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Bariatric and metabolic surgery in septuagenarians in England: a matched survival analysis
No full textBackground
The prevalence of obesity is rising alongside population ageing, yet the long-term benefits of metabolic and bariatric surgery (MBS) in older adults remain unclear. We aimed to evaluate the impact of MBS on survival in individuals aged ≥69 years with obesity.
Methods
We conducted a retrospective cohort study of patients aged ≥69 years managed in a UK tertiary bariatric centre between 2015 and 2024. Patients who underwent MBS were compared with matched controls who did not undergo MBS. Mahalanobis distance matching was performed (1:1) using age, BMI, ASA grade, type 2 diabetes, and cardiovascular disease. The primary outcome was all-cause mortality. Cox regression was used to assess survival.
Findings
One hundred and eighty-six patients were included; 44 underwent MBS. After matching, 44 MBS patients were compared to 34 controls. Median follow-up was 39 (IQR: 22-70) months. Matched Kaplan–Meier analysis demonstrated superior survival among MBS patients (p=0·004). MBS was associated with a 68% reduction in all-cause mortality on univariate analysis (HR 0·32, 95% CI: 0·11-0·92, p=0·036) and a 75% reduction in all-cause mortality on multivariate analysis (HR 0·25, 95% CI: 0·08-0·77, p=0·015). The postoperative 30-day morbidity rate was 9·1%, major complications occurred in 6·8%, and the mortality rate was 2·3%.
Interpretation
In a specialist setting, MBS was independently associated with improved survival in septuagenarians, with acceptable perioperative risk. Chronological age alone should not preclude consideration for MBS. These findings support further evaluation of surgical options in well-selected older adults living with obesity
From attention to activation: unraveling the enigmas of large language models
No full textWe study two strange phenomena in auto-regressive Transformers: (1) the dominance of the first token in attention heads; (2) the occurrence of large outlier activations in the hidden states. We find that popular large language models, such as Llama attend maximally to the first token in 98% of attention heads, a behaviour we attribute to the softmax function. To mitigate this issue, we propose a reformulation of softmax to softmax-1. Furthermore, we identify adaptive optimisers, e.g., Adam, as the primary contributor to the large outlier activations and introduce OrthoAdam, a novel optimiser that utilises orthogonal matrices to transform gradients, to address this issue. Finally, not only do our methods prevent these phenomena from occurring, but additionally, they enable Transformers to sustain their performance when quantised using basic algorithms, something that standard methods are unable to do. In summary, our methods reduce the attention proportion on the first token from 65% to 3.3%, the activation kurtosis in the hidden states from 1657 to 3.1, and perplexity penalty under 4-bit weight quantisation from 3565 to 0.3. Code is available at https://github.com/prannaykaul/OrthoAdam
Frequent failure of nutrients to increase plant biomass supports the need for precision fertilization in agriculture
No full textImplementing precision fertilization to maximize crop yield while minimizing economic and environmental impacts has become critical for agriculture. Variability in biomass response to fertilization within fields, among regions, and over time creates simultaneous risks of under-yielding and overfertilization. We quantify factors determining fertilization responsiveness (i.e., biomass increases with fertilization) up to 15 years in 61 unfertilized rangelands on six continents. We demonstrate widespread multi-year variability in responsiveness, with fertilization increasing average yield by 43% but failing to improve biomass 26% of the time. All sites were responsive at least once, but only four of 61 responded in all plots and years. Modelled management scenarios highlighted that fertilizer cessation is likely to generate sizable economic savings but always reduces yield because of the difficulty in predicting when and where biomass will be unresponsive. This work reveals substantial scale-dependent variability in fertilization responsiveness globally, while clarifying the prospects and pitfalls of managing more spatially and temporally precise nutrient application
Effects of SGLT2 ablation or inhibition on corticosterone secretion in high-fat-fed mice: exploring a nexus with cytokine levels
No full textAims/hypothesis Despite recent therapeutic advances, achieving optimal glycaemic control remains a challenge in managing type 2 diabetes. Sodium–glucose cotransporter 2 (SGLT2) inhibitors have emerged as effective treatments by promoting
urinary glucose excretion. However, the full scope of their mechanisms extends beyond glycaemic control. At present, their
immunometabolic effects remain elusive.
Methods To investigate the effects of SGLT2 inhibition or deletion, we compared the metabolic and immune phenotype
between high-fat-diet-fed control mice, mice treated chronically with dapagliflozin, and total-body Slc5a2-knockout mice.
Results SGLT2-null mice exhibited better glucose tolerance and insulin sensitivity (blood glucose during IPGTT AUC
0–90 min 1175 ± 57.4 mmol/l × min, mean ± SEM) compared with control (AUC 0–90 min 1857 ± 117.9 mmol/l × min,
p=0.05) or dapagliflozin-treated mice (AUC 0–90 min 1506 ± 68.72 mmol/l × min, p=0.09), independent of glycosuria and
body weight. Moreover, SGLT2-null mice demonstrated physiological regulation of corticosterone secretion, with lower
morning levels than control mice (p<0.01). Systemic cytokine profiling also unveiled significant alterations in inflamma tory mediators, particularly IL-6. Furthermore, unbiased proteomic analysis demonstrated downregulation of acute-phase
proteins and upregulation of glutathione-related proteins, suggesting a role in the modulation of antioxidant responses.
Conversely, IL-6 treatment increased SGLT2 expression in human kidney HK2 cells, suggesting a role for cytokines in the
effects of hyperglycaemia.
Conclusions/interpretation Collectively, our data elucidate a potential interplay between SGLT2 activity, immune modulation and metabolic homeostasis, as well as a potential feedback loop between SGLT2 expression and cytokine concentratio
Towards efficient end-of-life solutions in offshore wind
No full textOffshore wind farms, facilitating the exploitation of wind power as a renewable energy source, have grown rapidly in many parts of the world, including the North Sea, over the past decade. Their design life is envisaged to be approximately 25 years, and the current default end-of-life solution is that of full decommissioning, whereby developers are expected to remove all parts of the wind farm and restore the seabed to its prior condition. However, as some of the oldest installations are now nearing the end of their life, different forms of life extension for existing sites are considered as alternative and more sustainable solutions compared to full decommissioning. Some current studies consider partial decommissioning of a wind turbine, which involves completely removing the superstructure to the seabed level, leaving the original monopile embedded in the seabed. Considering that the power and size of turbines have been increasing, a new turbine will most likely need the support of a larger monopile, which could be installed to enclose the existing smaller monopile. The potential benefit of this approach is the avoidance of seabed disturbance by prior extraction of the existing monopile and the associated costs of such extraction. The study in this paper is exploratory and numerical in nature, utilising finite element analysis and parametric variations of monopile geometries in two distinctive seabed settings: a glacial till and a dense marine sand. The results focus on identifying the interaction mechanisms between the two monopiles based on their geometry
Scaling GR(1) synthesis via a compositional framework for LTL discrete event control
No full textWe present a compositional approach to controller synthe-
sis of discrete event system controllers with linear temporal logic (LTL) goals. We exploit the modular structure of the plant to be controlled, given as a set of labelled transition systems (LTS), to mitigate state explosion that monolithic approaches to synthesis are prone to. Maximally permissive safe controllers are iteratively built for subsets of the plant LTSs by solving weaker control problems. Observational synthesis equivalence is used to reduce the size of the controlled subset of the plant by abstracting away local events. The result of synthesis is also compositional, a set of controllers that when run in parallel ensure the LTL goal.
We implement synthesis in the MTSA tool for an expressive subset of LTL, GR(1), and show it computes solutions to that can be up to 1000 times larger than those that the monolithic approach can solve
Towards passively actuated short-range telehaptics for astronauts
No full textHuman extra-vehicular activity (EVA) plays a vital role in current and near future space exploration for two reasons: the superior dexterity exhibited by human astronauts, and their flexible problem-solving and decision-making capabilities. However, the dexterity of astronauts during EVA is limited by the flexibility and tactility of their EVA suit gloves, which are primarily designed to provide thermal insulation and pressure for the hand. This creates a compromise between utility and protection. To address this compromise, a Passively Actuated Short-range Telehaptic (PAST) device is proposed. The PAST device couples the motion of fingers between a robotic hand and a human hand through a hydraulically actuated linkage. It also transfers tactile information, including pressure, direction of motion, and position of contact, via a taxel array. Results demonstrate that the proposed prototype PAST device surpasses an unpressurised benchmark heavy work glove
(HWG) in tasks involving tactile position and motion direction identification. This provides evidence supporting the feasibility of enhancing astronaut dexterity during EVA through the use of PAST devices as an alternative paradigm to gloves
Assessing and improving methods and software tools for real-time outbreak response
No full textInfectious diseases are responsible for millions of preventable deaths per year globally. The frequency and severity of infectious disease outbreaks are increasing due to factors such as urbanisation, globalisation and climate change. In order to identify ways to improve our ability to respond effectively to infectious threats, we must evaluate the strengths and weaknesses of our current methods and software tools for outbreak analytics.
This thesis uses branching process methods for estimating the time-varying reproduction number (Rt) as a case study to reveal the common challenges encountered when responding to outbreaks in realtime. The findings highlight the need for resources to facilitate rapid and accurate parameterisation of models, the importance of extending tools to directly answer policy-relevant questions, and the necessity of accounting for limitations in disease incidence data.
In response to these issues, open source R packages and resources have been developed. An open source database and R package have been created to rapidly parameterise models for a WHO priority disease, Ebola Virus Disease. Additionally, the R package EpiEstim has been extended to estimate the transmission advantage of new pathogen variants in real-time and an Expectation-Maximisation algorithm has been implemented to reconstruct daily incidence data from any temporal aggregation of incidence. These developments prioritise usability alongside functionality, ensuring that they are widely accessible and applicable in a variety of outbreak contexts.
Overall, this thesis emphasises the importance of continuous innovation and evaluation of outbreak analytics tools to meet the evolving challenges of future epidemics and pandemics.Open Acces
Hill-type models of skeletal muscle and neuromuscular actuators: a systematic review
No full textBacked by a century of research and development, Hill-type models of skeletal muscle, often including a muscle-tendon complex and neuromechanical interface, are widely used for countless applications. Lacking recent comprehensive reviews, the field of Hill-type modeling is, however, dense and hard-to-explore, with detrimental consequences on innovation. Here we present the first systematic review of Hill-type muscle modeling. It aims to clarify the literature by detailing its contents and critically discussing the state-of-the-art by identifying the latest advances, current gaps, and potential future directions in Hill-type modeling. For this purpose, fifty-eight criteria-abiding Hill-type models were assessed according to a completeness evaluation, which identified the modelled muscle properties, and a modeling evaluation, which considered the level of validation and reusability of the models, as well as their modeling strategy and calibration. It is concluded that most models (1) do not significantly advance beyond historical foundational standards, (2) neglect the importance of parameter identification, (3) lack robust validation, and (4) are not reusable in other studies. Besides providing a convenient tool supported by extensive supplementary materials for navigating the literature, the results of this review highlight the need for global recommendations in Hill-type modeling to optimize inter-study consistency, knowledge transfer, and model reusability
Extracting self-similarity from data
No full textIdentifying self-similarity is key to understanding and modelling a plethora of phenomena in fluid mechanics. Unfortunately, this is not always possible to perform formally in highly complex flows. We propose a methodology to extract the similarity variables of a self-similar physical process directly from data, without prior knowledge of the governing equations or boundary conditions, based on an optimisation problem and symbolic regression. We analyse the accuracy and robustness of our method in five problems which have been influential in fluid mechanics research: a laminar boundary layer, Burger’s equation, a turbulent wake, a collapsing cavity and decaying turbulence. Our analysis considers datasets acquired via both numerical and wind tunnel experiments. The algorithm recovers the known self-similarity expressions in the first four problems and generates new insights into single length scale theories of homogeneous turbulence