Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Seasonal intercomparison of observational rainfall datasets over India during the southwest monsoon season

The Indian monsoon is an important component of Earth's climate system, accurate forecasting of its mean rainfall being essential for regional food and water security. Accurate measurement of rainfall is essential for various water-related applications, the evaluation of numerical models and detection and attribution of trends, but a variety of different gridded rainfall datasets are available for these purposes. In this study, six gridded rainfall datasets are compared against the India Meteorological Department (IMD) gridded rainfall dataset, chosen as the most representative of the observed system due to its high gauge density. The datasets comprise those based solely on rain gauge observations and those merging rain gauge data with satellite-derived products. Various skill metrics and subjective comparisons are carried out for the Indian region during the southwest monsoon season (June-September). Relative biases and skill metrics are documented at all-India and subregional scales. In the gauge-based (land-only) category, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of water resources (APHRODITE) and Global Precipitation Climatology Center (GPCC) datasets perform better relative to the others in terms of a variety of skill metrics. In the merged category, the Global Precipitation Climatology Project (GPCP) dataset is shown to perform better than the Climate Prediction Center Merged Analysis of Precipitation (CMAP) for the Indian monsoon in terms of various metrics, when compared with the IMD gridded data. Most of the datasets have difficulties in representing rainfall over orographic regions including the Western Ghats mountains, in Northeast India and the Himalayan foothills. The wide range of skill metrics seen among the datasets and even the change of sign of bias found in some years are causes of concern. This uncertainty between datasets is largest in Northeast India. These results will help those studying the Indian monsoon region to select an appropriate dataset depending on their application and focus of research

Employing mesenchymal stem cells to support tumor-targeted delivery of extracellular vesicle (EV)-encapsulated microRNA-379

Adult Mesenchymal Stem Cells (MSCs) have a well-established tumor-homing capacity, highlighting potential as tumor-targeted delivery vehicles. MSCs secrete extracellular vesicle (EV)-encapsulated microRNAs, which play a role in intercellular communication. The aim of this study was to characterize a potential tumor suppressor microRNA, miR-379, and engineer MSCs to secrete EVs enriched with miR-379 for in vivo therapy of breast cancer. miR-379 expression was significantly reduced in lymph node metastases compared to primary tumor tissue from the same patients. A significant reduction in the rate of tumor formation and growth in vivo was observed in T47D breast cancer cells stably expressing miR-379. In more aggressive HER2-amplified HCC-1954 cells, HCC-379 and HCC-NTC tumor growth rate in vivo was similar, but increased tumor necrosis was observed in HCC-379 tumors. In response to elevated miR-379, COX-2 mRNA and protein was also significantly reduced in vitro and in vivo. MSCs were successfully engineered to secrete EVs enriched with miR-379, with the majority found to be of the appropriate size and morphology of exosomal EVs. Administration of MSC-379 or MSC-NTC cells, or EVs derived from either cell population, resulted in no adverse effects in vivo. While MSC-379 cells did not impact tumor growth, systemic administration of cell-free EVs enriched with miR-379 was demonstrated to have a therapeutic effect. The data presented support miR-379 as a potent tumor suppressor in breast cancer, mediated in part through regulation of COX-2. Exploiting the tumor-homing capacity of MSCs while engineering the cells to secrete EVs enriched with miR-379 holds exciting potential as an innovative therapy for metastatic breast cancer.peer-reviewe

RETRACTED ARTICLE: Valproic acid attenuates intercellular adhesion molecule-1 and E-selectin through a chemokine ligand 5 dependent mechanism and subarachnoid hemorrhage induced vasospasm in a rat model

Abstract Background Up-regulation of regulated upon activation, normal T-cell expressed and secreted (RANTES/CCL5) and adhesion molecules is observed in the serum of animals following experimental subarachnoid hemorrhage (SAH). The present study was to examine the effect of valproic acid (VPA) on RANTES and alternation of adhesion molecules in this model. Methods A rodent SAH model was employed. Animals were randomly assigned into six groups. Basilar artery (BA) was harvested for intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule–1 (VCAM-1), and E-selectin evaluation (western blotting) and RANTES (rt-PCR). 1 ng CCL5 recombinant protein intrathecal injection was performed in the VPA + SAH groups. (N = 5). Results Convoluted internal elastic lamina, distorted endothelial wall, and smooth muscle micro-necrosis was prominently observed in the SAH groups, which is absent in the VPA treatment and the healthy controls. Treatment with VPA dose-dependently reduced the ICAM-1, E-selectin and RANTES level, compared with the SAH group (p <0.01). The administration of CCL5 significantly increased CD45(+) glia and ICAM-1 level in the VPA treatment groups. Conclusion VPA exerts its anti-vasospastic effect through the dual effect of inhibiting RANTES expression and reduced adhesion molecules. Besides, VPA also decreased CD45(+) cells transmigrated to the vascular wall. The administration of CCL5 significantly reversed the inhibitory effect of this compound on CD45(+) monocytes, E-selectin, and ICAM-1 level. This study also lends credence to support this compound could attenuate SAH induced adhesion molecules and neuro-inflammation in a CCL5 dependent mechanism