ABSTRACT
The cyanobacterium Lyngbya majuscula grows in marine and estuarine environments across the world and produces many biologically active compounds. Direct contact with L majuscula and its dermatoxins can cause seaweed dermatitis, which manifests as a papulovesicular eruption. As oceans warm, L majuscula will bloom more frequently; therefore, public awareness of L majuscula and seaweed dermatitis in oceanside communities can help promote precautions that can reduce the risk for exposure. This article describes the irritants that lead to dermatitis, clinical presentation, and prevention and management of seaweed dermatitis.
Subject(s)
Seaweed , Humans , CyanobacteriaABSTRACT
The progression of primary tumors to metastases remains a significant roadblock to the treatment of most cancers. Emerging evidence has identified genes that specifically affect metastasis and are potential therapeutic targets for managing tumor progression. However, these genes can have dual tumor promoter and suppressor functions that are contextual in manifestation, and that complicate their development as targeted therapies. CD44 and RHAMM/HMMR are examples of multifunctional proteins that can either promote or suppress metastases, as demonstrated in experimental models. These two proteins can be viewed as microenvironmental sensors and this minireview addresses the known mechanistic underpinnings that may determine their metastasis suppressor versus promoter functions. Leveraging this mechanistic knowledge for CD44, RHAMM, and other multifunctional proteins is predicted to improve the precision of therapeutic targeting to achieve more effective management of metastasis.
Subject(s)
Extracellular Matrix Proteins , Hyaluronan Receptors , Neoplasm Metastasis , Neoplasms , Tumor Microenvironment , Hyaluronan Receptors/metabolism , Hyaluronan Receptors/genetics , Humans , Neoplasm Metastasis/genetics , Neoplasms/genetics , Neoplasms/metabolism , Neoplasms/pathology , Extracellular Matrix Proteins/metabolism , Extracellular Matrix Proteins/genetics , Animals , Gene Expression Regulation, NeoplasticABSTRACT
Street-based sex workers experience considerable homelessness, drug use and police enforcement, making them vulnerable to violence from clients and other perpetrators. We used a deterministic compartmental model of street-based sex workers in London to estimate whether displacement by police and unstable housing/homelessness increases client violence. The model was parameterized and calibrated using data from a cohort study of sex workers, to the baseline percentage homeless (64%), experiencing recent client violence (72%), or recent displacement (78%), and the odds ratios of experiencing violence if homeless (1.97, 95% confidence interval 0.88-4.43) or displaced (4.79, 1.99-12.11), or of experiencing displacement if homeless (3.60, 1.59-8.17). Ending homelessness and police displacement reduces violence by 67% (95% credible interval 53-81%). The effects are non-linear; halving the rate of policing or becoming homeless reduces violence by 5.7% (3.5-10.3%) or 6.7% (3.7-10.2%), respectively. Modelled interventions have small impact with violence reducing by: 5.1% (2.1-11.4%) if the rate of becoming housed increases from 1.4 to 3.2 per person-year (Housing First initiative); 3.9% (2.4-6.9%) if the rate of policing reduces by 39% (level if recent increases had not occurred); and 10.2% (5.9-19.6%) in combination. Violence reduces by 26.5% (22.6-28.2%) if half of housed sex workers transition to indoor sex work. If homelessness decreased and policing increased as occurred during the COVID-19 pandemic in 2020, the impact on violence is negligible, decreasing by 0.7% (8.7% decrease-4.1% increase). Increasing housing and reducing policing among street-based sex workers could substantially reduce violence, but large changes are needed.
Subject(s)
Ill-Housed Persons , Sex Workers , Humans , Female , Police , Cohort Studies , London/epidemiology , Pandemics , ViolenceSubject(s)
Maternal Health Services , Quality Improvement , Child , Humans , Infant, Newborn , Female , Pregnancy , NigeriaABSTRACT
Bidirectional communication between the mitochondria and the nucleus is required for several physiological processes, and the nuclear epigenome is a key mediator of this relationship. ncRNAs are an emerging area of discussion for their roles in cellular function and regulation. In this review, we highlight the role of mitochondrial-encoded ncRNAs as mediators of communication between the mitochondria and the nuclear genome. We focus primarily on retrograde signaling, a process in which the mitochondrion relays ncRNAs to translate environmental stress signals to changes in nuclear gene expression, with implications on stress responses that may include disease(s). Other biological roles of mitochondrial-encoded ncRNAs, such as mitochondrial import of proteins and regulation of cell signaling, will also be discussed.
Communication between the nucleus (the cell control center) and the mitochondria (the energy-producing factories of the cell) is important for keeping cells working properly. Though communication goes both ways, signals sent from the mitochondria to the nucleus have become a big topic of discussion because they have been found to affect disease. ncRNAs are another topic that has been gaining traction. These are RNA transcripts that, instead of coding for proteins, have other roles in controlling our cells. Here we discuss ncRNAs that come from the mitochondria, called mt-ncRNAs. By sending mt-ncRNAs to the nucleus, mitochondria can send messages to the nucleus to help cells adapt to stress or changes in the environment. These mt-ncRNAs demonstrate the importance of mitochondria in controlling our cells. By studying this process, we gain information that helps in treating diseases.
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Cell Nucleus , Mitochondria , Humans , Cell Nucleus/genetics , Mitochondria/genetics , Mitochondria/metabolism , RNA, Untranslated/genetics , RNA, Untranslated/metabolism , Signal TransductionABSTRACT
OBJECTIVES: To assess the prevalence of non-communicable diseases (NCDs) and risk factors associated with pre-eclampsia and eclampsia (PE/E) in women of reproductive age (WRA) in Nigeria. DESIGN: A cross-sectional survey was administered to the entire study population. In the point-of-care testing, physical and biochemical measurements were taken in a subset of the participants. SETTING: The study was conducted in the Ikorodu and Alimosho local government areas (LGAs) in Lagos and the Abuja Municipal Area Council and Bwari LGAs in the Federal Capital Territory. PARTICIPANTS: Systematic random sampling was used to randomly select and recruit 639 WRA (aged 18-49 years) between May 2019 and June 2019. OUTCOME MEASURES: Prevalence of select NCDs (hypertension or raised blood pressure, diabetes or raised blood sugar levels, anaemia, truncal obesity and overweight/obesity) and risk factors associated with PE/E (physical activity, fruit and vegetable consumption, alcohol consumption and smoking). RESULTS: The prevalence of raised blood pressure measured among the WRA was 36.0% (95% CI 31.3% to 40.9%). Approximately 10% (95% CI 7.2% to 13.4%) of participants had raised blood sugar levels. About 19.0% (95% CI 15.3% to 23.2%) of the women had moderate or severe anaemia. Excluding WRA who were pregnant, 51.9% (95% CI 45.7% to 58.0%) of the women were either overweight or obese based on their body mass index. Approximately 58.8% (95% CI 53.8% to 63.6%) of WRA surveyed reported three to five risk factors for developing NCDs and PE/E in future pregnancies. CONCLUSIONS: The study identified a high prevalence of NCDs and associated PE/E risk factors in surveyed women, signifying the importance of early detection and intervention for modifiable NCD and associated PE/E risk factors in WRA. Further research is necessary to assess the national prevalence of NCDs.
Subject(s)
Anemia , Eclampsia , Hypertension , Noncommunicable Diseases , Pre-Eclampsia , Pregnancy , Humans , Female , Cross-Sectional Studies , Overweight/epidemiology , Noncommunicable Diseases/epidemiology , Pre-Eclampsia/epidemiology , Blood Glucose , Prevalence , Nigeria/epidemiology , Local Government , Risk Factors , Obesity/epidemiology , Hypertension/epidemiologyABSTRACT
This study provides comprehensive quantitative evidence suggesting that adaptations to extreme temperatures and pH imprint a discernible environmental component in the genomic signature of microbial extremophiles. Both supervised and unsupervised machine learning algorithms were used to analyze genomic signatures, each computed as the k-mer frequency vector of a 500 kbp DNA fragment arbitrarily selected to represent a genome. Computational experiments classified/clustered genomic signatures extracted from a curated dataset of [Formula: see text] extremophile (temperature, pH) bacteria and archaea genomes, at multiple scales of analysis, [Formula: see text]. The supervised learning resulted in high accuracies for taxonomic classifications at [Formula: see text], and medium to medium-high accuracies for environment category classifications of the same datasets at [Formula: see text]. For [Formula: see text], our findings were largely consistent with amino acid compositional biases and codon usage patterns in coding regions, previously attributed to extreme environment adaptations. The unsupervised learning of unlabelled sequences identified several exemplars of hyperthermophilic organisms with large similarities in their genomic signatures, in spite of belonging to different domains in the Tree of Life.
Subject(s)
Extremophiles , Extremophiles/genetics , Genomics/methods , Bacteria/genetics , Archaea/genetics , Genome, Archaeal/geneticsABSTRACT
BACKGROUND: Haemodialysis requires a permanent vascular access and relies on cannulation with two large bore needles. Point Of Care Ultrasound (POCUS) is a tool that may assist nursing staff with visualising cannula placement and prevent miscannulation. This can be particularly useful in regional hospitals with limited access to vascular access specialists. AIMS: To examine the impact of POCUS provision and education for nursing staff on confidence in cannulation and to understand the patient experience at three regional hospital haemodialysis units in South Australia. METHODS: A POCUS machine and dedicated nursing education were provided at each of the three sites. A pre-test post-test model was used to assess the individual nurses perceived competency before and after the delivery of a series of online ultrasound education modules and face to face training. Patient reported outcome measures (PROMs) were collected to understand the use of POCUS from the client perspective. RESULTS: There was a shift towards 'agree' or 'strongly agree' for all nursing surveys in regard to perceived competency (n = 15). This was statistically significant (p ⩽ 0.05) for all questions other than question 1 'I am confident in my ability to physically assess vascular access' (p = 0.06). The patients that completed the PROMs (n = 17) overall supported the ease and use of POCUS for haemodialysis cannulation and felt that it contributed to the nursing staff competency in cannulation. CONCLUSION: POCUS has the potential to be a valuable tool in regional haemodialysis units to support vascular access cannulation and potentially avoid metropolitan transfer due to cannulation difficulties. The non-significant change post intervention for question 1 likely reflects the haemodialysis nurses inherent pre-existing capacity to assess vascular access without the use of POCUS using the standard process of visual inspection, the use of a stethoscope and palpation ('look, listen and feel').
ABSTRACT
SUMMARY: We present an interactive Deep Learning-based software tool for Unsupervised Clustering of DNA Sequences (iDeLUCS), that detects genomic signatures and uses them to cluster DNA sequences, without the need for sequence alignment or taxonomic identifiers. iDeLUCS is scalable and user-friendly: its graphical user interface, with support for hardware acceleration, allows the practitioner to fine-tune the different hyper-parameters involved in the training process without requiring extensive knowledge of deep learning. The performance of iDeLUCS was evaluated on a diverse set of datasets: several real genomic datasets from organisms in kingdoms Animalia, Protista, Fungi, Bacteria, and Archaea, three datasets of viral genomes, a dataset of simulated metagenomic reads from microbial genomes, and multiple datasets of synthetic DNA sequences. The performance of iDeLUCS was compared to that of two classical clustering algorithms (k-means++ and GMM) and two clustering algorithms specialized in DNA sequences (MeShClust v3.0 and DeLUCS), using both intrinsic cluster evaluation metrics and external evaluation metrics. In terms of unsupervised clustering accuracy, iDeLUCS outperforms the two classical algorithms by an average of â¼20%, and the two specialized algorithms by an average of â¼12%, on the datasets of real DNA sequences analyzed. Overall, our results indicate that iDeLUCS is a robust clustering method suitable for the clustering of large and diverse datasets of unlabeled DNA sequences. AVAILABILITY AND IMPLEMENTATION: iDeLUCS is available at https://github.com/Kari-Genomics-Lab/iDeLUCS under the terms of the MIT licence.
Subject(s)
Deep Learning , Base Sequence , Algorithms , Archaea , Cluster AnalysisABSTRACT
BACKGROUND: RHAMM is a multifunctional protein that is upregulated in breast tumors, and the presence of strongly RHAMM+ve cancer cell subsets associates with elevated risk of peripheral metastasis. Experimentally, RHAMM impacts cell cycle progression and cell migration. However, the RHAMM functions that contribute to breast cancer metastasis are poorly understood. METHODS: We interrogated the metastatic functions of RHAMM using a loss-of-function approach by crossing the MMTV-PyMT mouse model of breast cancer susceptibility with Rhamm-/- mice. In vitro analyses of known RHAMM functions were performed using primary tumor cell cultures and MMTV-PyMT cell lines. Somatic mutations were identified using a mouse genotyping array. RNA-seq was performed to identify transcriptome changes resulting from Rhamm-loss, and SiRNA and CRISPR/Cas9 gene editing was used to establish cause and effect of survival mechanisms in vitro. RESULTS: Rhamm-loss does not alter initiation or growth of MMTV-PyMT-induced primary tumors but unexpectedly increases lung metastasis. Increased metastatic propensity with Rhamm-loss is not associated with obvious alterations in proliferation, epithelial plasticity, migration, invasion or genomic stability. SNV analyses identify positive selection of Rhamm-/- primary tumor clones that are enriched in lung metastases. Rhamm-/- tumor clones are characterized by an increased ability to survive with ROS-mediated DNA damage, which associates with blunted expression of interferon pathway and target genes, particularly those implicated in DNA damage-resistance. Mechanistic analyses show that ablating RHAMM expression in breast tumor cells by siRNA knockdown or CRISPR-Cas9 gene editing blunts interferon signaling activation by STING agonists and reduces STING agonist-induced apoptosis. The metastasis-specific effect of RHAMM expression-loss is linked to microenvironmental factors unique to tumor-bearing lung tissue, notably high ROS and TGFB levels. These factors promote STING-induced apoptosis of RHAMM+ve tumor cells to a significantly greater extent than RHAMM-ve comparators. As predicted by these results, colony size of Wildtype lung metastases is inversely related to RHAMM expression. CONCLUSION: RHAMM expression-loss blunts STING-IFN signaling, which offers growth advantages under specific microenvironmental conditions of lung tissue. These results provide mechanistic insight into factors controlling clonal survival/expansion of metastatic colonies and has translational potential for RHAMM expression as a marker of sensitivity to interferon therapy.
Subject(s)
Lung Neoplasms , Mammary Neoplasms, Animal , Animals , Reactive Oxygen Species , Mammary Neoplasms, Animal/genetics , Lung Neoplasms/pathology , RNA, Small Interfering , DNA DamageABSTRACT
BACKGROUND: Nigeria has one of the highest maternal mortality ratios (MMR) globally with an MMR of 512 (per 100,000 live births) and the proportion of maternal deaths due to non-communicable diseases (NCDs) is increasing. While evidence shows that many of these deaths are preventable, limited attention is being paid to the unique vulnerabilities and experiences of women of reproductive age (WRA) with NCDs and their risk factors, as well as the barriers to the screening, diagnosis, and management of these diseases in Nigeria. METHODS: This study explored the lives of WRA in Lagos and Federal Capital Territory in Nigeria from May to June 2019 using a community-based participatory research (CBPR) methodology called Photovoice which is aligned with CBPR as it includes procedures such as the identification of important community issues, discussion of photo assignments and data analysis. Twenty-four women of reproductive age were provided with digital cameras and trained on how to capture photos that conveyed their current health, healthcare utilization and engagement, and experience journeys. Individual interviews with the women were held for an in-depth exploration of the photographs. The data was then analysed thematically. RESULTS: Six distinct themes were identified across the barriers highlighted by the women: food and nutrition, home and family, neighborhood-built environment, economic instability, religion and spirituality and low prioritization of self-care. These themes captured the challenge of reduced agency, limited contribution and participation, and a complex relationship between visible and invisible illness. CONCLUSION: The perspectives of WRA in Nigeria obtained through this qualitative research provided a strong substratum for understanding the environmental barriers that predispose WRA to NCDs in Nigeria. The results of the study are useful for the improvement of woman-centred services of prevention, diagnosis, and management of NCD risk factors across the maternal and reproductive health care continuum in Nigeria.
Subject(s)
Noncommunicable Diseases , Female , Humans , Delivery of Health Care , Nigeria , Noncommunicable Diseases/therapy , Patient Acceptance of Health Care , Reproduction , Community-Based Participatory ResearchABSTRACT
There has been increasing prevalence in the community of chronic kidney disease and an increased demand for nephrology trained nursing staff.We explored how nephrology trained nurses are impacted by daily caseload pressure, organisational support and workplace education.A co-designed 57-item questionnaire developed by the research team and clinical nephrology nurses hosted on Qualtrics™ was distributed to nephrology nurses in Australia and New Zealand.The 370 respondents described a strong professional identity as a nephrology nurse. 70% described pressure to work overtime and only 2% were adequately staffed. 40% felt at times that their patients clinical care was 'unsafe' and one-third described the erosion of work-based educational opportunities. However, team collegiality was high, a strength of the nursing profession.The nephrology nursing workforce will face important challenges over the next decade and there must be an organisational response to prevent continued staff shortages.
Subject(s)
Nephrology Nursing , Nephrology , Nursing Staff , Humans , Nephrology/education , New Zealand , Organizational Culture , Australia , WorkforceABSTRACT
Astroviruses are a family of genetically diverse viruses associated with disease in humans and birds with significant health effects and economic burdens. Astrovirus taxonomic classification includes two genera, Avastrovirus and Mamastrovirus. However, with next-generation sequencing, broader interspecies transmission has been observed necessitating a reexamination of the current host-based taxonomic classification approach. In this study, a novel taxonomic classification method is presented for emergent and as yet unclassified astroviruses, based on whole genome sequence k-mer composition in addition to host information. An optional component responsible for identifying recombinant sequences was added to the method's pipeline, to counteract the impact of genetic recombination on viral classification. The proposed three-pronged classification method consists of a supervised machine learning method, an unsupervised machine learning method, and the consideration of host species. Using this three-pronged approach, we propose genus labels for 191 as yet unclassified astrovirus genomes. Genus labels are also suggested for an additional eight as yet unclassified astrovirus genomes for which incompatibility was observed with the host species, suggesting cross-species infection. Lastly, our machine learning-based approach augmented by a principal component analysis (PCA) analysis provides evidence supporting the hypothesis of the existence of human astrovirus (HAstV) subgenus of the genus Mamastrovirus, and a goose astrovirus (GoAstV) subgenus of the genus Avastrovirus. Overall, this multipronged machine learning approach provides a fast, reliable, and scalable prediction method of taxonomic labels, able to keep pace with emerging viruses and the exponential increase in the output of modern genome sequencing technologies.
ABSTRACT
There is extensive qualitative evidence of violence and enforcement impacting sex workers who are ethnically or racially minoritized, and gender or sexual minority sex workers, but there is little quantitative evidence. Baseline and follow-up data were collected among 288 sex workers of diverse genders (cis/transgender women and men and non-binary people) in London (2018-2019). Interviewer-administered and self-completed questionnaires included reports of rape, emotional violence, and (un)lawful police encounters. We used generalized estimating equation models (Stata vs 16.1) to measure associations between (i) ethnic/racial identity (Black, Asian, mixed or multiple vs White) and recent (6 months) or past police enforcement and (ii) ethnic/racial and sexual identity (lesbian, gay or bisexual (LGB) vs. heterosexual) with recent rape and emotional violence (there was insufficient data to examine the association with transgender/non-binary identities). Ethnically/racially minoritized sex workers (26.4%) reported more police encounters partly due to increased representation in street settings (51.4% vs 30.7% off-street, p = 0.002). After accounting for street setting, ethnically/racially minoritized sex workers had higher odds of recent arrest (adjusted odds ratio 2.8, 95% CI 1.3-5.8), past imprisonment (aOR 2.3, 95% CI 1.1-5.0), police extortion (aOR 3.3, 95% CI 1.4-7.8), and rape (aOR 3.6, 95% CI 1.1-11.5). LGB-identifying sex workers (55.4%) were more vulnerable to rape (aOR 2.4, 95% CI 1.1-5.2) and emotional violence. Sex workers identifying as ethnically/racially minoritized (aOR 2.1, 95% CI 1.0-4.5), LGB (aOR 2.0, 95% CI 1.0-4.0), or who use drugs (aOR 2.0, 95% CI 1.1-3.8) were more likely to have experienced emotional violence than white-identifying, heterosexual or those who did not use drugs. Experience of any recent police enforcement was associated with increased odds of rape (aOR 3.6, 95% CI 1.3-8.4) and emotional violence (aOR 4.9, 95% CI 1.8-13.0). Findings show how police enforcement disproportionately targets ethnically/racially minoritized sex workers and contributes to increased risk of rape and emotional violence, which is elevated among sexual and ethnically/racially minoritized workers.
Subject(s)
Sex Workers , Female , Humans , Male , Cohort Studies , Systemic Racism , Violence , Law EnforcementABSTRACT
INTRODUCTION: Respectful maternity care (RMC) is fundamental to women's and families' experience of care and their decision about where to give birth. Studies from multiple countries describe the mistreatment of women during facility-based childbirth, though only a small number of studies from Guatemala have been published. Less information is available on women's negative and positive experiences of childbirth care and health workers' perceptions and experiences of providing maternity care. METHODS: As part of a program implemented in the Western Highlands of Guatemala to improve quality of reproductive maternal newborn and child health care, a mixed methods assessment was conducted in three hospitals and surrounding areas to understand women's and health workers' experience and perceptions of maternity care. The quantitative component included a survey of 31 maternity health workers and 140 women who had recently given birth in these hospitals. The qualitative component included in-depth interviews (IDIs) and focus group discussions (FGDs) with women and maternity health workers and managers. RESULTS: Women reported a mix of positive and negative experiences of childbirth care related to interpersonal and health system factors. 81% of surveyed women reported that health workers had treated them with respect while 21.4% of women reported verbal abuse. Fifty-five percent and 12% of women, respectively, reported not having access to a private toilet and bath or shower. During IDIs and FGDs, many women described higher rates of verbal abuse directed at women who do not speak Spanish. A regression analysis of survey results indicated that speaking Ixil or K'iche at home was associated with a higher likelihood of women being treated negatively during childbirth in a facility. Health worker survey results corroborated negative aspects of care described by women and also reported mistreatment of health workers by clients and families (70.9%) and colleagues (48.2%). CONCLUSIONS: This study adds to the literature on women's experience of institutional childbirth and factors that influence this experience by triangulating experience and perceptions of both women and health workers. This assessment highlights opportunities to address mistreatment of both women and health workers and to build on positive care attributes to strengthen RMC for all women.
Subject(s)
Maternal Health Services , Attitude of Health Personnel , Child , Female , Guatemala , Health Services Accessibility , Humans , Infant, Newborn , Male , Parturition , Pregnancy , Quality of Health CareABSTRACT
Analyzing the information-rich content of RNA can help uncover genetic events associated with social insect castes or other social polymorphisms. Here, we exploit a series of cDNA libraries previously derived from whole-body tissue of different castes as well as from three behaviourally distinct populations of the Eastern subterranean termite Reticulitermes flavipes. We found that the number (~0.5 M) of single nucleotide variants (SNVs) was roughly equal between nymph, worker and soldier caste libraries, but dN/dS (ratio of nonsynonymous to synonymous substitutions) analysis suggested that some of these variants confer a caste-specific advantage. Specifically, the dN/dS ratio was high (~4.3) for genes expressed in the defensively specialized soldier caste, relative to genes expressed by other castes (~1.7−1.8) and regardless of the North American population (Toronto, Raleigh, Boston) from which the castes were sampled. The populations, meanwhile, did show a large difference in SNV count but not in the manner expected from known demographic and behavioural differences; the highly invasive unicolonial population from Toronto was not the least diverse and did not show any other unique substitution patterns, suggesting any past bottleneck associated with invasion or with current unicoloniality has become obscured at the RNA level. Our study raises two important hypotheses relevant to termite sociobiology. First, the positive selection (dN/dS > 1) inferred for soldier-biased genes is presumably indirect and of the type mediated through kin selection, and second, the behavioural changes that accompany some social insect urban invasions (i.e., 'unicoloniality') may be detached from the loss-of-diversity expected from invasion bottlenecks.
ABSTRACT
SUMMARY: SomaticSiMu is an in silico simulator of single and double base substitutions, and single base insertions and deletions in an input genomic sequence to mimic mutational signatures. SomaticSiMu outputs simulated DNA sequences and mutational catalogues with imposed mutational signatures. The tool is the first mutational signature simulator featuring a graphical user interface, control of mutation rates and built-in visualization tools of the simulated mutations. Simulated datasets are useful as a ground truth to test the accuracy and sensitivity of DNA sequence classification tools and mutational signature extraction tools under different experimental scenarios. The reliability of SomaticSiMu was affirmed by (i) supervised machine learning classification of simulated sequences with different mutation types and burdens, and (ii) mutational signature extraction from simulated mutational catalogues. AVAILABILITY AND IMPLEMENTATION: SomaticSiMu is written in Python 3.8.3. The open-source code, documentation and tutorials are available at https://github.com/HillLab/SomaticSiMu under the terms of the CreativeCommonsAttribution4.0InternationalLicense. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Subject(s)
Genomics , Software , Reproducibility of Results , Mutation , GenomeABSTRACT
We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of primary DNA sequences, and generates "mimic" sequence FCGRs to self-learn data patterns (genomic signatures) through the optimization of multiple neural networks. A majority voting scheme is then used to determine the final cluster assignment for each sequence. The clusters learned by DeLUCS match true taxonomic groups for large and diverse datasets, with accuracies ranging from 77% to 100%: 2,500 complete vertebrate mitochondrial genomes, at taxonomic levels from sub-phylum to genera; 3,200 randomly selected 400 kbp-long bacterial genome segments, into clusters corresponding to bacterial families; three viral genome and gene datasets, averaging 1,300 sequences each, into clusters corresponding to virus subtypes. DeLUCS significantly outperforms two classic clustering methods (K-means++ and Gaussian Mixture Models) for unlabelled data, by as much as 47%. DeLUCS is highly effective, it is able to cluster datasets of unlabelled primary DNA sequences totalling over 1 billion bp of data, and it bypasses common limitations to classification resulting from the lack of sequence homology, variation in sequence length, and the absence or instability of sequence annotations and taxonomic identifiers. Thus, DeLUCS offers fast and accurate DNA sequence clustering for previously intractable datasets.
Subject(s)
Deep LearningABSTRACT
OBJECTIVES: To examine legal and social determinants of violence, anxiety/depression among sex workers. METHODS: A participatory prospective cohort study among women (inclusive of transgender) ≥18 years, selling sex in the last 3 months in London between 2018 and 2019. We used logistic generalised estimating equation models to measure associations between structural factors on recent (6 months) violence from clients or others (local residents, strangers), depression/anxiety (Patient Health Questionnaire-4). RESULTS: 197 sex workers were recruited (96% cisgender-women; 46% street-based; 54% off-street) and 60% completed a follow-up questionnaire. Street-based sex workers experienced greater inequalities compared with off-street in relation to recent violence from clients (73% vs 36%); police (42% vs 7%); intimate partner violence (IPV) (56% vs 18%) and others (67% vs 17%), as well as homelessness (65% vs 7%) and recent law enforcement (87% vs 9%). Prevalence of any STI was 17.5% (17/97). For street-based sex workers, recent arrest was associated with violence from others (adjusted OR (aOR) 2.77; 95% CI 1.11 to 6.94) and displacement by police was associated with client violence (aOR 4.35; 95% CI 1.36 to 13.90). Financial difficulties were also associated with client violence (aOR 4.66; 95% CI 1.64 to 13.24). Disability (aOR 3.85; 95% CI 1.49 to 9.95) and client violence (aOR 2.55; 95% CI 1.10 to 5.91) were associated with anxiety/depression. For off-street sex workers, financial difficulties (aOR 3.66; 95% CI 1.64 to 8.18), unstable residency (aOR 3.19; 95% CI 1.36 to 7.49), IPV (aOR 3.77; 95% CI 1.30 to 11.00) and alcohol/drug use were associated with client violence (aOR 3.16; 95% CI 1.26 to 7.92), while always screening and refusing clients was protective (aOR 0.36; 95% CI 0.15 to 0.87). Disability (aOR 5.83; 95% CI 2.34 to 14.51), unmet mental health needs (aOR 3.08; 95% CI 1.15 to 8.23) and past eviction (aOR 3.99; 95% CI 1.23 to 12.92) were associated with anxiety/depression. CONCLUSIONS: Violence, anxiety/depression are linked to poverty, unstable housing and police enforcement. We need to modify laws to allow sex workers to work safely and increase availability of housing and mental health services.