Andy Burnham is set to spend his first day working at the northern branch of Downing Street. No 10 North in Manchester will form part of the prime minister's aim to shift power from Whitehall and Westminster to regions across the country. Ministers Lucy Powell and Louise Haigh will also operate regularly from the new site, with up to 300 civil servants expected to join them by the end of next year. On Friday in Manchester Burnham will chair a meeting of the National Economic Council, a cabinet committee first launched in 2008 to respond to economic challenges around the UK. Ahead of that meeting, the PM said: For 40 years, power and resources have been sucked into the centre, and too many communities have felt forgotten, without the attention and investment they deserve.

Follow this section to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW? Smart Alerts: Get notified about major news as it happens. Follow this tag to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW?

Follow this section to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW? Smart Alerts: Get notified about major news as it happens. Follow this tag to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW?

Follow this section to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW? Smart Alerts: Get notified about major news as it happens. Follow this tag to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW?

Angeliki Stogia has been selected as the Labour Party candidate for the upcoming Gorton and Denton by-election. The Manchester councillor was chosen to represent the party after Greater Manchester mayor Andy Burnham was denied permission to enter the contest a week ago. The by-election on 26 February in the Greater Manchester constituency was prompted by the resignation of former MP Andrew Gwynne on health grounds. Stogia said she was thrilled and excited as a proud Mancunian woman to start campaigning in the constituency. She said she was so looking forward to going out on the doorstep and winning this for Labour.

'I spoke to ChatGPT 8 times a day' - Gen Z's loneliness'crisis' Working from home after years spent alone over Covid lockdowns, 23-year-old Paisley said he began to feel trapped, and felt only AI could help him. I lost the ability to socialise, he said, and like many in Gen Z, he turned to AI for company. At one point, I was talking to ChatGPT six, seven, eight times a day about my problems, I just couldn't get away from it, it was a dangerous slope. He shared his experience of loneliness with 22-year-old documentary maker Sam Tullen, who told the BBC what Paisley was going through was part of a wider Gen Z loneliness crisis. Gen Z, a term used for those born between 1997 and 2012, often referred to as the first'digital native' generation.

Objective: Large language models (LLMs) are attracting increasing interest in healthcare. This commentary evaluates the potential of LLMs to improve clinical prediction models (CPMs) for diagnostic and prognostic tasks, with a focus on their ability to process longitudinal electronic health record (EHR) data. Findings: LLMs show promise in handling multimodal and longitudinal EHR data and can support multi-outcome predictions for diverse health conditions. However, methodological, validation, infrastructural, and regulatory chal- lenges remain. These include inadequate methods for time-to-event modelling, poor calibration of predictions, limited external validation, and bias affecting underrepresented groups. High infrastructure costs and the absence of clear regulatory frameworks further prevent adoption. Implications: Further work and interdisciplinary collaboration are needed to support equitable and effective integra- tion into the clinical prediction. Developing temporally aware, fair, and explainable models should be a priority focus for transforming clinical prediction workflow.

Survivors of childhood cancer need lifelong monitoring for side effects from radiotherapy. However, longitudinal data from routine monitoring is often infrequently and irregularly sampled, and subject to inaccuracies. Due to this, measurements are often studied in isolation, or simple relationships (e.g., linear) are used to impute missing timepoints. In this study, we investigated the potential role of Gaussian Processes (GP) modelling to make population-based and individual predictions, using insulin-like growth factor 1 (IGF-1) measurements as a test case. With training data of 23 patients with a median (range) of 4 (1-16) timepoints we identified a trend within the range of literature reported values. In addition, with 8 test cases, individual predictions were made with an average root mean squared error of 31.9 (10.1 - 62.3) ng/ml and 27.4 (0.02 - 66.1) ng/ml for two approaches. GP modelling may overcome limitations of routine longitudinal data and facilitate analysis of late effects of radiotherapy.

'This is a matter of national security.' An artist's rendering of the spacecraft in the SWIFT constellation stationed in a triangular pyramid formation between the sun and Earth. A solar sail allows the spacecraft at the pyramid's tip to hold station without conventional fuel. Breakthroughs, discoveries, and DIY tips sent every weekday. Just like Earth's severe thunderstorms, solar storms can cause their own kinds of havoc.

This paper examines the impact of Generative Artificial Intelligence (GenAI) on scientific practices, conducting a qualitative review of selected literature to explore its applications, benefits, and challenges. The review draws on the OpenAlex publication database, using a Boolean search approach to identify scientific literature related to GenAI (including large language models and ChatGPT). Thirty-nine highly cited papers and commentaries are reviewed and qualitatively coded. Results are categorized by GenAI applications in science, scientific writing, medical practice, and education and training. The analysis finds that while there is a rapid adoption of GenAI in science and science practice, its long-term implications remain unclear, with ongoing uncertainties about its use and governance. The study provides early insights into GenAI's growing role in science and identifies questions for future research in this evolving field.