Comparative sanitation data from high-frequency phone surveys across 3 countries.

With less than half of the world's urban population having safely managed sanitation due to the high cost and difficulty of building sewers and treatment plants, many rely on off-grid options like pit latrines and septic tanks, which are hard to empty and often lead to illegal waste dumping; this research focuses on container-based sanitation (CBS) as an emerging off-grid solution. Off-grid sanitation refers to waste management systems that operate independently of centralized infrastructure and CBS is a service providing toilets that collect human waste in sealable containers, which are regularly emptied and safely disposed of. These data relate to a project investigating CBS in Kenya, Peru, and South Africa, focusing on how different user groups access and utilize sanitation - contrasting CBS with other types. Participants, acting as citizen scientists, collected confidential data through a dedicated smartphone app designed by the authors and external contractors. This project aimed to explore the effective scaling, management, and regulation of off-grid sanitation systems, relevant to academics in urban planning, water and sanitation services, institutional capability, policy and governance, and those addressing inequality and poverty reduction. The 12-month data collection period offered participants small incentives for weekly engagement, in a micro payment for micro tasks approach. Participants were randomly selected, attended a training workshop, and (where needed) were given a smartphone which they could keep at the end of the project. We conducted weekly smartphone surveys in over 300 households across informal settlements. These surveys aimed to understand human-environment interactions by capturing daily life, wellbeing, income, infrastructural service use, and socioeconomic variables at a weekly resolution, contributing to more informed analyses and decision-making. The smartphone-based approach offers efficient, cost-effective, and flexible data collection, enabling extensive geographical coverage, broad subject areas, and frequent engagement. The Open Data Kit (ODK) tools were used to support data collection in the resource-constrained environment with limited or intermittent connectivity.

Enhanced skin regeneration and therapeutic delivery using novel diamond-augmented zinc oxide.

BACKGROUND: Recent advancements in dermatological therapeutics have highlighted the need for treatments that enhance skin regeneration and healing. Diamond-Augmented Zinc Oxide (ND-ZnO) technology combines zinc oxide with diamond particles in a unique core-shell structure, offering a multifaceted approach to overall skin health. AIMS: This study evaluates the efficacy of ND-ZnO in promoting human dermal fibroblast migration and growth, enhancing total collagen synthesis, and improving transdermal delivery of active ingredients as a daily comprehensive skin regeneration topical therapy. PATIENTS/METHODS: In vitro assays assessed wound healing, collagen production, and skin absorption. Human Dermal Fibroblasts (HDFs) were used in scratch wound assays. Collagen synthesis was quantified using enzyme-linked immunosorbent assays (ELISA). Permeation tests were performed on reconstructed human epidermal tissues to evaluate niacinamide absorption. Clinical case studies validated ND-ZnO efficacy in post-CO2 laser treatments and Actinic Keratosis removal recovery. RESULTS: ND-ZnO increased HDF migration by 198% compared to controls. Collagen synthesis assays showed a 71.3% restoration of collagen production in aged HDFs. Skin permeation studies revealed a 203% increase in niacinamide skin absorption with ND-ZnO. Clinical case studies demonstrated faster and more effective healing post-ablative CO2 laser and significant improvements in Actinic Keratosis recovery. CONCLUSIONS: ND-ZnO technology enhances wound healing, collagen synthesis, and active ingredient delivery, offering substantial benefits for daily skin regeneration and other dermatological applications. This innovative approach holds promise for advancing dermatological therapeutics, providing comprehensive skin care solutions that address both protective and regenerative needs.

Tribbles1 is host protective during in vivo mycobacterial infection.

Tuberculosis is a major global health problem and is one of the top 10 causes of death worldwide. There is a pressing need for new treatments that circumvent emerging antibiotic resistance. Mycobacterium tuberculosis parasitises macrophages, reprogramming them to establish a niche in which to proliferate, therefore macrophage manipulation is a potential host-directed therapy if druggable molecular targets could be identified. The pseudokinase Tribbles1 (Trib1) regulates multiple innate immune processes and inflammatory profiles making it a potential drug target in infections. Trib1 controls macrophage function, cytokine production, and macrophage polarisation. Despite wide-ranging effects on leukocyte biology, data exploring the roles of Tribbles in infection in vivo are limited. Here, we identify that human Tribbles1 is expressed in monocytes and is upregulated at the transcript level after stimulation with mycobacterial antigen. To investigate the mechanistic roles of Tribbles in the host response to mycobacteria in vivo, we used a zebrafish Mycobacterium marinum (Mm) infection tuberculosis model. Zebrafish Tribbles family members were characterised and shown to have substantial mRNA and protein sequence homology to their human orthologues. trib1 overexpression was host-protective against Mm infection, reducing burden by approximately 50%. Conversely, trib1 knockdown/knockout exhibited increased infection. Mechanistically, trib1 overexpression significantly increased the levels of proinflammatory factors il-1ß and nitric oxide. The host-protective effect of trib1 was found to be dependent on the E3 ubiquitin kinase Cop1. These findings highlight the importance of Trib1 and Cop1 as immune regulators during infection in vivo and suggest that enhancing macrophage TRIB1 levels may provide a tractable therapeutic intervention to improve bacterial infection outcomes in tuberculosis.

Single cell sequencing data identify distinct B cell and fibroblast populations in stricturing Crohn's disease.

Single cell RNA sequencing of human full thickness Crohn's disease (CD) small bowel resection specimens was used to identify potential therapeutic targets for stricturing (S) CD. Using an unbiased approach, 16 cell lineages were assigned within 14,539 sequenced cells from patient-matched SCD and non-stricturing (NSCD) preparations. SCD and NSCD contained identical cell types. Amongst immune cells, B cells and plasma cells were selectively increased in SCD samples. B cell subsets suggested formation of tertiary lymphoid tissue in SCD and compared with NSCD there was an increase in IgG, and a decrease in IgA plasma cells, consistent with their potential role in CD fibrosis. Two Lumican-positive fibroblast subtypes were identified and subclassified based on expression of selectively enriched genes as fibroblast clusters (C) 12 and C9. Cells within these clusters expressed the profibrotic genes Decorin (C12) and JUN (C9). C9 cells expressed ACTA2; ECM genes COL4A1, COL4A2, COL15A1, COL6A3, COL18A1 and ADAMDEC1; LAMB1 and GREM1. GO and KEGG Biological terms showed extracellular matrix and stricture organization associated with C12 and C9, and regulation of WNT pathway genes with C9. Trajectory and differential gene analysis of C12 and C9 identified four sub-clusters. Intra sub-cluster gene analysis detected 13 co-regulated gene modules that aligned along predicted pseudotime trajectories. CXCL14 and ADAMDEC1 were key markers in module 1. Our findings support further investigation of fibroblast heterogeneity and interactions with local and circulating immune cells at earlier time points in fibrosis progression. Breaking these interactions by targeting one or other population may improve therapeutic management for SCD.

A Dual Inertial Measurement Unit System for Classifying Standard Overhead Drill Movements in Elite Women's Water Polo.

INTRODUCTION: Water polo upper limb external load monitoring cannot be currently measured accurately because of technological and methodological challenges. This is problematic as large fluctuations in overhead movement volume and intensity may affect performance and alter injury risk. Inertial measurement units (IMU) and machine learning techniques have been shown to accurately classify overhead movements in other sports. We investigated the model accuracy and class precision, sensitivity, and specificity of IMU and machine learning techniques to classify standard overhead drill movements in elite women's water polo. METHODS: Ten women's water polo players performed standard drills of swimming, blocking, low-intensity throwing and high-intensity throwing under training conditions. Athletes wore two IMU: one on the upper back and the other on the distal forearm. Each movement was videoed and coded to a standard overhead drill movement. IMU and coded video data were merged to verify the IMU-detected activity classification of each movement to that of the video. Data were partitioned into a training and a test set and used to form a decision tree algorithm. Model accuracy and class precision, sensitivity, and specificity were assessed. RESULTS: IMU resultant acceleration and angular velocity values displayed drill-specific values. A total of 194 activities were identified by the model in the test set, with 8 activities being incorrectly classified. Model accuracy was 95.88%. Percentage class precision, sensitivity, and specificity were as follows: blocking (96.15, 86.21, 99.39), high-intensity throwing (100, 100, 100), low-intensity throwing (93.48, 93.48, 97.97), and swimming (94.81, 98.65, 96.67). CONCLUSIONS: IMU and machine learning techniques can accurately classify standard overhead drill movements in elite women's water polo.