Immune cells use active tugging forces to distinguish affinity and accelerate evolution

Cells are known to exert forces to sense their physical surroundings for guidance of motion and fate decisions. Here, we propose that cells might do mechanical work to drive their own evolution, taking inspiration from the adaptive immune system. Growing evidence indicates that immune B cells - capable of rapid Darwinian evolution - use cytoskeletal forces to actively extract antigen from other cells' surface. To elucidate the evolutionary significance of force usage, we develop a theory of tug-of-war antigen extraction that maps receptor binding characteristics to clonal reproductive fitness, revealing physical determinants of selection strength. This framework unifies mechanosensing and affinity-discrimination capabilities of evolving cells: pulling against stiff antigen tethers enhances discrimination stringency at the expense of absolute extraction. As a consequence, active force usage can accelerate adaptation but may also cause extinction of cell populations, resulting in an optimal range of pulling strength that matches molecular rupture forces observed in cells. Our work suggests that nonequilibrium, physical extraction of environmental signals can make biological systems more evolvable at a moderate energy cost.Comment: 14 pages, 6 figure

Evaluation of cortical bone perfusion using dynamic contrast enhanced ultrashort echo time imaging: a feasibility study.

Background:Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has been used to study perfusion in a wide variety of soft tissues including the bone marrow. Study of perfusion in hard tissues such as cortical bone has been much more limited because of the lack of detectable MR signal from them using conventional pulse sequences. However, two-dimensional (2D) ultrashort echo time (UTE) sequences detect signal from cortical bone and allow fast imaging of this tissue. In addition, adiabatic 2D inversion recovery UTE (IR-UTE) sequences can provide excellent signal suppression of soft tissues, such as muscle and marrow, and allow cortical bone to be seen with high contrast and reduced artefacts. We aimed to assess the feasibility of using 2D UTE and 2D IR-UTE sequences to perform DCE-MRI in the cortical bone of rabbits and human volunteers. Methods:Cortical bone perfusion was studied in rabbits (n=12) and human volunteers (n=3) using 2D UTE and 2D IR-UTE sequences on a clinical 3T scanner. Dynamic data with an in-plane resolution of ~0.5×0.5 mm2, single slice thickness of 3 mm for rabbits and 10 mm for human volunteers, and temporal resolution of 23 s for 2D UTE imaging of rabbits, 28 s for 2D UTE imaging of human volunteers, and 60 s for 2D IR-UTE imaging of both the rabbits and human volunteers were acquired before and after the injection of a Gd contrast agent (Gd-BOPTA: Multihance; Bracco Imaging SpA, Milan, Italy). The dose was 0.06 mmol/kg for rabbits and 0.2 mmol/kg for human subjects. Kinetic analyses based on the Brix model, as well as simple calculations of maximum enhancement (ME) and enhancement slope (ES), were performed. Results:The 12 rabbits showed a mean Ktrans of 0.36±0.07 min-1, Kep of 8.42±3.17 min-1, ME of 28.30±6.83, ES of 0.35±0.18 for the femur with the 2D UTE sequence, and a mean Ktrans of 0.45±0.10 min-1, Kep of 9.80±0.50 min-1, ME of 48.84±12.12, and ES of 0.69±0.27 for the femur with the 2D IR-UTE sequence. Lower ME and ES values were observed in the tibial midshaft of healthy human volunteers compared to rabbits. Conclusions:These results show that 2D UTE and 2D IR-UTE sequences are capable of detecting dynamic contrast enhancement in cortical bone in both rabbits and healthy human volunteers. Clinical studies with these techniques are likely to be feasible

From Home Energy Audit to Retrofit and Beyond

Many in Michigan, like countless others across the United States, live in energy inefficient, detached single-family homes. There is an enormous opportunity to decrease state residential energy consumption and its subsequent greenhouse gas emissions, improve occupant comfort, and bolster home values by auditing and retrofitting these homes with more efficient energy systems. In accordance with Michigan state law PA 295, DTE Energy maintains an energy optimization (EO) program aimed at conserving electricity and gas. Under this program, the utility company offers residential customers several options and incentives to invest in energy saving measures. However, participation by homeowners has been limited. Through collaboration between the University of Michigan and DTE Energy, this project sought to evaluate the effectiveness of the utility’s audit-to-retrofit programs and overall residential EO program. Software tools—including MySQL (a relational database management system), R (a statistical analysis package), ArcGIS (a geographic information system), and SurveyGizmo (an online survey development platform) — facilitated quantitative and qualitative program evaluation. These findings informed actionable recommendations to increase program participation, improve customer satisfaction, and target future EO participants. This comprehensive assessment examined both temporal and spatial scales and should help create better mechanisms for data storage, manipulation, and visualization. Largescale data analysis in the context of residential energy efficiency is becoming increasingly necessary and important for utilities. An integrated approach such as the one laid out in this report could improve the way utilities like DTE Energy implement home energy efficiency programs, assess these programs, and help increase participation for future programs.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/97777/4/From_Home_Energy_Audit_to_Retrofit_and_Beyond.May_2013.V22.pd

Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review

This systematic literature review comprehensively examines the application of Large Language Models (LLMs) in forecasting and anomaly detection, highlighting the current state of research, inherent challenges, and prospective future directions. LLMs have demonstrated significant potential in parsing and analyzing extensive datasets to identify patterns, predict future events, and detect anomalous behavior across various domains. However, this review identifies several critical challenges that impede their broader adoption and effectiveness, including the reliance on vast historical datasets, issues with generalizability across different contexts, the phenomenon of model hallucinations, limitations within the models' knowledge boundaries, and the substantial computational resources required. Through detailed analysis, this review discusses potential solutions and strategies to overcome these obstacles, such as integrating multimodal data, advancements in learning methodologies, and emphasizing model explainability and computational efficiency. Moreover, this review outlines critical trends that are likely to shape the evolution of LLMs in these fields, including the push toward real-time processing, the importance of sustainable modeling practices, and the value of interdisciplinary collaboration. Conclusively, this review underscores the transformative impact LLMs could have on forecasting and anomaly detection while emphasizing the need for continuous innovation, ethical considerations, and practical solutions to realize their full potential

Short-term outcomes of robot-assisted versus video-assisted thoracoscopic surgery for non-small cell lung cancer patients with neoadjuvant immunochemotherapy: a single-center retrospective study

BackgroundNeoadjuvant immunochemotherapy has been increasingly applied to treat non-small cell lung cancer (NSCLC). However, the comparison between robotic-assisted thoracoscopic surgery (RATS) and video-assisted thoracoscopic surgery (VATS) in the feasibility and oncological efficacy following neoadjuvant immunochemotherapy is scarce. This study aims to assess the superiorities of RATS over (VATS) concerning short-term outcomes in treating NSCLC patients with neoadjuvant immunochemotherapy.MethodsNSCLC patients receiving RATS or VATS lobectomy following neoadjuvant immunochemotherapy at Shanghai Chest Hospital from 2019 to 2022 were retrospectively identified. Baseline clinical characteristics, perioperative outcomes, and survival profiles were analyzed.ResultsForty-six NSCLC patients with neoadjuvant immunochemotherapy were included and divided into the RATS (n=15) and VATS (n=31) groups. The baseline clinical characteristics and induction-related adverse events were comparable between the two groups (all p>0.050). The 30-day mortality in the RATS and VATS groups were 0% and 3.23%, respectively (p=1.000). Patients undergoing RATS were associated with reduced surgical-related intensive unit care (ICU) stay than those receiving VATS (0.0 [0.0-0.0] vs. 0.0 [0.0-1.0] days, p=0.026). Moreover, RATS assessed more N1 LNs (6.27 ± 1.94 vs 4.90 ± 1.92, p=0.042) and LN stations (3.07 ± 1.03 vs 2.52 ± 0.57, p=0.038) compared with VATS. By comparison, no difference was found in surgical outcomes, pathological results, and postoperative complications between the RATS and VATS groups (all p>0.050). Finally, RATS and VATS achieved comparable one-year recurrence-free survival (82.96% vs. 85.23%, p=0.821) and the timing of central nervous system, LN, and bone recurrences (all p>0.050).ConclusionRATS is safe and feasible for NSCLC patients with neoadjuvant immunochemotherapy, reducing surgical-related ICU stay, assessing increased N1 LNs and stations, and achieving similar survival profiles to VATS

Offshore multi-purpose platforms for a Blue Growth: a technological, environmental and socio-economic review

“Blue Growth” and “Blue Economy” is defined by the World Bank as: “the sustainable use of ocean resources for economic growth, improved livelihoods and jobs, while preserving the health of ocean ecosystem”. Multi-purpose platforms (MPPs) can be defined as offshore platforms serving the needs of multiple offshore industries (energy and aquaculture), aim at exploiting the synergies and managing the tensions arising when closely co-locating systems from these industries. Despite a number of previous projects aimed at assessing, from a multidisciplinary point of view, the feasibility of multipurpose platforms, it is here shown that the state-of-the-art has focused mainly on single-purpose devices, and adopting a single discipline (either economic, or social, or technological, or environmental) approach. Therefore, the aim of the present study is to provide a multidisciplinary state of the art review on, whenever possible, multi-purpose platforms, complementing it with single-purpose and/or single discipline literature reviews when not possible. Synoptic tables are provided, giving an overview of the multi-purpose platform concepts investigated, the numerical approaches adopted, and a comprehensive snapshot classifying the references discussed by industry (offshore renewables, aquaculture, both) and by aspect (technological, environmental, socio-economic). The majority of the multi-purpose platform concepts proposed are integrating only multiple offshore renewable energy devices (e.g. hybrid wind-wave), with only few integrating also aquaculture systems. MPPs have significant potential in economizing CAPEX and operational costs for the offshore energy and aquaculture industry by means of concerted spatial planning and sharing of infrastructur

Associations of dietary factors with gastric cancer risk: insights from NHANES 2003–2016 and mendelian randomization analyses

Background: Gastric cancer (GC) continues to be one of the leading causes of cancer-related deaths globally. Diet significantly influences the incidence and progression of GC. However, the relationship between dietary intake and GC is inconsistent.Methods: A study was conducted with adults who participated in the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2016 to investigate possible associations between 32 dietary factors and GC. To further detect potential causal relationships between these dietary factors and the risk of GC, a two-sample Mendelian randomization (MR) analysis was conducted. The primary method employed was the inverse variance weighted (IVW) analysis, and its results were further validated by four other methods.Results: Of the 35,098 participants surveyed, 20 had a history of GC. Based on the results of weighted logistic multivariate analysis, it was observed that there was a positive correlation between total fat intake [odds ratio (OR) = 1.09, 95% confidence interval (CI): (1.01–1.17), p = 0.03] and GC as well as negative association of dietary monounsaturated fatty acids (MUFAs) intake [OR = 0.83, 95% CI: (0.76–0.92), p < 0.001]. Further evaluations of the odds of GC across the quartiles of dietary MUFAs showed that the top quartile of total MUFA intake was associated with a lower likelihood of GC in three different models [model1: OR = 0.03, 95% CI: (0.00–0.25), p < 0.01; model2: OR = 0.04, 95% CI: (0.00–0.38), p = 0.01; model3: OR = 0.04, 95% CI: (0.00–0.40), p = 0.01]. For the MR analyses, genetic instruments were selected from the IEU Open GWAS project; IVW analysis showed that GC risk was not associated with MUFAs [OR = 0.82, 95% CI: (0.59–1.14), p = 0.23] or the ratio of MUFAs to total fatty acids [OR = 1.00, 95% CI: (0.75–1.35), p = 0.98]. Similar results were observed when using the other MR methods.Conclusion: The NHANES study revealed that consuming MUFAs was linked to a lower risk of GC, although the results of MR analyses do not provide evidence of a causal relationship. Additional research is therefore necessary to clarify these findings