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Impact of hysterectomy on opioid use in patients with adenomyosis: A nationwide register study

Introduction Dysmenorrhea and heavy menstrual bleeding are the most common symptoms in adenomyosis, in addition to infertility and chronic pelvic pain. Hysterectomy is a common treatment for adenomyosis symptoms with curative effect on heavy menstrual bleeding but with less studied effects on pain reduction. Material and methods This is a nationwide retrospective register-based cohort study including all hysterectomized patients with pathology-verified adenomyosis between 1 January 2012 and 31 December 2015 with a long-term follow-up three years pre- and three years postoperatively. Two national registers were linked in order to describe the primary outcome of proportion with use of opioids among hysterectomized patients with and without adenomyosis pre- and postoperatively. Logistic and multinomial regression models were used. Results A total of 2,228 (15%) patients had pathology-verified adenomyosis. Overall opioid use was 18.6% and 21.1% three years before and three years after surgery, respectively. Results showed a significantly increased risk of opioid use three years after hysterectomy in patients with preoperative use of opioids and antidepressants (adjusted Odds Ratio (aOR) 5.7, 95% Confidence Interval (CI) 4.5–7.2 and aOR 1.4, 95% CI 1.1–1.8). The risk of needing long-term opioids was higher among patients with smaller uteri (<300g, aOR 2.8, 95% CI 1.7–4.7) compared to women with uterine sizes ≥600g. Conclusions Hysterectomy does not reduce opioid use among adenomyosis patients in long-term follow-up, although the subjective reduction of pain was not investigated in this study. Women with preoperative use of opioids/antidepressants and uterine size <300g are at increased risk for chronic opioid use.

Shell colour luminance of Cuban painted snails, Polymita picta and Polymita muscarum (Gastropoda: Cepolidae)

Climate change is a global environmental threat, directly affecting biodiversity. Terrestrial gastropods are particularly susceptible to alterations in temperature and humidity and have develop morph-physiological and behavioural adaptations in this regard. Shell colour polymorphism and its potential implication for thermoresistance constitute an unexplored field in Neotropical land snails. The variation in shell colour luminance is characterized in the threatened endemic Eastern Cuban tree snails Polymita picta and Polymita muscarum using digital tools; being able to discriminate shell luminance between colour morphs for both species, under different image-taking conditions. For P. muscarum, the albino morph presented the highest luminance values (152.7 ± 0.4); while the lowest values correspond to the brown morph with dark bands (112.9 ± 0.8). Otherwise, for P. picta, the morphs showing the highest luminance were yellow with a pink sutural band (112.8 ± 7.1) and pale yellow (112.6 ± 10.3) and the lowest luminance corresponded to the black morph (44.5 ± 1.2). The presence of dark bands decreased the luminance values regardless of their position in the shell, the morph and the species analysed. In general, the shells of P. muscarum have higher luminance than those of P. picta. Luminance variations demonstrate the ’indiscrete’ nature of this trait and highlight the complex interactions between evolutionary mechanisms and shell color polymorphism in Polymita. This supports the hypothesis that colour has adaptive value for thermoregulation, encompassing not only the background colour but also the coloration of the bands. The differences in the shell luminance in both species suggest a correlation with the geographical distribution and corresponding habitats. Based on our findings, yellowish morphs will be more resistant to future climatic conditions in their respective habitats on the island.

Similarities and differences in waste composition over time and space determined by multivariate distance analyses

The composition of solid waste affects technology choices and policy decisions regarding its management. Analyses of waste composition studies are almost always made on a parameter by parameter basis. Multivariate distance techniques can create wholisitic determinations of similarities and differences and were applied here to enhance a series of waste composition comparisons. A set of New York City residential waste composition studies conducted in 1990, 2004, 2013, and 2017 were compared to EPA data and to 88 studies conducted in other US jurisdictions from 1987–2021. The total residential waste stream and the disposed wastes in NYC were found to be similar in nature, and very different from the composition of wastes set out for recycling. Disposed wastes were more similar across the five NYC boroughs in a single year than in one borough over the 28-year time period, but recyclables were more similar across 14 years than across the boroughs in a single year. Food and plastics percentages in total and disposed waste streams increased over time, and paper percentages fell. The food disposal rate in NYC over time increased much less than EPA data show. The rate of plastics and paper disposal in NYC decreased. NYC data largely conformed to trends from the 88 other waste composition studies and did not generally agree with EPA data sets. The use of novel-to-waste studies multivariate distance analyses offers the promise of simplifying the identification of overall similarities and differences across waste studies, and so improving management and planning for solid waste.

The impact of reduced skeletal muscle mass at stroke onset on 3-month functional outcomes in acute ischemic stroke patients

Introduction Sarcopenia, characterized by reduced skeletal muscle mass (RMM), is increasingly recognized as a significant factor influencing outcomes in various health conditions, including stroke. Although most studies focus on sarcopenia developing during stroke rehabilitation, the impact of sarcopenia present at the onset of acute ischemic stroke remains underexplored. This study aims to evaluate the effect of RMM at stroke onset on 3-month functional outcomes in acute ischemic stroke patients. Materials and methods We prospectively enrolled acute ischemic stroke patients admitted between May 2019 and December 2019. Muscle mass was accessed early during hospitalization using whole-body dual-energy X-ray absorptiometry (DXA), and patients were categorized into RMM and normal muscle mass (NMM) groups based on the Asian Working Group for Sarcopenia (AWGS) criteria. Functional outcomes at 3 months were assessed using the modified Rankin Scale (mRS), with unfavorable outcomes defined as mRS scores 2–5. Multivariable logistic regression and SHAP (Shapley Additive exPlanations) analyses were used to evaluate the independent impact of RMM on 3-months functional outcomes. Results A total of 99 patients were analyzed. The RMM group had a significantly higher prevalence of unfavorable outcomes at 3 months compared to the NMM group (p < 0.001). Patients with RMM were older and presented with more severe strokes. Multivariable analysis confirmed RMM as an independent predictor of unfavorable outcomes (adjusted OR: 8.07, 95% CI: 1.603–40.66, p = 0.011), even after adjusting for age and initial stroke severity. SHAP analysis ranked RMM as the second most influential predictor of unfavorable outcomes, following NIHSS on admission. These findings indicate that RMM not only worsens initial stroke severity but also independently hinders post-stroke recovery. Conclusions Reduced muscle mass at the onset of acute ischemic stroke is a significant, independent predictor of unfavorable outcomes at 3 months. In addition to its impact on recovery, RMM is linked to older age and more severe strokes, worsening prognosis. Maintaining muscle mass is also crucial for stroke prevention, as it supports cardiovascular health and resilience. Early identification and intervention for sarcopenia can improve recovery and reduce future stroke risk.

Estimating the burden of underdiagnosis within England: A modelling study of linked primary care data

Introduction Undiagnosed chronic disease has serious health consequences, and variation in rates of underdiagnosis between populations can contribute to health inequalities. We aimed to estimate the level of undiagnosed disease of 11 common conditions and its variation across sociodemographic characteristics and regions in England. Methods We used linked primary care, hospital and mortality data on approximately 1.3 million patients registered at a GP practice for more than one year from 01/04/2008–31/03/2020 from Clinical Practice Research Datalink. We created a dynamic state model with six states based on the diagnosis and mortality of 11 conditions: coronary heart disease (CHD), stroke, hypertension, chronic obstructive pulmonary disease, type 2 diabetes, dementia, breast cancer, prostate cancer, lung cancer, colorectal cancer, and depression/anxiety. Undiagnosed disease was conceptualised as those who died with a condition but were not previously diagnosed. This was combined with observed data on the incidence of diagnosis, the case fatality rate in the diagnosed, and an assumption about how that rate varies with diagnosis to estimate the number of undiagnosed disease cases over the total number of disease cases (underdiagnosis) in each population group. We estimated underdiagnosis by year, sex, 10-year age group, relative deprivation, and administrative region. We then applied small-area estimation techniques to derive underdiagnosis estimates for health planning areas (CCGs). Results Levels of underdiagnosis varied between 16% for stroke and 69% for prostate cancer in 2018. For all diseases, the level of underdiagnosis declined over time. Underdiagnosis was not consistently concentrated in areas with high deprivation. For depression/anxiety and stroke, underdiagnosis was estimated to be higher in less deprived CCGs, whilst for CHD and T2DM, it was estimated to be higher in more deprived CCGs, with no apparent relationships for other conditions. We found no uniform spatial patterns of underdiagnosis across all diseases, and the relationship between age, deprivation and the probability of being undiagnosed varied greatly between diseases. Discussion Our findings suggest that underdiagnosis is not consistently concentrated in areas with high deprivation, nor is there a uniform spatial underdiagnosis pattern across diseases. This novel method for estimating the burden of underdiagnosis within England depends on the quality of routinely collected data, but it suggests that more research is needed to understand the key drivers of underdiagnosis.

Associations between the Global Diet Quality Score and risk of type 2 diabetes: Tehran lipid and glucose study

Background Previous studies reported that focusing on healthy lifestyle, especially high diet quality is necessary for preventing type 2 diabetes (T2D). This study investigated the association between the innovative index, the Global Diet Quality Score (GDQS), and the risk of Type 2 Diabetes incidence. Methods In this secondary analysis, we included elective adult participants (n = 5948) from the third and fourth survey of the Tehran Lipid and Glucose Study. Participants checked out until the sixth phase with an average follow-up of 6.65 years. Expert nutritionists collected dietary data using a valid and reliable semi-quantitative food frequency questionnaire. The GDQS were calculated, including healthy and unhealthy food group scores. Biochemical and anthropometric characteristics were assessed during the first and follow-up surveys. Multivariable Cox proportional hazards regression models were used to estimate the progression of T2D in association with the GDQS. Results This study was implemented on 2,688 men and 3,260 women, respectively with the mean (SD) age of 41.5(14.1) and 39.3(13.02) years. A total of 524 subjects were found to have had T2D incidence. The healthy component of GDQS was conversely associated with T2D incidence [HR: 1, 0.91 (0.84–0.98), 0.91 (0.84–0.98), 0.84 (0.77–0.92) P trend = <0.001] in an adjusted model. The unhealthy component of GDQS was conversely associated with T2D incidence in an adjusted model [HR: 1, 0.86 (0.80–0.92), 0.93 (0.86–1.01), 0.89 (0.81–0.98) P trend = 0.009]. Conclusion The results of this study suggested that higher adherence to the healthy component of GDQS and lower intake of the unhealthy component decreased the risk of T2D incidence.

Active Disturbance Rejection Control for an automotive suspension system based on parameter tuning using a fuzzy technique

Road surface roughness is the cause of vehicle vibration, which is considered a system disturbance. Previous studies on suspension system control often ignore the influence of disturbances while designing the controller, leading to system performance degradation under severe vibration conditions. In this work, we propose a control method to improve active suspension performance that reduces vehicle vibration by eliminating the influence of road disturbances. The proposed method is formed based on the combination of an Active Disturbance Rejection Control (ADRC) technique with control coefficients tuned by a dynamic fuzzy technique formed based on special membership functions called Active Disturbance Rejection Control Based on Fuzzy (ADRCBF). An Extended State Observer (ESO) estimates state variables and disturbances. The performance of the proposed controller is evaluated through the numerical simulation process with three different cases. According to the calculation results, the acceleration and displacement of the sprung mass are significantly reduced when the suspension system is controlled by the proposed technique, compared with the passive suspension system and the active suspension system controlled by a Proportional-Integral-Derivative (PID) technique. In addition, the suspension travel follows the road disturbance with a small error. The error estimated by the ESO does not exceed 3.5% (for sinusoidal and random excitation). In general, system adaptation is ensured under many investigated conditions based on tuning the controller parameters by the soft computing method.

Optimal Synergy between Azulenes and Acenes in Azuacenes with 6-7-5 Ring Topology

Effect of fatigability on sprint time performance and force-velocity profile according to maturity status in young rugby players

Little is known about the influence of fatigue in repeated overground sprinting on force-velocity properties in children and adolescents, while this ability to repeat sprints is important for future progress in rugby union. Sprint time decline is commonly used to assess fatigability. However, it does not provide data on biomechanical aspects of sprint performance such as maximal power, force, and velocity production. As sprint time performance and force-velocity properties do not linearly change during adolescence, considering maturity status is important. This study aimed to assess the effect of fatigue on sprint time performance fatigability, force-velocity parameters, and mechanical effectiveness according to maturity status. A group of fifteen boys (12.5 ± 0.5 years) children and a group of seventeen boys (15.1 ± 0.6 years) adolescent rugby players completed seven blocks, consisting of a 30-meter sprint followed by five minutes of high-intensity exercise with one minute of passive recovery. The force-velocity parameters were calculated at each sprint, and performance decrement was assessed using a fatigue index. A main effect of block repetition was found for maximal power output, maximal force, maximal velocity, 30-meter sprint time, fatigue index and mechanical effectiveness parameters with large effect sizes (p <0.001; ηp2 = 0.19 to 0.47) and without a main effect of maturity status (p = 0.37 to 0.99; ηp2 = 0.00 to 0.05). This could be explained by the modalities (duration, intensity, recovery) of the protocol and the training level of the adolescent group. For both groups, the decrease in maximal power output was due more to a reduction in maximal velocity than force, and mechanical effectiveness was negatively impacted. Coaches could prioritize the training of horizontal force at high velocity under fatigue conditions, as this ability tends to be the most affected. They could also incorporate training on mechanical effectiveness as this is a determinant in team sports.

Summon a demon and bind it: A grounded theory of LLM red teaming

Engaging in the deliberate generation of abnormal outputs from Large Language Models (LLMs) by attacking them is a novel human activity. This paper presents a thorough exposition of how and why people perform such attacks, defining LLM red-teaming based on extensive and diverse evidence. Using a formal qualitative methodology, we interviewed dozens of practitioners from a broad range of backgrounds, all contributors to this novel work of attempting to cause LLMs to fail. We focused on the research questions of defining LLM red teaming, uncovering the motivations and goals for performing the activity, and characterizing the strategies people use when attacking LLMs. Based on the data, LLM red teaming is defined as a limit-seeking, non-malicious, manual activity, which depends highly on a team-effort and an alchemist mindset. It is highly intrinsically motivated by curiosity, fun, and to some degrees by concerns for various harms of deploying LLMs. We identify a taxonomy of 12 strategies and 35 different techniques of attacking LLMs. These findings are presented as a comprehensive grounded theory of how and why people attack large language models: LLM red teaming.

Ni-Catalyzed Regioselective Alkylarylation of Unactivated Alkenes in Amines Enabled by Cooperative Ligand Effects of Nitriles and Electron-Deficient Alkenes

Dynamics and triggers of misinformation on vaccines

The Covid-19 pandemic has sparked renewed attention to the risks of online misinformation, emphasizing its impact on individuals’ quality of life through the spread of health-related myths and misconceptions. In this study, we analyze 6 years (2016–2021) of Italian vaccine debate across diverse social media platforms (Facebook, Instagram, Twitter, YouTube), encompassing all major news sources–both questionable and reliable. We first use the symbolic transfer entropy analysis of news production time-series to dynamically determine which category of sources, questionable or reliable, causally drives the agenda on vaccines. Then, leveraging deep learning models capable to accurately classify vaccine-related content based on the conveyed stance and discussed topic, respectively, we evaluate the focus on various topics by news sources promoting opposing views and compare the resulting user engagement. Our study uncovers misinformation not as a parasite of the news ecosystem that merely opposes the perspectives offered by mainstream media, but as an autonomous force capable of even overwhelming the production of vaccine-related content from the latter. While the pervasiveness of misinformation is evident in the significantly higher engagement of questionable sources compared to reliable ones (up to 11 times higher in median value), our findings underscore the need for consistent and thorough pro-vax coverage to counter this imbalance. This is especially important for sensitive topics, where the risk of misinformation spreading and potentially exacerbating negative attitudes toward vaccines is higher. While reliable sources have successfully promoted vaccine efficacy, reducing anti-vax impact, gaps in pro-vax coverage on vaccine safety led to the highest engagement with anti-vax content.

Vestibular stimulation and space-time interaction affect the perception of time during whole-body rotations

Among the factors, such as emotions, that distort time perception, vestibular stimulation causes a contraction in subjective time. Unlike emotions, the intensity of vestibular stimulation can be easily and precisely modified, making it possible to study the quantitative relationship between stimulation and its effect on time perception. We hypothesized that the contraction of subjective time would increase with the vestibular stimulation magnitude. In the first experiment, participants sat on a rotatory chair and reproduced time intervals between the start and the end of whole-body passive rotations (40° or 80°; dynamic condition) or between two consecutive low-amplitude shakes (static condition). We also assessed reaction time under the same conditions to evaluate the attentional effect of the stimuli. As expected, duration reproduction in the 40° rotation was shorter than that observed in the static condition, but this effect was partly reversed for 80° rotations. In other words, vestibular stimulation shortens the perceived time interval, but this effect weakens with stronger stimulation. Attentional changes do not explain this unexpected result, as reaction time did not change between conditions. We hypothesized that the space-time interaction (i.e., spatially larger stimuli are perceived as lasting longer) could explain these findings. To assess this, in a second experiment participants were subjected to the same protocol but with three rotation amplitudes (30°, 60°, and 120°). The duration reproductions were systematically shorter for the lower amplitudes than for the higher amplitudes; so much so that for the highest amplitude (120°), the duration reproduction increased so that it did not differ from the static condition. Overall, the experiments show that whole-body rotation can contract subjective time, probably at the rather low level of the interval timing network, or dilate it, probably at a higher level via the space-time interaction.

Energy-exergy and environ-economic (4E) analysis of heat storage-based single-slope solar stills integrated with solar air heater

The energy-exergy and environ-economic (4E) analysis was conducted on a solar still with and without a hybrid thermal energy storage system (TESS) and a solar air heater. The proposed solar still was modified by integrating a rectangular aluminium box filled with paraffin wax and black gravel as the TESS and coupled with a solar air heater. Paraffin wax was selected due to its widespread availability and proven effectiveness in accelerating desalination, improving process uniformity, and maintaining optimal temperature levels. Throughout the experiments, meticulous data on mass loss, air velocity, and temperature were recorded for both conditions. The daily energy efficiency varies from 40.80% to 31.72%, showing a reduction rate with increased water depth. Estimates were made on the average exergy efficiency, losses, outflow, and inflow for the solar still. These were done for both setups. The analysis revealed that CO2 mitigation and credit were more favorable with the TESS. Furthermore, the Energy Payback Time (EPBT) for the hybrid heat storage-based single-slope solar still coupled with a solar air heater is 1.87 years. On the other hand, EPBT values for the hybrid heat storage single-slope solar still and the conventional single-slope solar still were 1.65 years and 0.95 years, respectively. Integrating a thermal energy storage system and solar air heater significantly improved the performance and sustainability of the solar still for desalination, making it a more efficient and environmentally friendly option for freshwater production.

Sharing images of children on social media: British motherhood influencers and the privacy paradox

This study examines the extent to which popular British motherhood influencers infringe on their children’s privacy by posting images of them online. We conducted a content analysis of 5,253 Instagram posts from ten UK-based influencers, supplemented by self-reported data from these influencers. This represents the first comprehensive analysis of actual sharing practices in the British motherhood influencer industry, linking observed behavior with self-reported perceptions. Children appeared in over 75% of the posts (3,917), though the proportion of posts containing embarrassing, intimate, or revealing content was relatively low (11.5%). Notably, sponsorships and product advertisements were present in 46.4% of posts featuring children, indicating that children’s images are frequently used for financial gain. Despite this, post popularity did not vary based on the inclusion of children, as posts featuring children did not receive more likes than those without. Influencers reported strong trust in online safety on Instagram, and reported indifference or willingness to sharenting suggesting that sharing images of their children may be a deliberate strategy rather than an accidental act. Half of the influencers did not accurately estimate their past sharenting behavior. This study extends the existing body of knowledge on sharenting behaviour and the privacy paradox by establishing a foundation of parents’ real-world posting habits and connecting them to their beliefs about publicly sharing their children’s images in the UK context. The findings do not strongly support the privacy paradox in this sample.

Combining Distibene, Diazoolefins, and Visible Light: Synthesis and Reactivity of Inorganic Rings

Integrating life cycle assessment into supply chain optimization

Integrating Supply Chain Optimization (SCO) with Life Cycle Assessment (LCA) is essential for creating supply chains that are both economically efficient and environmentally sustainable. While SCO focuses on optimizing network structures and decisions related to product and service delivery, LCA systematically assesses the environmental impacts across the entire supply chain. The existing literature treats SCO and LCA as separate, sequential steps, often leading to inconsistencies in scope and challenges in data transfer and rescaling. Our research presents a novel Supply Chain Life Cycle Optimization (SCLCO) model that integrates SCO and LCA. Our SCLCO model is based on LCA data structures, incorporates multi-time period, closed-loop SCO decisions (e.g. reverse chain management, inventory control, network design), and is capable of considering the three pillars of sustainability: environmental, economic, and social. It includes harmonizing principles, terminology, and notation, thereby bridging the gap between the SCO and LCA communities through a generalized formulation. Computational experiments on a selected SCO model from Operations Research literature validate the SCLCO and demonstrate its effectiveness in providing valuable insights to both SCO and LCA practitioners and researchers. The results emphasize that the simultaneous execution of SCO and LCA in SCLCO minimizes the risk of overlooking decision impacts and facilitates data transfer from existing LCA databases.

Short-term impact of low air pressure on plants’ functional traits

Lower atmospheric pressure affects biologically relevant physical parameters such as gas partial pressure and concentration, leading to increased water vapor diffusivity and greater soil water content loss through evapotranspiration. This might impact plant photosynthetic activity, resource allocation, water relations, and growth. However, the direct impact of low air pressure on plant physiology is largely unknown. This study examined the effects of low air pressure, alone and combined with two water inputs, on different functional traits of three plant species transplanted from montane grasslands at 1,500 m a.s.l. during the first four weeks of their early phenological stage: Trifolium pratense, Hieracium pilosella, and Brachypodium rupestre. Using the terraXcube Ecotron facility which can simulate different climatic conditions, we isolated the effect of air pressure from those of other, related environmental factors (temperature, humidity, and solar radiation) by simulating three different elevations with corresponding air pressures: 1,500 m a.s.l. (85 kPa, control scenario), 2,500 m a.s.l. (75 kPa), and 4,000 m a.s.l. (62 kPa) and we used two different water regimes to observe the combined effect of low air pressure and the impact of varying water inputs on plants. In T. pratense and H. pilosella, we observed an increase in stomatal conductance but a reduction in aboveground biomass at the lowest pressure compared to the control scenario after four weeks of incubation. Contrastingly, B. rupestre showed an interactive effect of air pressure and water treatment on chlorophyll and biomass nitrogen content, which were reduced under higher soil water conditions at 85kPa. This study serves as an initial step in isolating the specific impact of air pressure on plant physiology, demonstrating the potential of the facility for future research. The mixed response patterns across species highlight that atmospheric pressure could be a driving factor to consider when assessing plant responses along elevational gradient.

Kynurenines and aerobic exercise capacity in chronic kidney disease: A cross-sectional and longitudinal study

Background The causes of reduced aerobic exercise capacity (ExCap) in chronic kidney disease (CKD) are multifactorial, possibly involving the accumulation of tryptophan (TRP) metabolites such as kynurenine (KYN) and kynurenic acid (KYNA), known as kynurenines. Their relationship to ExCap has yet to be studied in CKD. We hypothesised that aerobic ExCap would be negatively associated with plasma levels of TRP, KYN and KYNA in CKD. Methods We included 102 patients with non-dialysis CKD stages 2–5 (CKD 2–3, n = 54; CKD 4–5, n = 48) and 54 healthy controls, age- and sex-matched with the CKD 2–3 group. ExCap was assessed as peak workload during a maximal cycle ergometer test. Plasma KYN, KYNA and TRP were determined by high-performance liquid chromatography. Kidney function was evaluated by glomerular filtration rate (GFR) and estimated GFR. The CKD 2–3 group and healthy controls repeated tests after five years. The association between TRP, KYN, KYNA and ExCap in CKD was assessed using a generalised linear model. Results At baseline, there were significant differences between all groups in aerobic ExCap, KYN, KYNA, TRP and KYN/TRP. KYNA increased in CKD 2–3 during the follow-up period. In CKD 2–5, KYNA, KYN/TRP and KYNA/KYN were all significantly negatively associated with ExCap at baseline, whereas KYN and TRP were not. Kynurenines were significantly correlated with GFR (p < 0.001 for all). Including GFR in the statistical model, no kynurenines were independently associated with ExCap at baseline. At follow-up, the increase in KYN and KYN/TRP was related to a decrease in ExCap in CKD 2–3. After adjusting for GFR, increase in KYN/TRP remained an independent significant predictor of a decline in ExCap in CKD 2–3. Conclusion Aerobic ExCap was inversely associated with plasma levels of kynurenines in CKD at baseline and follow-up.

Modeling of chemo-radiotherapy targeting growing vascular tumors: A continuum-level approach

The aim of this study is to demonstrate the enhanced efficiency of combined therapeutic strategies for the treatment of growing tumors, based on computational experiments of a continuous-level modeling framework. In particular, the tumor growth is simulated within a host tissue and treated as a multiphase fluid, with each cellular species considered as a distinct fluid phase. Our model integrates the impact of chemical species on tumor dynamics, and we model –through reaction-diffusion equations– the spatio-temporal evolution of oxygen, vascular endothelial growth factor (VEGF) and chemotherapeutic agents. Simulations of a growing tumor exposed to external radiation showcase the rapid impact of radiotherapy on tumor suppression, however this effect diminishes over time. To enhance the therapeutic efficiency of radiotherapy, we investigate the combination of external radiation with the anti-VEGF drug bevacizumab and the cytotoxic drug docetaxel. Our simulations demonstrate that this synergistic approach integrates the immediate effectiveness of radiation therapy with the enduring tumor-suppressive capabilities of chemotherapy.