Higher education students increasingly consume ultra-processed foods (UPFs) because they are affordable, convenient, and heavily marketed, and this pattern has been linked to adverse health outcomes. Beyond health risks, emerging evidence suggests UPFs may elicit addictive-like eating behaviors. To better understand which foods are perceived as most addictive, we applied a Best-Worst Scaling (BWS) approach-a stated-preference method-to quantify the relative perceived addictiveness of foods varying in level of processing. A cross-sectional online survey was conducted between May 10 and July 5, 2024, among 609 higher education students in the province of Liège, Belgium. Food addiction was measured using the modified Yale Food Addiction Scale version 2.0 (mYFAS 2.0). To identify which foods were perceived as most and least addictive, we used a BWS choice experiment. Participants evaluated 15 sets of 5 foods (randomly selected from 30) and, in each set, identified the food that would trigger the most and the least addictive-like problems as defined by the mYFAS 2.0 criteria. From these repeated choices, we calculated a Relative Importance Score (RIS) for each food, based on the standardized difference between its best and worst selections. The RIS provides a continuous measure of each food's perceived addictiveness relative to all others. Foods were categorized using the NOVA classification. The prevalence of food addiction was 24.0% in the sample (5.4% mild, 6.4% moderate, and 12.2% severe). BWS results showed clear differences in perceived addictiveness across foods. Ultra-processed foods consistently ranked as the most problematic, with salted potato chips (RIS = 7.662; 95% CI 7.458-7.866), chocolate brownies (RIS = 7.579; 95% CI 7.357-7.802), sugary sweets (RIS = 7.462; 95% CI 7.234-7.689), and sugary soft drinks (RIS = 7.227; 95% CI 6.971-7.482). These foods did not differ significantly from one another but were distinctly more problematic than minimally processed or processed foods. Addictive-like eating behaviors were highly prevalent among higher education students. The application of a BWS design provided a nuanced, quantitative ranking of foods based on perceived addictiveness, highlighting the predominance of ultra-processed items. These findings underscore the need for targeted public health interventions addressing the role of UPFs in problematic eating behaviors.
To achieve any goal, a configuration of cognitive processes (i.e., "task set") is needed. Navigating between goals requires switching between task sets. Such switching entails a cognitive toll ("switch cost") that is manifested as a performance cost: Switching between tasks takes longer than repeating the same task. The study of the toll of navigating between task goals has been confined to stimulus-response tasks, characterized by bare-bones features. We argue that this has prevented researchers from exploring how far task-switching can reach. Task goals (e.g., choosing a vacation destination) are not confined to stimulus-response tasks (e.g., deciding on the parity of a number) and extend to more complex decisions. We combine two lines of research, that of task-switching and that of choosing between positive options versus choosing between negative options. To the extent that choosing between positive options differs mechanistically (i.e., activates different task sets) from choosing between negative ones (as previous research suggests), switching between positive and negative choices (vs. repeating them) should induce a switch cost. In a reanalysis of the data of six studies (N = 694), we found a consistent pattern of a switch cost between positive and negative choices, supported by both a frequentist and a Bayesian meta-analysis. We further replicated the effect in two preregistered, well-powered studies (N = 241 and N = 205). We discuss the implications of our findings to different accounts of switch cost. We propose that switch cost can be used to implicitly differentiate between different concepts, as an example of where task-switching research can venture. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Adolescents and young adults (AYA) continue to experience the highest rates of kidney allograft failure despite major advances in transplantation medicine and the widespread implementation of transition programs designed to support transfer from pediatric- to adult-centered care. This editorial examines the contemporary findings reported by Marroquin et al. from the United States Renal Data System (USRDS) and places these observations within the broader context of developmental medicine, transition science, transplant immunology, and emerging adulthood. Recent USRDS data demonstrate that adolescents and young adults remain at substantially increased risk of early graft loss compared with older adult recipients, even after adjustment for donor quality, socioeconomic factors, insurance status, sensitization, and comorbidities. While nonadherence remains an important contributor, accumulating evidence suggests that excess risk may also reflect developmental, psychosocial, structural, and potentially biological vulnerabilities unique to adolescence and emerging adulthood. These include challenges related to autonomy acquisition, educational and financial instability, mental health, neurocognitive burden, changing family support structures, healthcare-system fragmentation, and age-related immunologic factors. Persistent excess graft loss among AYA kidney transplant recipients suggests that current transition frameworks may insufficiently address the developmental realities of emerging adulthood. Future models should move beyond transfer of medical responsibility alone and emphasize longitudinal developmental support that integrates pediatric and adult transplant services, psychosocial care, mental health resources, and structured autonomy development. Such approaches may improve long-term graft survival, quality of life, and healthcare sustainability.
ObjectiveFalls are a serious complication of Parkinson's disease, leading to functional decline, psychological distress, and substantial economic burden. Although multiple interventions have been proposed, structured quantitative guidance on prioritising fall-prevention strategies for clinical implementation in Parkinson's disease remains limited.DesignA multi-method study integrating a structured narrative review, expert consensus via a two-round Delphi process with 15 multidisciplinary Parkinson's disease experts, and multi-criteria decision-making using the Best-Worst Method to identify and quantitatively prioritise fall-prevention strategies for people with Parkinson's disease.SettingExpert-based consensus and decision-analysis study.ParticipantsFifteen multidisciplinary experts with clinical and research expertise in Parkinson's disease and neurorehabilitation.InterventionFall-prevention interventions identified through a structured narrative review and refined through a two-round Delphi process, followed by prioritisation using the Best-Worst Method.Main measuresRelative priority weights of intervention categories and sub-criteria derived using the Best-Worst Method based on expert judgements.ResultsThe Delphi process yielded three main criteria (exercise, dance-based interventions, and neuroscience-based interventions) and 14 sub-criteria. Best-Worst Method weighting showed that exercise had the highest priority (weight=0.49), followed by dance-based interventions (weight=0.32) and neuroscience-based interventions (weight=0.19). Within exercise, balance training and resistance strength training received the greatest weights, whereas Tai Chi and transcranial direct current stimulation received the highest expert-derived priority weights within the dance-based and neuroscience-based categories, respectively.ConclusionThis integrative framework provides an evidence-informed hierarchy of expert-derived priorities for fall-prevention interventions and may support clinical decision-making and programme design, while highlighting the need for further effectiveness and implementation research.
Chronic inflammatory skin conditions significantly impact the quality of life (QoL) of those affected. Itch is a cardinal symptom in many of these conditions, contributing decisively to the burden of disease. This cross-sectional study explored how itch and related factors mediate the relationship between disease severity and QoL impairment. Adult patients with chronic pruritus arising from psoriasis, atopic dermatitis, chronic prurigo, or chronic urticaria completed a set of validated questionnaires assessing worst and average itch intensity (worst itch intensity on the numerical rating scale [WI-NRS]/average itch intensity on the numerical rating scale [AI-NRS]), impairment of QoL with the 5-pruritus life quality (5PLQ), daily time with itch, scratching frequency, and sleep disturbance. Disease severity was evaluated using validated disease-specific scales. Spearman's rank correlation was performed to assess intercorrelations between 5PLQ scores, disease severity, and itch-related factors. A linear regression analysis investigated associations of 5PLQ with demographic and clinical factors. Mediation analyses examined whether the link between disease severity and 5PLQ scores was mediated by itch intensity, daily itch duration, scratching frequency, and sleep disturbance. A total of 522 patients (282 female, median age: 56.0 years) participated in the study. 5PLQ scores correlated weakly with disease severity (r = 0.201, p < 0.001), and strongly with itch-related factors (r = 515-0.603, p < 0.001). The linear regression analysis revealed a positive association between 5PLQ scores and female sex (β: 0.887, p = 0.003), moderate disease severity (β: 1.552, p = 0.032), scratching frequency (β: 0.370, p < 0.001), and sleep disturbance (β: 0.427, p < 0.001). Mediation analyses showed that the association between disease severity and QoL impairment was partially mediated by average itch intensity (indirect β: 0.168, p = 0.049), daily itch duration (indirect β: 0.270, p < 0.001), scratching frequency (indirect β: 0.205, p = 0.010), and sleep disturbance (indirect β: 0.235, p = 0.006). Average itch intensity, daily itch duration, scratching, and sleep disturbance mediate the relationship between disease severity and impairment of QoL. Interventions targeting these aspects of disease may improve patient outcomes. Chronic inflammatory skin conditions are highly prevalent in our society, contributing to substantial impairment of quality of life. Itch is the major symptom associated with these diseases, impacting the daily activities and sleep of those affected. We enrolled 522 patients with chronic itch arising from common inflammatory skin condition (atopic dermatitis, psoriasis, prurigo, or urticaria) at two clinics and ten dermatological offices across the states of North Rhine-Westphalia and Lower Saxony in Germany to study how itch-related factors explain the known relationship between disease severity and impairment of quality of life. Patients completed a set of questionnaires inquiring about various aspects of itch (including intensity, daily time with itch, scratching frequency, sleep disturbance), as well as impairment of quality of life. A dermatologist assessed disease severity on the basis of the skin examination. We observed significant associations between disease severity, itch-related factors, and impairment of quality of life. The amount of time patients experienced itch in a day was the factor that most strongly explained how disease severity led to an impaired quality of life. The degree of sleep disturbance was the next most important factor, followed by how often patients scratched and average itch intensity but not peak itch episodes. These results highlight that different aspects of itch play a role in reducing quality of life in patients with inflammatory skin diseases. It is therefore of great importance to assess these factors in routine care. Treatments that target these dimensions of itch may improve care and well-being in this patient population.
In intensity-modulated proton therapy (IMPT), the benefit of adding planning organ-at-risk volume (PRV)-like nominal constraints to direct robust optimization for serial organs at risk remains uncertain when target-OAR separation is minimal. Using paraspinal chordoma as a model, we evaluated whether an additional nominal canal/thecal sac (PRV-like) constraint improves OAR sparing or compromises target coverage. Ten patients with paraspinal chordomas were planned using two IMPT strategies: direct cord robust optimization alone (Cord-RO) and direct cord optimization with additional nominal canal/thecal sac constraint (Canal-RO). PTV-based helical tomotherapy (HT) was generated as a secondary benchmark. Prespecified institutional criteria were used for planning, prioritizing OAR constraints over coverage; when standard coverage goals were not achieved, GTV D98 ≥ 59 Gy(RBE) was accepted as the fallback criterion. Endpoints included target coverage, cord/canal doses, and robustness. Statistical comparisons used Wilcoxon signed-rank, Friedman, and Cochran's Q tests, two-sided, p < 0.05. All plans met plan-specific OAR constraints. Cord-RO achieved superior target coverage (median HR-CTV D98 [Gy(RBE)]: 63.05 vs. 57.38 vs. 59.46; p ≤ 0.002) and met the fallback objective (GTV D98 ≥59 Gy[RBE]) in 10/10 cases versus 4/10 and 7/10 (p=0.011) in Canal-RO and HT respectively. Robustness favored Cord-RO (median worst-case CTV D95: 90% vs 85%, p=0.018). Nominal cord D0.03cc was similar; worst-case cord D0.03cc was slightly lower with Canal-RO. When targets abut serial OARs, our results suggest that direct OAR-based robust optimization without additional PRV-like constraints improve target coverage and robustness while maintaining acceptable OAR doses. PRV constraints may be reserved for re-irradiation or when target-OAR separation is adequate.
Clear surgical margins are crucial for oral cancer (OSCC) patients' prognosis. The rising incidence of close or compromised margins (CCM) is a significant concern. This study aimed to identify preoperative and post-operative predictors of CCM in OSCC. We conducted a retrospective analysis of 1913 treatment-naïve OSCC patients treated at a single institution. Clinical, radiological, and pathological data were collected, with CCM defined as ≤ 5 mm. Statistical analyses included logistic regression and recursive partitioning models. We included 1913 patients with 197 (10.5%) exhibiting CCM. Preoperative predictors associated with the risk of CCM included the use of physical examination alone for staging, cT3-4 classification, and single-team approach for resection and reconstruction. These preoperative features, together with bone invasion and worst pattern of invasion, were significant in the post-operative setting. Effective preoperative staging and a two-team surgical approach increase the likelihood of obtaining clear surgical margins in patients with OSCC and should be pursued in the preoperative setting. Pathological features like bone invasion and worst pattern of invasion (WPOI) allow for the stratification of patients at higher risk for CCM.
Polarization-insensitive all-optical wavelength conversion (AOWC) is essential for flexible wavelength routing in reconfigurable optical networks, including potential satellite optical networks. However, conventional polarization-diversity schemes require stringent matching between parallel conversion branches, which is difficult to maintain under practical hardware constraints. Here we experimentally demonstrate a relaxed-tolerance four-wave mixing in semiconductor optical amplifiers (SOA-FWM) AOWC scheme for 10 Gbps OOK and QPSK signals using branch-resolved monitoring and calibrated equalization. For OOK, a real-valued amplitude coefficient is estimated from the aligned branch waveforms and mapped to the optical amplitude-control units (ACUs). For QPSK, a complex calibration coefficient is determined from the synchronously acquired branch records; its magnitude sets the ACU's adjustment, whereas the complete coefficient is used for offline complex-field reconstruction. At an optimized operating point of -2.58 dBm signal power, 11.61 dBm pump power, and 350 mA SOA current, the state-of-polarization (SOP) induced idler power fluctuation is reduced from 5.46 dB to 1.25 dB for OOK and from 7.67 dB to 1.49 dB for QPSK. Across four representative SOP conditions, the worst-case estimated bit-error rate (BER) of the converted OOK idler is reduced from 4.74 × 10-1 to 3.80 × 10-9. For QPSK the error vector magnitude (EVM) range is narrowed from 11.1%-41.5% to 12.0%-14.8%, while the worst-case estimated BER decreases from 7.95 × 10-3 to 7.1 × 10-12. The penalties observed at initially favorable SOPs reflect the trade-off between output-power equalization and best-case signal quality. These results provide a laboratory-scale proof of concept for relaxing branch-matching requirements in polarization-diversity SOA-FWM converters.
Iron deficiency (ID) is frequent in heart failure (HF). Among patients with HF and ID, those with impaired iron transport (IIT) (transferrin saturation (TSAT) <20%) have the worst ID phenotype. In HF, exercise limitation is mainly related to abnormality in oxygen delivery (VO2) and utilisation and/or to ventilation inefficiency. We evaluated whether it is possible to identify the leading cause of exercise limitation in patients with HF and IIT. Observational study. Retrospective study. We analysed 1043 consecutive hospitalised patients with HF (66±14 years, 49.8% females) who underwent cardiopulmonary exercise test (CPET). Associations between CPET parameters and TSAT were explored using general linear models adjusted for potential confounders (haemoglobin, left ventricle ejection fraction, age, gender, C reactive protein, serum creatinine). We observed that: (a) 413 patients with HF and IIT had worse functional capacity compared with non-IIT cases: peak VO2 (15±3 vs 16±6 mL/min/kg, p<0.0001) and ventilation/carbon dioxide relationship (VE/VCO2) slope (38±9 vs 33±8, p<0.0001); (b) VE/VCO2 values remained significantly different between IIT and non-IIT cases after adjusting for confounding variables including peak VO2; differently, peak VO2 after adjusting also for VE/VCO2 slope, resulted not different in IIT compared with non-IIT HF cases; (c) patients with both low peak VO2 (<14 mL/min/kg) and high VE/VCO2 (≥34) had a higher B-type natriuretic peptide (BNP), lower TSAT and higher MECKI (Metabolic Exercise combined with Cardiac and Kidney Index) score compared with patients with high peak VO2 and low VE/VCO2 (BNP 951±1041 vs 413±623 pg/mL (p<0.0001); TSAT 19.5%±10.5% vs 26.9%±10.2% (p<0.0001); MECKI score 14.8%±1.4% vs 1.2%±2.3% (p<0.0001). High VE/VCO2 slope is directly associated with IIT, independent of peak VO2, suggesting a pivotal role for ventilation inefficiency in exercise impairment in patients with IIT and HF. In patients with HF, the worst exercise performance is associated with low TSAT, high BNP and the highest MECKI score.
Primary intestinal diffuse large B-cell lymphoma (PI-DLBCL) is a rare subtype of non-Hodgkin lymphoma. We aimed to evaluate the prognostic significance of age in patients with PI-DLBCL. The Surveillance, Epidemiology, and End Results (SEER) database 2000-2021 was reviewed for patients ≥18 years old diagnosed with PI-DLBCL. Overall survival (OS) and cancer-specific survival (CSS) were the primary endpoints. Multivariable Cox proportional hazards models were used to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs). Patients were categorized as 18-59, 60-79, and ≥80 years old. A total of 4167 patients were included. Compared to the 18-59 age group, patients aged 60-79 had worse OS (aHR = 2.39, 95% CI: 2.11-2.70) and CSS (aHR = 1.83, 95% CI: 1.57-2.13), and those ≥80 years old had the worst survival (OS/CSS: aHR = 5.25/3.86; 95% CI: 4.56-6.03/3.26-4.58). Across all age groups, chemotherapy (OS aHR range: 0.39-0.63) and surgery (OS aHR range: 0.65-0.78) were significantly associated with reduced mortality. In the 18-59 year old group, B symptoms (OS/CSS aHR = 1.52/1.81) and being unmarried or divorced/widowed (CSS aHRs: 1.49-1.59) predicted worse outcomes. In the 60-79 year old group, male sex (OS/CSS aHR = 1.25/1.25) and Black race (CSS: aHR = 1.71) were significant risk factors. Age is a strong, independent predictor of survival in patients with PI-DLBCL. Younger patients had more diverse prognostic factors, while treatment status was the dominant determinant in older adults. These findings support age-specified treatment approaches for patients with PI-DLBCL.
Projections suggest that the number of adults living with multimorbidity will continue growing in the coming decades. Little is known, however, about the potential impact of prevention policies on multimorbidity. We applied a validated microsimulation model of multimorbidity accumulation to simulate theoretical scenarios of health improvement and inequality reduction in England over 30 years (2019-2049), compared to a baseline scenario of continuing patterns in accumulation. Four theoretical scenarios were based on Benach et al.'s typology of health policies: 1) targeted intervention on the worst-off; 2) universal policy + additional focus on the gap; 3) redistributive policy; 4) proportionate universalism; plus an idealistic fifth scenario completely removing socioeconomic inequality in transition times between states. We selected a target of 3% reduction in mortality for scenarios 1-4, based on reductions seen from tobacco control policies. Outputs compared were: difference in 2049 projected prevalence and numbers compared to baseline, total cases prevented/postponed compared to baseline, and expected years lived without multimorbidity at age 30. Our results suggest that gains in levelling socioeconomic inequalities in health would prevent/postpone multimorbidity cases and reduce relative health inequalities among those aged <65. However, this would also likely lead to increased absolute numbers living with multimorbidity overall. Our theoretical modelling suggests effective and equitable policies have potential to reduce the population-level burden of multimorbidity, postponing a substantial number of multimorbidity cases, particularly before age 65. This is, however, likely to lead to greater absolute numbers of multimorbidity cases as individuals live for longer.
The claim that Monte Carlo is the most accurate method is a case of misattributed credit. This claim is based on experience with advanced systems MC- NPX, Geant4 and EGS. These systems achieve remarkable performance because they use most accurate physics, not because they use random numbers. The latter simpli es algorithms, but contaminates the solution with random noise. Currently prevalent fast Monte Carlo algorithms retain this worst part while achieving high computing speed at the expense of the best part - accurate physics. We employ an opposite strategy. We develop a Boltzmann solver for protons that retains unchanged the physics of most ad- vanced Monte Carlo systems. We eliminate random noise, because our solution method is deterministic. Our method is also applicable to heavier ions, helium and carbon, for example. To develop a fast and accurate deterministic Boltzmann solver for protons. It calculates dose distributions and uence spectra. The spectra are needed for biolog- ical modelling. The main application is treatment planning of proton beam therapy. We solve the Boltzmann transport equation using an iterative procedure. Our algorithm accounts for Coulomb scattering and nuclear reactions. It uses the same physical models, as do the most rigorous Monte Carlo systems. Thereby it achieves the same low level of systematic errors. Our solver does not involve random sampling. The solution is not contaminated by statistical noise. This means that the overall un- certainties of our solver are lower than those realistically achievable with Monte Carlo. Furthermore, our solver is orders of magnitude faster. Its another advantage is that it calculates uence spectra. They are needed for calculation of relative biological e ec- tiveness, especially when advanced radiobiological models are used that may present a challenge for other algorithms. We have developed a novel Boltzmann equation solver, have written pro- totype software, and completed its testing for calculations in water. For 40-220 MeV protons we calculated uence spectra, depth doses, three-dimensional dose distribu- tions for narrow Gaussian beams. The CPU time was 5-11 ms for depth doses and uence spectra at multiple depths. Gaussian beam calculations took 31-78 ms. All the calculations were run on a single Intel i7 2.9 GHz CPU. Comparison of our solver with Geant4 showed good agreement for all energies and depths. For the 1%/1 mm -test the pass rate was 0.95-0.99. In this test, 1% was the di erence between our and Geant4 doses at the same point. The test included low dose regions down to 1% of the maximum dose. Results of the study provide a foundation for achieving a high comput- ing speed with uncompromised accuracy in proton treatment planning systems.
Intermediate-risk neuroblastoma patients older than 18 months, with non-MYCN amplified, International Neuroblastoma Risk Group Staging System localized, unresectable or International Neuroblastoma Staging System stage 3 tumors, and unfavorable histology have inferior outcomes compared with other intermediate-risk patients. This study aimed to identify genetic prognostic biomarkers within this rare subgroup. We conducted a large, international study including chromosomal copy number in all cases, next-generation DNA sequencing in most, and telomere maintenance mechanisms and gene expression in a subset, and correlated results with patient survival. Among 98 tumors, 9/98 (9.2%) had oncogene amplifications (CDK4/MDM2/TERT coamplification (n = 1), CDK4/MDM2 coamplification (n = 4), CDK4 (n = 2), TERT (n = 1), and MYC (n = 1)), while 63/98 (64.3%) had typical segmental chromosomal aberrations (tSCAs). Patients with tumors with oncogene amplification had the worst 5-year event-free survival (EFS; 0%; P < .0001 log-rank test) and 5-year overall survival (OS; 44.4% [95% CI, 21.4 to 92.3]; P < .01 log-rank test). Patients with tumors harboring tSCAs had inferior EFS compared with those with numerical chromosomal aberrations only (51.7% [95% CI, 40.6 to 65.8] v 93.3% [95% CI, 81.5 to 100]; P < .01). Patients with p53 pathway tumor alterations (n = 10) had worse EFS than those without (0% v 61.1% [95% CI, 50.3 to 74.3]; P < .0001, log-rank test) and worse OS (26.7% [95% CI, 8.9 to 80.3] v 80.9% [95% CI, 71.8 to 91.3]; P < .001 log-rank test). Multivariable analysis identified tSCAs as an independent prognostic variable for EFS and oncogene amplification or p53 pathway abnormalities as independent prognostic variables for EFS and OS. Oncogene amplification and/or p53 pathway abnormalities and/or typical SCAs identify patients with intermediate-risk neuroblastoma with inferior outcome for whom intensified or alternative treatments should be considered.
The 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitor rosuvastatin is a substrate of breast cancer resistance protein (BCRP). BCRP inhibition increases rosuvastatin plasma concentrations and may result in concentration-dependent muscle toxicity, at worst rhabdomyolysis. We investigated if concomitant use of rosuvastatin and drugs identified as in vitro BCRP inhibitors shows an increased number of rhabdomyolysis events based on pharmacovigilance data. From reports in the US Food and Drug Administration Adverse Event Reporting System for patients using rosuvastatin, we formed interaction (rosuvastatin with inhibitor) and non-interaction (rosuvastatin without inhibitor) groups for 71 BCRP inhibitors. These groups were further divided into subgroups with or without rhabdomyolysis. For each inhibitor, we calculated reporting odds ratio (ROR) and 95% confidence intervals (CIs). We identified 9777 individual rosuvastatin-related reports during 2013-2023, including 815 rhabdomyolysis reports. Of the 71 inhibitors, 19 had enough reports for analysis. Significantly increased RORs were obtained for the clinical BCRP inhibitors febuxostat (ROR 2.47, 95% CI 1.38-4.43) and ticagrelor (ROR 4.15, 95% CI 3.32-5.20). Amiodarone, erlotinib and rifampicin showed significantly increased RORs. Our findings support known interactions involving febuxostat and ticagrelor and suggest that also other BCRP inhibitors may increase the risk of rosuvastatin-induced rhabdomyolysis. The cholesterol‐lowering drug rosuvastatin is a substrate of breast cancer resistance protein (BCRP). BCRP inhibition increases rosuvastatin plasma concentrations, which may result in rhabdomyolysis, severe muscle toxicity. Using pharmacovigilance data, we investigated if concomitant use of rosuvastatin and BCRP inhibitors results in an increased number of rhabdomyolysis events. We identified 9777 rosuvastatin‐related reports, including 815 rhabdomyolysis reports. Of the 19 inhibitors with enough data, significantly increased reporting odds ratios were obtained for amiodarone, erlotinib, febuxostat, rifampicin and ticagrelor. Our findings support known interactions involving febuxostat and ticagrelor and suggest that other BCRP inhibitors may also increase the rosuvastatin‐induced rhabdomyolysis risk.
In commercial microgrids, for effective energy management and reliable decision-making, it is imperative to include the uncertainties in load demands as well as in the renewable energy generation. To refine the research focus, the proposed work focusses on solar PV-load forecasting in the smart grid environments. The rise in demand fluctuations necessitates an improved 10% accuracy in the forecasting models. But whenever the forecasting horizon length crosses time steps of 12, the existing models becomes unstable in predicting, with a degradation in accuracy and scalability by 8-15%. Limited research works are available to analyze the effect of rolling-horizon in managing the uncertainties. In this scenario, the proposed work employing transformer-based PV-load forecasting framework, can achieve an improved probabilistic forecasting accuracy of greater than 12%. Horizon-aware learning mechanisms are incorporated into the proposed model to accurately estimate the uncertainty. Model rolling-horizon based experiments using MATLAB environment simulation is performed on the proposed model for validation purposes. All forecasts and probability analyses illustrated in the present document are produced through simulation results by the authors using consistent simulation conditions. Three different operational conditions are considered for the evaluation with the performance metrics being the continuous ranked probability score (CRPS) and pinball loss. Improved quality of probabilistic forecasting is visible with a reduction in CRPS value by 12.6% and effective prediction interval capture is seen with internal coverage of 9.4%. The computational cost and requirements have been lowered by 18%. The architecture can scale up to about 14 different forecasting horizons, with consistent stability under different PV and load conditions. The numerical results confirm consistent improvements in the performance gains of the proposed forecasting model. Further this transformer-model based approach outperforms both gates recurrent unit baselines and long short-term memory models. There is a 12% gain improvement in average case scenarios and about 6% gain improvement in worst case scenarios, making the model suitable for applications that demand latency time of less than 1.5 s. Thus, the detailed analysis demonstrates performance gains in terms of different evaluation metrics. Thus, the overall results exhibit superior performance as against other existing modelling techniques. When scaling up the transformer-based modelling concept beyond horizon steps of 14, there is a degradation in the forecasting performance, which can be analyzed in future scope.
Scientifically grounded and clinically applicable dietary management is essential for patients with chronic diseases. However, in routine practice, nutritionists frequently lack efficient and scalable tools to deliver targeted, guideline-consistent nutritional guidance across diverse and complex clinical scenarios. To develop and conduct an exploratory expert-rating evaluation of Med-Diet, a large language model (LLM)-based agent for generating dietary plans for chronic diseases. We built Med-Diet using DeepSeek-R1, integrated clinical dietary guidelines, evaluated it on 79 real cases covering common, rare, and complex noncommunicable diseases, and compared it with four general-purpose LLMs (DeepSeek-R1, GPT-4o, GLM-Z1-32B, and Llama-3.3-70B). Fourteen clinical experts from different fields conducted blinded, multidimensional ratings of generated dietary plans. Furthermore, an exploratory comparative experiment assessed nutritionists' efficiency and output quality without and with Med-Diet assistance. Med-Diet received higher mean preference scores from expert evaluators compared to all baseline LLMs (mean score of 4.09 ± 0.64). Expert ratings suggested superior performance for Med-Diet in dimensions including accuracy, safety, nutritional balance, personalization, practicality, and overall recommendation (all p < 0.05). DeepSeek-R1 ranked second with an overall average score of 3.60 ± 0.68. This model performed the strongest in rare disease scenarios but lagged behind Med-Diet in common diseases and complex cases. GPT-4o (3.33 ± 0.66) and GLM-Z1-32B (3.35 ± 0.75) showed moderate and inconsistent performance, while Llama-3.3-70B performed the worst (3.00 ± 0.69). When nutritionists used Med-Diet to assist in dietary plan generation, the median time required decreased from 17.5 min to 13.0 min (p < 0.05). Expert scores for accuracy, personalization, practicality, and overall recommendation were higher in the Med-Diet-assisted group (adjusted p < 0.05). In this expert-rating study, Med-Diet-generated dietary plans received higher preference scores from clinical experts compared to those from general-purpose LLMs. These preliminary findings suggest that knowledge injection and framework constraints of Med-Diet may improve expert-perceived quality of AI-generated dietary plans. Med-Diet shows potential as an adjunctive tool in the dietary management of chronic diseases, but its clinical safety and effectiveness require prospective validation.
Asthma, COPD, and ACO are chronic airway disorders with distinct and overlapping features. This study aimed to compare clinical profiles, inflammatory biomarkers, and quality of life among these groups. A cross-sectional study was conducted on 168 patients (56 each with asthma, COPD, and ACO). All participants underwent clinical assessment, spirometry, St George's Respiratory Questionnaire (SGRQ), skin prick testing, and measurement of inflammatory markers, including FeNO, eosinophil count, total IgE, vitamin D, hs-CRP, and interleukins (IL-4, 5, 6, 8, 13, 17, 33). ACO patients were younger than COPD patients but older than asthma patients. Asthma patients had the highest prevalence of allergic rhinitis and skin prick positivity. FEV 1 and FEV 1 /FVC were significantly lower in COPD and ACO compared to asthma, but not different between COPD and ACO. Bronchodilator response was higher in asthma and ACO than in COPD. Asthma patients had significantly higher FeNO, eosinophil counts, and IgE levels compared to COPD, with ACO showing intermediate values. IL-4 and IL-5 were highest in asthma, IL-6 and IL-8 in COPD, with ACO again showing intermediate levels. ACO patients had the highest SGRQ scores, indicating the worst quality of life. Correlation analysis showed group-specific associations between interleukins and clinical parameters. ACO exhibits intermediate clinical and inflammatory profiles between asthma and COPD. While individual biomarkers assist in characterizing these diseases, a combination of clinical, functional, and inflammatory parameters offers better differentiation. ACO patients experience a significant symptom burden, necessitating tailored diagnostic and therapeutic approaches.
Cities worldwide face increasing threats from Extreme Climate Change, as hazards such as heatwaves, droughts, and floods pose growing risks to urban populations and infrastructure. However, global regional assessments of exposure to extreme climate hazards under worst-case scenarios remain limited. This study presents a global assessment of regional exposure to heatwaves, droughts, and floods by the end of the century using upper-quartile projections from 20 CMIP6 climate models under the SSP5-8.5 emissions scenario. Changes in these hazards were evaluated individually and in combination across thousands of cities. Results indicate heatwave frequency will increase by over 90% in many tropical and coastal urban areas, and temperature extremes up to 12.7 °C above historical values will occur in high-latitude cities. Over 120 cities are projected to exceed critical wet-bulb temperature thresholds for human health. Drought severity is projected to intensify significantly in South America, Africa, and Southeast Asia, becoming up to 3.2 times more severe than historical extremes. Flood risks, measured by river discharge, are projected to increase substantially in South America and Asia, with increases up to 85 times historical levels. Compound hazard analysis further identifies significant overlapping exposure in cities across Africa, Southeast Asia, and South America. These findings highlight substantial regional exposure to extreme climate hazards and emphasise the urgent need for targeted urban adaptation and resilience planning worldwide.
We investigated the prevalence and predictors of postoperative pain severity following breast cancer surgery in Jordan. We enrolled 230 women undergoing mastectomy or partial mastectomy for breast cancer at a cancer center in Jordan. The participants provided demographic and clinical data, and we assessed their postoperative pain within 24 hours following surgery. A total of 212 patients completed the survey. Their ages ranged from 24‒84 years (M = 55.83, SD = 13.55). Among them, 73 (34%) underwent total mastectomy, and 139 (65.6%) had breast-conserving partial mastectomy. Within 24 hours after surgery, the mean worst possible pain scores at rest and with movement were 2.26 (SD = 1.9) and 4.28 (SD = 2.3), respectively. More than 31% of participants (n = 67) reported moderate to severe pain at rest, and 128 (60.4%) experienced moderate to severe pain with movement. Multiple regression analysis showed that age (β = -0.210, p = .003), chronic opioid use (β = 0.296, p < .001), and preemptive medication (β = -0.156, p = .030) were significant predictors of pain at rest. Age (β = -0.351, p < .0001), chronic opioid use (β = 0.147, p = .011), preemptive medication (β = ‒0.156, p = .002), and nonsteroidal anti-inflammatory drugs use (β = ‒0.149, p = .018) predicted pain with movement. We conclude that postoperative pain remains a substantial concern among Jordanian breast cancer patients, particularly for those who are younger, have a history of chronic opioid use, or do not receive preemptive analgesia.
Carbon dioxide (CO2) fixation and subsequent activation represent grand challenges in materials science and chemical catalysis, with the aim of mitigating the worst impacts of global warming and associated climate change. Vibrational spectroscopy can provide essential structural insights into the binding and activation of CO2 on potential reduction catalysts. The nature of carbon dioxide adsorption on rhodium cluster anions, Rhn- (n = 3-12), has been investigated using a combination of infrared free-electron laser spectroscopy and quantum chemical calculations. A clear cluster-size dependence to the nature of the binding is observed. On the smallest clusters, Rhn- (n ≤ 4), CO2 is dissociatively adsorbed, as indicated by a carbonyl stretch at 1880 cm-1. By contrast, larger clusters, Rhn- (n ≥ 7), exhibit highly activated molecular binding, but both motifs are observed on intermediate cluster sizes (n = 5, 6). The extent of chemical activation is clearly discernible spectroscopically and arises from the propensity of CO2 to attach across Rh-Rh bridge sites, coupled with significant electron transfer from the metal cluster.