Direct costs of managing in-ward dengue patients in Sri Lanka: A prospective study

Introduction The cost in managing hospitalised dengue patients varies across countries depending on access to healthcare, management guidelines, and state sponsored subsidies. For health budget planning, locally relevant, accurate costing data from prospective studies, is essential. Objective To characterise the direct costs of managing hospitalised patients with suspected dengue infection in Sri Lanka. Methods Colombo Dengue Study is a prospective single centre cohort study in Sri Lanka recruiting suspected hospitalised dengue fever patients in the first three days of fever and following them up until discharge. The diagnosis of dengue is retrospectively confirmed and the cohort therefore has a group of non-dengue fever patients with a phenotypically similar illness, managed as dengue while in hospital. The direct costs of hospital admission (base and investigation costs, excluding medication) were calculated for all recruited patients and compared between dengue and non-dengue categories as well as across subgroups (demographic, clinical or temporal) within each of these categories. We also explored if excluding dengue upfront, would lead to an overall cost saving in several hypothetical scenarios. Results From October 2017 to February 2020, 431 adult dengue patients and 256 non-dengue fever patients were recruited. The hospitalisation costs were USD 18.02 (SD: 4.42) and USD 17.55 (SD: 4.09) per patient per day for dengue and non-dengue patients respectively (p>0.05). Laboratory investigations (haematological, biochemical and imaging) accounted for more than 50% of the total cost. The costs were largely homogenous in all subgroups within or across dengue and non-dengue categories. Excluding dengue upfront by subsidised viral genomic testing may yield overall cost savings for non-dengue patients. Conclusion As non-dengue patients incur a similar cost per day as the dengue patients, confirming dengue diagnosis using subsidised tests for patients presenting in the first three days of fever may be cost-efficient

Networking the nucleus

The nuclei of differentiating cells exhibit several fundamental principles of self-organization. They are composed of many dynamical units connected physically and functionally to each other—a complex network—and the different parts of the system are mutually adapted and produce a characteristic end state. A unique cell-specific signature emerges over time from complex interactions among constituent elements that delineate coordinate gene expression and chromosome topology. Each element itself consists of many interacting components, all dynamical in nature. Self-organizing systems can be simplified while retaining complex information using approaches that examine the relationship between elements, such as spatial relationships and transcriptional information. These relationships can be represented using well-defined networks. We hypothesize that during the process of differentiation, networks within the cell nucleus rewire according to simple rules, from which a higher level of order emerges. Studying the interaction within and among networks provides a useful framework for investigating the complex organization and dynamic function of the nucleus

Development of a machine learning model for early prediction of plasma leakage in suspected dengue patients

Background At least a third of dengue patients develop plasma leakage with increased risk of life-threat-ening complications. Predicting plasma leakage using laboratory parameters obtained in early infection as means of triaging patients for hospital admission is important for resource-limited settings. Methods A Sri Lankan cohort including 4,768 instances of clinical data from N = 877 patients (60.3% patients with confirmed dengue infection) recorded in the first 96 hours of fever was consid-ered. After excluding incomplete instances, the dataset was randomly split into a development and a test set with 374 (70%) and 172 (30%) patients, respectively. From the development set, five most informative features were selected using the minimum description length (MDL) algorithm. Random forest and light gradient boosting machine (LightGBM) were used to develop a classification model using the development set based on nested cross validation. An ensemble of the learners via average stacking was used as the final model to predict plasma leakage. Results Lymphocyte count, haemoglobin, haematocrit, age, and aspartate aminotransferase were the most informative features to predict plasma leakage. The final model achieved the area under the receiver operating characteristics curve, AUC = 0.80 with positive predictive value, PPV = 76.9%, negative predictive value, NPV = 72.5%, specificity = 87.9%, and sensitivity = 54.8% on the test set. Conclusion The early predictors of plasma leakage identified in this study are similar to those identified in several prior studies that used non-machine learning based methods. However, our observations strengthen the evidence base for these predictors by showing their relevance even when individual data points, missing data and non-linear associations were consid-ered. Testing the model on different populations using these low-cost observations would identify further strengths and limitations of the presented model

Effect of prior Zika and dengue virus exposure on the severity of a subsequent dengue infection in adults

Given the structural similarity between Zika and dengue viruses, prior infection from one virus is hypothesized to modulate the severity of a subsequent infection from the other virus. A previous paediatric cohort study observed that a prior Zika infection may increase the risk of a subsequent symptomatic or severe dengue infection. The Colombo Dengue study is a prospective hospital-based cohort study in Sri Lanka that recruits symptomatic adult dengue patients within the first three days of fever. Anti-Dengue Envelope and anti-Zika NS1 IgG antibodies were tested by ELISA (Euroimmun, Lubeck, Germany) in all recruited patients. Associations between pre-morbid seroprevalence for either or both infections and adverse clinical outcomes of the current dengue infection were explored. A total of 507 dengue infected patients were assessed of whom 342 (68%) and 132 (26%) patients had anti-dengue IgG and anti-Zika IgG respectively. People with combined prior dengue and zika exposure as well as prior dengue exposure alone, were at increased risk of plasma leakage, compensated and uncompensated shock, and severe dengue (p < 0·05), compared to people without prior exposure to either infection. The effect of prior Zika exposure alone could not be established due to the small the number of primary dengue infections with prior Zika exposure

Genomic Surveillance of Recent Dengue Outbreaks in Colombo, Sri Lanka

All four serotypes of the dengue virus (DENV1–4) cause a phenotypically similar illness, but serial infections from different serotypes increase the risk of severe disease. Thus, genomic surveillance of circulating viruses is important to detect serotype switches that precede community outbreaks of disproportionate magnitude. A phylogenetic analysis was conducted on near full length DENV genomes sequenced from serum collected from a prospective cohort study from the Colombo district, Sri Lanka during a 28-month period using Oxford nanopore technology, and the consensus sequences were analyzed using maximum likelihood and Bayesian evolutionary analysis. From 523 patients, 328 DENV sequences were successfully generated (DENV1: 43, DENV2: 219, DENV3:66). Most circulating sequences originated from a common ancestor that was estimated to have existed from around 2010 for DENV2 and around 2015/2016 for DENV1 and DENV3. Four distinct outbreaks coinciding with monsoon rain seasons were identified during the observation period mostly driven by DENV2 cosmopolitan genotype, except for a large outbreak in 2019 contributed by DENV3 genotype I. This serotype switch did not result in a more clinically severe illness. Phylogeographic analyses showed that all outbreaks started within Colombo city and then spread to the rest of the district. In 2019, DENV3 genotype I, previously, rarely reported in Sri Lanka, is likely to have contributed to a disease outbreak. However, this did not result in more severe disease in those infected, probably due to pre-existing DENV3 immunity in the community. Targeted vector control within Colombo city before anticipated seasonal outbreaks may help to limit the geographic spread of outbreaks

Improving signal-to-noise ratio of structured light microscopy based on photon reassignment

In this paper, we report a method for 3D visualization of a biological specimen utilizing a structured light wide-field microscopic imaging system. This method improves on existing structured light imaging modalities by reassigning fluorescence photons generated from off-focal plane excitation, improving in-focus signal strength. Utilizing a maximum likelihood approach, we identify the most likely fluorophore distribution in 3D that will produce the observed image stacks under structured and uniform illumination using an iterative maximization algorithm. Our results show the optical sectioning capability of tissue specimens while mostly preserving image stack photon count, which is usually not achievable with other existing structured light imaging methods

A dynamical model reveals gene co-localizations in nucleus

Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the observed co-localization of genes within a defined subnuclear region. A simple standard Brownian motion model in two and three dimensions shows that preferential co-localization is possible for co-regulated genes without any direct interaction, and suggests the occurrence may be due to a limitation in the number of available transcription factors. Experimental data of chromatin movements demonstrates that fractional rather than standard Brownian motion is more appropriate to model gene mobilizations, and we tested our dynamical model against recent static experimental data, using a sub-diffusion process by which the genes tend to colocalize more easily. Moreover, in order to compare our model with recently obtained experimental data, we studied the association level between genes and factors, and presented data supporting the validation of this dynamic model. As further applications of our model, we applied it to test against more biological observations. We found that increasing transcription factor number, rather than factory number and nucleus size, might be the reason for decreasing gene co-localization. In the scenario of frequency-or amplitude-modulation of transcription factors, our model predicted that frequency-modulation may increase the co-localization between its targeted genes

Environmental contamination of pathogenic and intermediate pathogenic <em>Leptospira</em> spp in two divisional secretariats of Kandy district

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The NCI-60 methylome and its integration into CellMiner

A unique resource for systems pharmacology and genomic studies is the NCI-60 cancer cell line panel, which provides data for the largest publicly available library of compounds with cytotoxic activity (∼21,000 compounds), including 108 FDA-approved and 70 clinical trial drugs as well as genomic data, including whole-exome sequencing, gene and miRNA transcripts, DNA copy number, and protein levels. Here, we provide the first readily usable genome-wide DNA methylation database for the NCI-60, including 485,577 probes from the Infinium HumanMethylation450k BeadChip array, which yielded DNA methylation signatures for 17,559 genes integrated into our open access CellMiner version 2.0 (https://discover.nci.nih.gov/cellminer). Among new insights, transcript versus DNA methylation correlations revealed the epithelial/mesenchymal gene functional category as being influenced most heavily by methylation. DNA methylation and copy number integration with transcript levels yielded an assessment of their relative influence for 15,798 genes, including tumor suppressor, mitochondrial, and mismatch repair genes. Four forms of molecular data were combined, providing rationale for microsatellite instability for 8 of the 9 cell lines in which it occurred. Individual cell line analyses showed global methylome patterns with overall methylation levels ranging from 17% to 84%. A six-gene model, including PARP1, EP300, KDM5C, SMARCB1, and UHRF1 matched this pattern. In addition, promoter methylation of two translationally relevant genes, Schlafen 11 (SLFN11) and methylguanine methyltransferase (MGMT), served as indicators of therapeutic resistance or susceptibility, respectively. Overall, our database provides a resource of pharmacologic data that can reinforce known therapeutic strategies and identify novel drugs and drug targets across multiple cancer type

Seeking legitimacy through CSR: Institutional Pressures and Corporate Responses of Multinationals in Sri Lanka

Arguably, the corporate social responsibility (CSR) practices of multinational enterprises (MNEs) are influenced by a wide range of both internal and external factors. Perhaps most critical among the exogenous forces operating on MNEs are those exerted by state and other key institutional actors in host countries. Crucially, academic research conducted to date offers little data about how MNEs use their CSR activities to strategically manage their relationship with those actors in order to gain legitimisation advantages in host countries. This paper addresses that gap by exploring interactions between external institutional pressures and firm-level CSR activities, which take the form of community initiatives, to examine how MNEs develop their legitimacy-seeking policies and practices. In focusing on a developing country, Sri Lanka, this paper provides valuable insights into how MNEs instrumentally utilise community initiatives in a country where relationship-building with governmental and other powerful non-governmental actors can be vitally important for the long-term viability of the business. Drawing on neo-institutional theory and CSR literature, this paper examines and contributes to the embryonic but emerging debate about the instrumental and political implications of CSR. The evidence presented and discussed here reveals the extent to which, and the reasons why, MNEs engage in complex legitimacy-seeking relationships with Sri Lankan institutions