Neonicotinoids thiamethoxam and clothianidin adversely affect the colonisation of invertebrate populations in aquatic microcosms

Surface waters are sometimes contaminated with neonicotinoids: a widespread, persistent, systemic class of insecticide with leaching potential. Previous ecotoxicological investigations of this chemical class in aquatic ecosystems have largely focused on the impacts of the neonicotinoid imidacloprid; few empirical, manipulative studies have investigated the effect on invertebrate abundances of two other neonicotinoids which are now more widely used: clothianidin and thiamethoxam. In this study, we employ a simple microcosm semi-field design, incorporating a one-off contamination event, to investigate the effect of these pesticides at field-realistic levels (ranging from 0 to 15 ppb) on invertebrate colonisation and survival in small ephemeral ponds. In line with previous research on neonicotinoid impacts on aquatic invertebrates, significant negative effects of both neonicotinoids were found. There were clear differences between the two chemicals, with thiamethoxam generally producing stronger negative effects than clothianidin. Populations of Chironomids (Diptera) and Ostracoda were negatively affected by both chemicals, while Culicidae appeared to be unaffected by clothianidin at the doses used. Our data demonstrate that field-realistic concentrations of neonicotinoids are likely to reduce populations of invertebrates found in ephemeral ponds, which may have knock on effects up the food chain. We highlight the importance of developing pesticide monitoring schemes for European surface waters

Kidney transplant in diabetic patients: modalities, indications and results

<p>Abstract</p> <p>Background</p> <p>Diabetes is a disease of increasing worldwide prevalence and is the main cause of chronic renal failure. Type 1 diabetic patients with chronic renal failure have the following therapy options: kidney transplant from a living donor, pancreas after kidney transplant, simultaneous pancreas-kidney transplant, or awaiting a deceased donor kidney transplant. For type 2 diabetic patients, only kidney transplant from deceased or living donors are recommended. Patient survival after kidney transplant has been improving for all age ranges in comparison to the dialysis therapy. The main causes of mortality after transplant are cardiovascular and cerebrovascular events, infections and neoplasias. Five-year patient survival for type 2 diabetic patients is lower than the non-diabetics' because they are older and have higher body mass index on the occasion of the transplant and both pre- and posttransplant cardiovascular diseases prevalences. The increased postransplant cardiovascular mortality in these patients is attributed to the presence of well-known risk factors, such as insulin resistance, higher triglycerides values, lower HDL-cholesterol values, abnormalities in fibrinolysis and coagulation and endothelial dysfunction. In type 1 diabetic patients, simultaneous pancreas-kidney transplant is associated with lower prevalence of vascular diseases, including acute myocardial infarction, stroke and amputation in comparison to isolated kidney transplant and dialysis therapy.</p> <p>Conclusion</p> <p>Type 1 and 2 diabetic patients present higher survival rates after transplant in comparison to the dialysis therapy, although the prevalence of cardiovascular events and infectious complications remain higher than in the general population.</p

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Router, network comprising a router, method for routing data in a network

A router for a network is arranged for guiding data traffic from one of a first plurality Ni of inputs (I) to one or more of a second plurality No of outputs (O). The inputs each have a third plurality m of input queues for buffering data. The third plurality m is greater than 1, but less than the second plurality No. The router includes a first selection facility for writing data received at an input to a selected input queue of the input, and a second selection facility for providing data from an input queue to a selected output. Pairs of packets having different destinations Oj and Ok are arranged in the same queue for a total number of Nj,k inputs, characterized in that Nj,