Challenges of modeling rainfall triggered landslides in a data-sparse region: A case study from the Western Ghats, India

Accurate rainfall estimates are required to forecast the spatio-temporal distribution of rain-triggered landslides. In this study, a comparison between rain gauge and satellite rainfall data for assessing landslide distribution in a data-sparse region, the mountainous district of Idukki, along the Western Ghats of southwestern India, is carried out. Global Precipitation Mission Integrated Multi-satellitE Retrievals for GPM-Late (GPM IMERG-L) rainfall products were compared with rain gauge measurements, and it was found that the satellite rainfall observations were underpredicting the actual rainfall. A conditional merging algorithm was applied to develop a product that combines the accuracy of rain gauges and the spatial variability of satellite precipitation data. Correlation Coefficient (CC) and Root Mean Squared Error (RMSE) were used to check the performance of the conditional merging process. An example from a station with the least favorable statistics shows the CC increasing from 0.589 to 0.974 and the RMSE decreasing from 65.22 to 20.01. A case scenario was considered that evaluated the performance of a landslide prediction model by relying solely on a sparse rain gauge network. Rainfall thresholds computed from both the conditionally merged GPM IMERG-L and the rain gauge data were compared and the differences indicated that relying solely on a discrete, sparse rain gauge network would create false predictions. A total of 18.7% of landslide predictions only were identified as true positives, while 60.7% was the overall false-negative rate, and the remaining were false-positives. This pointed towards the need of having a continuous data that is both accurate in measurement and efficient in capturing spatial variability of rainfall

On merging the fields of neural networks and adaptive data structures to yield new pattern recognition methodologies

The aim of this talk is to explain a pioneering exploratory research endeavour that attempts to merge two completely different fields in Computer Science so as to yield very fascinating results. These are the well-established fields of Neural Networks (NNs) and Adaptive Data Structures (ADS) respectively. The field of NNs deals with the training and learning capabilities of a large number of neurons, each possessing minimal computational properties. On the other hand, the field of ADS concerns designing, implementing and analyzing data structures which adaptively change with time so as to optimize some access criteria. In this talk, we shall demonstrate how these fields can be merged, so that the neural elements are themselves linked together using a data structure. This structure can be a singly-linked or doubly-linked list, or even a Binary Search Tree (BST). While the results themselves are quite generic, in particular, we shall, as a prima facie case, present the results in which a Self-Organizing Map (SOM) with an underlying BST structure can be adaptively re-structured using conditional rotations. These rotations on the nodes of the tree are local and are performed in constant time, guaranteeing a decrease in the Weighted Path Length of the entire tree. As a result, the algorithm, referred to as the Tree-based Topology-Oriented SOM with Conditional Rotations (TTO-CONROT), converges in such a manner that the neurons are ultimately placed in the input space so as to represent its stochastic distribution. Besides, the neighborhood properties of the neurons suit the best BST that represents the data

Predicting disease risk areas through co-production of spatial models: the example of Kyasanur Forest Disease in India’s forest landscapes

Zoonotic diseases affect resource-poor tropical communities disproportionately, and are linked to human use and modification of ecosystems. Disentangling the socio-ecological mechanisms by which ecosystem change precipitates impacts of pathogens is critical for predicting disease risk and designing effective intervention strategies. Despite the global “One Health” initiative, predictive models for tropical zoonotic diseases often focus on narrow ranges of risk factors and are rarely scaled to intervention programs and ecosystem use. This study uses a participatory, co-production approach to address this disconnect between science, policy and implementation, by developing more informative disease models for a fatal tick-borne viral haemorrhagic disease, Kyasanur Forest Disease (KFD), that is spreading across degraded forest ecosystems in India. We integrated knowledge across disciplines to identify key risk factors and needs with actors and beneficiaries across the relevant policy sectors, to understand disease patterns and develop decision support tools. Human case locations (2014–2018) and spatial machine learning quantified the relative role of risk factors, including forest cover and loss, host densities and public health access, in driving landscape-scale disease patterns in a long-affected district (Shivamogga, Karnataka State). Models combining forest metrics, livestock densities and elevation accurately predicted spatial patterns in human KFD cases (2014–2018). Consistent with suggestions that KFD is an “ecotonal” disease, landscapes at higher risk for human KFD contained diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high indigenous cattle density, and low coverage of dry deciduous forest. Models predicted new hotspots of outbreaks in 2019, indicating their value for spatial targeting of intervention. Co-production was vital for: gathering outbreak data that reflected locations of exposure in the landscape; better understanding contextual socio-ecological risk factors; and tailoring the spatial grain and outputs to the scale of forest use, and public health interventions. We argue this inter-disciplinary approach to risk prediction is applicable across zoonotic diseases in tropical settings

Small-molecule-mediated OGG1 inhibition attenuates pulmonary inflammation and lung fibrosis in a murine lung fibrosis model

Interstitial lung diseases such as idiopathic pulmonary fibrosis (IPF) are caused by persistent micro-injuries to alveolar epithelial tissues accompanied by aberrant repair processes. IPF is currently treated with pirfenidone and nintedanib, compounds which slow the rate of disease progression but fail to target underlying pathophysiological mechanisms. The DNA repair protein 8-oxoguanine DNA glycosylase-1 (OGG1) has significant roles in the modulation of inflammation and metabolic syndromes. Currently, no pharmaceutical solutions targeting OGG1 have been utilized in the treatment of IPF. In this study we show Ogg1-targeting siRNA mitigates bleomycin-induced pulmonary fibrosis in male mice, highlighting OGG1 as a tractable target in lung fibrosis. The small molecule OGG1 inhibitor, TH5487, decreases myofibroblast transition and associated pro-fibrotic gene expressions in fibroblast cells. In addition, TH5487 decreases levels of pro-inflammatory mediators, inflammatory cell infiltration, and lung remodeling in a murine model of bleomycin-induced pulmonary fibrosis conducted in male C57BL6/J mice. OGG1 and SMAD7 interact to induce fibroblast proliferation and differentiation and display roles in fibrotic murine and IPF patient lung tissue. Taken together, these data suggest that TH5487 is a potentially clinically relevant treatment for IPF but further study in human trials is required

Effects of dietary carotenoids on mouse lung genomic profiles and their modulatory effects on short-term cigarette smoke exposures

Male C57BL/6 mice were fed diets supplemented with either β-carotene (BC) or lycopene (LY) that were formulated for human consumption. Four weeks of dietary supplementations results in plasma and lung carotenoid (CAR) concentrations that approximated the levels detected in humans. Bioactivity of the CARs was determined by assaying their effects on the activity of the lung transcriptome (~8,500 mRNAs). Both CARs activated the cytochrome P450 1A1 gene but only BC induced the retinol dehydrogenase gene. The contrasting effects of the two CARs on the lung transcriptome were further uncovered in mice exposed to cigarette smoke (CS) for 3 days; only LY activated ~50 genes detected in the lungs of CS-exposed mice. These genes encoded inflammatory-immune proteins. Our data suggest that mice offer a viable in vivo model for studying bioactivities of dietary CARs and their modulatory effects on lung genomic expression in both health and after exposure to CS toxicants

Co-Expression of α9β1 Integrin and VEGF-D Confers Lymphatic Metastatic Ability to a Human Breast Cancer Cell Line MDA-MB-468LN

INTRODUCTION AND OBJECTIVES: Lymphatic metastasis is a common occurrence in human breast cancer, mechanisms remaining poorly understood. MDA-MB-468LN (468LN), a variant of the MDA-MB-468GFP (468GFP) human breast cancer cell line, produces extensive lymphatic metastasis in nude mice. 468LN cells differentially express α9β1 integrin, a receptor for lymphangiogenic factors VEGF-C/-D. We explored whether (1) differential production of VEGF-C/-D by 468LN cells provides an autocrine stimulus for cellular motility by interacting with α9β1 and a paracrine stimulus for lymphangiogenesis in vitro as measured with capillary-like tube formation by human lymphatic endothelial cells (HMVEC-dLy); (2) differential expression of α9 also promotes cellular motility/invasiveness by interacting with macrophage derived factors; (3) stable knock-down of VEGF-D or α9 in 468LN cells abrogates lymphangiogenesis and lymphatic metastasis in vivo in nude mice. RESULTS: A comparison of expression of cyclo-oxygenase (COX)-2 (a VEGF-C/-D inducer), VEGF-C/-D and their receptors revealed little COX-2 expression by either cells. However, 468LN cells showed differential VEGF-D and α9β1 expression, VEGF-D secretion, proliferative, migratory/invasive capacities, latter functions being stimulated further with VEGF-D. The requirement of α9β1 for native and VEGF-D-stimulated proliferation, migration and Erk activation was demonstrated by treating with α9β1 blocking antibody or knock-down of α9. An autocrine role of VEGF-D in migration was shown by its impairment by silencing VEGF-D and restoration with VEGF-D. 468LN cells and their soluble products stimulated tube formation, migration/invasiveness of HMVEC-dLy cell in a VEGF-D dependent manner as indicated by the loss of stimulation by silencing VEGF-D in 468LN cells. Furthermore, 468LN cells showed α9-dependent stimulation of migration/invasiveness by macrophage products. Finally, capacity for intra-tumoral lymphangiogenesis and lymphatic metastasis in nude mice was completely abrogated by stable knock-down of either VEGF-D or α9 in 468LN cells. CONCLUSION: Differential capacity for VEGF-D production and α9β1 integrin expression by 468LN cells jointly contributed to their lymphatic metastatic phenotype

Co-production of knowledge as part of a OneHealth approach to better control zoonotic diseases

There is increased global and national attention on the need for effective strategies to control zoonotic diseases. Quick, effective action is, however, hampered by poor evidence-bases and limited coordination between stakeholders from relevant sectors such as public and animal health, wildlife and forestry sectors at different scales, who may not usually work together. The OneHealth approach recognises the value of cross-sectoral evaluation of human, animal and environmental health questions in an integrated, holistic and transdisciplinary manner to reduce disease impacts and/or mitigate risks. Co-production of knowledge is also widely advocated to improve the quality and acceptability of decision-making across sectors and may be particularly important when it comes to zoonoses. This paper brings together OneHealth and knowledge co-production and reflects on lessons learned for future OneHealth co-production processes by describing a process implemented to understand spill-over and identify disease control and mitigation strategies for a zoonotic disease in Southern India (Kyasanur Forest Disease). The co-production process aimed to develop a joint decision-support tool with stakeholders, and we complemented our approach with a simple retrospective theory of change on researcher expectations of the system-level outcomes of the co-production process. Our results highlight that while co-production in OneHealth is a difficult and resource intensive process, requiring regular iterative adjustments and flexibility, the beneficial outcomes justify its adoption. A key future aim should be to improve and evaluate the degree of inter-sectoral collaboration required to achieve the aims of OneHealth. We conclude by providing guidelines based on our experience to help funders and decision-makers support future co-production processes

Describing the impact of health research: a Research Impact Framework

BACKGROUND: Researchers are increasingly required to describe the impact of their work, e.g. in grant proposals, project reports, press releases and research assessment exercises. Specialised impact assessment studies can be difficult to replicate and may require resources and skills not available to individual researchers. Researchers are often hard-pressed to identify and describe research impacts and ad hoc accounts do not facilitate comparison across time or projects. METHODS: The Research Impact Framework was developed by identifying potential areas of health research impact from the research impact assessment literature and based on research assessment criteria, for example, as set out by the UK Research Assessment Exercise panels. A prototype of the framework was used to guide an analysis of the impact of selected research projects at the London School of Hygiene and Tropical Medicine. Additional areas of impact were identified in the process and researchers also provided feedback on which descriptive categories they thought were useful and valid vis-à-vis the nature and impact of their work. RESULTS: We identified four broad areas of impact: I. Research-related impacts; II. Policy impacts; III. Service impacts: health and intersectoral and IV. Societal impacts. Within each of these areas, further descriptive categories were identified. For example, the nature of research impact on policy can be described using the following categorisation, put forward by Weiss: Instrumental use where research findings drive policy-making; Mobilisation of support where research provides support for policy proposals; Conceptual use where research influences the concepts and language of policy deliberations and Redefining/wider influence where research leads to rethinking and changing established practices and beliefs. CONCLUSION: Researchers, while initially sceptical, found that the Research Impact Framework provided prompts and descriptive categories that helped them systematically identify a range of specific and verifiable impacts related to their work (compared to ad hoc approaches they had previously used). The framework could also help researchers think through implementation strategies and identify unintended or harmful effects. The standardised structure of the framework facilitates comparison of research impacts across projects and time, which is useful from analytical, management and assessment perspectives

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council

Extent of knowledge and attitudes on plagiarism among undergraduate medical students in South India - a multicentre, cross-sectional study to determine the need for incorporating research ethics in medical undergraduate curriculum

BACKGROUND: Undergraduate medical students in India participate in various research activities However, plagiarism is rampant, and we hypothesize that it is the lack of knowledge on how to avoid plagiarism. This study’s objective was to measure the extent of knowledge and attitudes towards plagiarism among undergraduate medical students in India. METHODS: It was a multicentre, cross-sectional study conducted over a two-year period (January 2018 – December 2019). Undergraduate medical students were given a pre-tested semi-structured questionnaire which contained: (a) Demographic details; (b) A quiz developed by Indiana University, USA to assess knowledge; and (c) Attitudes towards Plagiarism (ATP) questionnaire. RESULTS: Eleven medical colleges (n = 4 government medical colleges [GMCs] and n = 7 private medical colleges [PMCs]) participated. A total of N = 4183 students consented. The mean (SD) knowledge score was 4.54 (1.78) out of 10. The factors (adjusted odds ratio [aOR]; 95% Confidence interval [CI]; p value) that emerged as significant predictors of poor knowledge score were early years of medical education (0.110; 0.063, 0.156; < 0.001) and being enrolled in a GMC (0.348; 0.233, 0.463; < 0.001).The overall mean (SD) scores of the three attitude components namely permissive, critical and submissive norms were 37.56 (5.25), 20.35 (4.20) and 31.20 (4.28) respectively, corresponding to the moderate category. CONCLUSION: The overall knowledge score was poor. A vast majority of study participants fell in the moderate category of attitude score. These findings warrant the need for incorporating formal training in the medical education curriculum