edu.au/dlocalmotif/

The in situ transcriptomic landscape of breast tumour-associated and normal adjacent endothelial cells.

BACKGROUND AND AIMS: Triple Negative Breast Cancer (TNBC) is associated with increased angiogenesis, which is known to aid tumour growth and metastasis. Anti-angiogenic therapies that have been developed to target this feature have mostly generated disappointing clinical results. Further research into targeted approaches is limited by a lack of understanding of the in situ molecular profile of tumour-associated vasculature. In this study, we aimed to understand the differences in the molecular profiles of tumour endothelial cells vs normal-adjacent endothelial cells in TNBC tissues. METHOD: We have applied unbiased whole transcriptome spatial profiling of in situ gene expressions of endothelial cells localized in full-face patient TNBC tissues (n = 4) and normal-adjacent regions of the same patient breast tissues. RESULTS: Our comparative analysis revealed that 2412 genes were differentially expressed (padj < 0.05) between the tumour endothelial cells and normal-adjacent endothelial cells. Pathway enrichment showed the enrichment of gene sets related to cell-cell, cell-ECM adhesion, chromatin organization and remodeling, and protein-DNA complex subunit organization. CONCLUSION: Overall, the results revealed unique molecular profiles and signalling pathways of tumour-associated vasculature, which is a critical step towards larger cohort studies investigating potential targets for TNBC prognosis and anti-angiogenic treatments.

TGF-ß signalling limits effector function capacity of NK cell anti-tumour immunity in human bladder cancer.

BACKGROUND: Natural killer (NK) cells are important innate immunity players and have unique abilities to recognize and eliminate cancer cells, particularly in settings of antibody-opsonization and antibody-dependant cellular cytotoxicity (ADCC). However, NK cell-based responses in bladder cancers to therapeutic antibodies are typically immunosuppressed, and these immunosuppressive mechanisms are largely unknown. METHODS: Single cell RNA sequencing (scRNA-seq) and high-dimensional flow cytometry were used to investigate the phenotype of tumour-infiltrating NK cells in patients with bladder cancer. Further, in vitro, and in vivo models of this disease were used to validate these findings. FINDINGS: NK cells within bladder tumours displayed reduced expression of FcγRIIIa/CD16, the critical Fc receptor involved in ADCC-mediated cytotoxicity, on both transcriptional and protein levels. Transcriptional signatures of transforming growth factor (TGF)-ß-signalling, a pleiotropic cytokine known for its immunosuppressive and tissue residency-inducing effects, were upregulated in tumour-infiltrating NK cells. TGF-ß mediated CD16 downregulation on NK cells, was further validated in vitro, which was accompanied by a transition into a tissue residency phenotype. This CD16 downregulation was also abrogated by TGF-ßR signalling inhibition, which could also restore the ADCC ability of NK cells subject to TGF-ß effects. In a humanized mouse model of bladder cancer, mice treated with a TGF-ß inhibitor exhibited increased ADCC activity compared to mice treated only with antibodies. INTERPRETATION: This study highlights how TGF-ß-rich bladder cancers inhibit NK cell-mediated ADCC by downregulating CD16. TGF-ß inhibition represents new avenues to reverse immunosuppression and enhance the tumoricidal capacity of NK cells in bladder cancer. FUNDING: The Guimaraes Laboratory is funded by a US Department of Defense-Breast Cancer Research Program-Breakthrough Award Level 1 (#BC200025), a grant (#2019485) awarded through the Medical Research Future Fund (MRFF, with the support of the Queensland Children's Hospital Foundation, Microba Life Sciences, Richie's Rainbow Foundation, Translational Research Institute (TRI) and UQ), and a grant (#RSS_2023_085) funded by a Metro South Health Research Support Scheme. J.K.M.W. is funded by a UQ Research Training Program PhD Scholarship and N.O. is funded by a NHMRC Postgraduate Scholarship (#2021932).

Identification of MicroRNAs in the West Nile Virus Vector Culex tarsalis (Diptera: Culicidae).

MicroRNAs (miRNAs) are a group of small noncoding RNAs that regulate gene expression during important biological processes including development and pathogen defense in most living organisms. Presently, no miRNAs have been identified in the mosquito Culex tarsalis (Diptera: Culicidae), one of the most important vectors of West Nile virus (WNV) in North America. We used small RNA sequencing data and in vitro and in vivo experiments to identify and validate a repertoire of miRNAs in Cx. tarsalis mosquitoes. Using bioinformatic approaches we analyzed small RNA sequences from the Cx. tarsalis CT embryonic cell line to discover orthologs for 86 miRNAs. Consistent with other mosquitoes such as Aedes albopictus and Culex quinquefasciatus, miR-184 was found to be the most abundant miRNA in Cx. tarsalis. We also identified 20 novel miRNAs from the recently sequenced Cx. tarsalis genome, for a total of 106 miRNAs identified in this study. The presence of selected miRNAs was biologically validated in both the CT cell line and in adult Cx. tarsalis mosquitoes using RT-qPCR and sequencing. These results will open new avenues of research into the role of miRNAs in Cx. tarsalis biology, including development, metabolism, immunity, and pathogen infection.

HPV status represents dominant trait driving delineation of survival-associated gene co-expression networks in head and neck cancer.

Integration of high-dimensional tumor gene expression data with clinicopathological data can increase our understanding of disease diversity, enable retrospective patient stratification, and identify new potential biomarkers and therapeutic targets. Using a systems biology approach, we provide a holistic overview of gene co-expression networks in head and neck squamous cell carcinomas (HNSCC). Weighted gene co-expression network analysis of HNSCC RNA sequencing data from 519 patients from The Cancer Genome Atlas (TCGA) was used to determine correlates of 5-year survival, using regression tree-based optimal threshold calculations. Survival-associated gene sets were transformed to gene set scores that were assessed for correlation with clinicopathological data. We identified 8 gene co-expression modules for HNSCC tumors, each of which contained co-expressed genes associated significantly with 5-year survival. Survival-associated co-expression gene signatures correlated dominantly with tumor HPV and p16 status. Network analysis identified that survival was associated with signaling networks of infection, immunity, epithelial-mesenchymal transition (EMT), hypoxia, glycolysis, focal adhesion, extracellular matrix, MYC signaling, autophagy and transcriptional regulation. EMT-associated gene signatures were expressed dominantly in fibroblasts, and cancer-associated fibroblasts were inversely correlated with immune activity. Interestingly, a high Immune Suppression Score based on expression of 21 genes associated with immune inhibition and including immune checkpoints, cytokines and regulatory T cell factors, was also associated with increased survival probability, and was significantly higher in HPV+ HNSCC. Networks associated with HNSCC survival were further associated with survival in cervical cancer, melanoma and lung cancer. This study defines 5129 genes associated with HNSCC survival, organized into co-expressed networks, their correlation with clinicopathological data, and with gene expression data from other malignant diseases, and provides a source for the discovery of biomarkers and novel therapies for HNSCC.

Barriers and facilitators to COVID-19 vaccine uptake among Australian health professional students during the pandemic: a nationwide study.

Using a cross-sectional online survey we investigated knowledge, attitudes, and risk perception about COVID-19 vaccination and identified factors influencing vaccine uptake among Australian health professional students from October 2021 to January 2022. We analysed data from 1114 health professional students from 17 Australian universities. Most participants were enrolled in nursing programs (n = 958, 86.8%), and 91.6% (n = 858) of the participants received COVID-19 vaccination. Approximately 27% believed COVID-19 was no more serious than seasonal influenza and that they had a low risk of acquiring COVID-19. Nearly 20% disagreed that COVID-19 vaccines in Australia were safe and perceived they were at higher-risk of acquiring COVID infection than the general population. Higher-risk perception viewing vaccination as their professional responsibility, and vaccine mandate strongly predicted vaccination behaviour. Participants consider COVID-19 information from health professionals, government websites, and World Health Organization as the most trusted information sources. The findings highlight that healthcare decision-makers and university administrators need to monitor students' hesitancy with vaccination to improve students' promotion of the vaccination to the general population.

Molecular basis for specificity of nuclear import and prediction of nuclear localization.

Although proteins are translated on cytoplasmic ribosomes, many of these proteins play essential roles in the nucleus, mediating key cellular processes including but not limited to DNA replication and repair as well as transcription and RNA processing. Thus, understanding how these critical nuclear proteins are accurately targeted to the nucleus is of paramount importance in biology. Interaction and structural studies in the recent years have jointly revealed some general rules on the specificity determinants of the recognition of nuclear targeting signals by their specific receptors, at least for two nuclear import pathways: (i) the classical pathway, which involves the classical nuclear localization sequences (cNLSs) and the receptors importin-α/karyopherin-α and importin-ß/karyopherin-ß1; and (ii) the karyopherin-ß2 pathway, which employs the proline-tyrosine (PY)-NLSs and the receptor transportin-1/karyopherin-ß2. The understanding of specificity rules allows the prediction of protein nuclear localization. We review the current understanding of the molecular determinants of the specificity of nuclear import, focusing on the importin-α•cargo recognition, as well as the currently available databases and predictive tools relevant to nuclear localization. This article is part of a Special Issue entitled: Regulation of Signaling and Cellular Fate through Modulation of Nuclear Protein Import.

A probabilistic model of nuclear import of proteins.

MOTIVATION: Nucleo-cytoplasmic trafficking of proteins is a core regulatory process that sustains the integrity of the nuclear space of eukaryotic cells via an interplay between numerous factors. Despite progress on experimentally characterizing a number of nuclear localization signals, their presence alone remains an unreliable indicator of actual translocation. RESULTS: This article introduces a probabilistic model that explicitly recognizes a variety of nuclear localization signals, and integrates relevant amino acid sequence and interaction data for any candidate nuclear protein. In particular, we develop and incorporate scoring functions based on distinct classes of classical nuclear localization signals. Our empirical results show that the model accurately predicts whether a protein is imported into the nucleus, surpassing the classification accuracy of similar predictors when evaluated on the mouse and yeast proteomes (area under the receiver operator characteristic curve of 0.84 and 0.80, respectively). The model also predicts the sequence position of a nuclear localization signal and whether it interacts with importin-α. AVAILABILITY: http://pprowler.itee.uq.edu.au/NucImport