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The United Kingdom's smokefree generation policy aims to end smoking by prohibiting tobacco sales to anyone born on or after January 1, 2009. Its success may depend on how tobacco is currently accessed, especially through illicit channels. This study examined cigarette and hand-rolling tobacco purchasing trends and patterns by age, socioeconomic position, vaping status, and nation. Data came from a representative monthly cross-sectional survey in Great Britain, October 2020 to April 2025. We analyzed responses from 9966 participants (≥16y) who reported current cigarette smoking and where they had purchased cigarettes/hand-rolling tobacco in the past 6 months. Logistic regression models estimated (i) time trends and (ii) independent associations with age, socioeconomic position, vaping status, and nation, adjusted for smoking frequency and survey wave. Domestic in-person retail purchasing remained the dominant source but declined over time (from 94.0% to 86.7%). Online purchasing remained rare (2.8%) while cross-border and illicit purchasing increased (reaching 32.8% and 23.1% in 2025), with illicit purchasing more than doubling between mid-2023 and 2025. Cross-border purchasing was more common among adults aged 18-64 years and those who were more advantaged (adjusted odds ratios [aOR] = 0.35 [0.28-0.45] for least vs. most advantaged). Illicit purchasing was more common among those who were younger (eg, aOR = 5.38 [2.81-10.29] for 16-17y vs. ≥65y), less advantaged (eg, aOR = 1.48 [1.17-1.87] for least vs. most), and who also vaped (aOR = 1.26 [1.09-1.47]). While most people aged ≥16 who smoke in Great Britain continue to purchase tobacco through domestic in-person retail outlets, a substantial and growing minority-particularly those who are younger, less advantaged, and those who both smoke and vape-buy from illicit sources. The growing prevalence of illicit tobacco purchasing suggests the need for sustained investment in enforcement ahead of the implementation of the proposed smokefree generation policy. Without such efforts, reductions in legal access may be undermined by increased reliance on illegal supply routes. However, it is important to note that our figures reflect the proportion purchasing from each source among people who smoke and reported their source of purchase, not total market consumption. The increase in prevalence of illicit tobacco purchasing may represent shifts in purchasing patterns rather than a definitive increase in the overall size of the illicit market.
This paper proposes a day-ahead scheduling framework to analyze and optimize the impact of the coordinated active and reactive power management of wind turbines (WTs) and battery energy storage systems (BESSs) on the energy losses and CO2 emissions of AC microgrids (MGs). Within this framework, the BESS plays a central role by absorbing surplus renewable generation, mitigating curtailment, supporting voltage regulation, and ensuring a stable and reliable dispatch over a 24-hour horizon. A population-based genetic algorithm (PGA) is proposed as the main solution methodology, while particle swarm optimization (PSO) and the multiverse optimizer (MVO) are employed as benchmark methods for comparison. To ensure a fair assessment, all optimization techniques are implemented under the same parallel processing scheme, using the same decision-variable encoding, feasibility correction procedure, and hourly sequential AC power-flow method. The objective is to minimize network energy losses and CO2 emissions under both grid-connected and islanded operating modes. The proposed methodology is validated on 33-node and 69-node MGs, both evaluated under variable demand and wind-generation scenarios to capture the uncertainty and temporal variability associated with renewable production and load behavior. In addition, the BESS model includes charging/discharging efficiency, self-discharge effects, and battery lifetime assessment under the proposed operating scenarios, allowing a more realistic representation of storage performance. The optimization methods are evaluated over 100 independent runs using the best solution, average solution, standard deviation, and computational time as performance indicators. The results show that the proposed PGA provides the most robust and repeatable performance, while also highlighting the operational contribution of the BESS, reducing renewable curtailment, and guaranteeing compliance with all technical constraints, under deterministic baseline operation and under uncertain time-varying operating conditions in both test systems.
This paper proposes a scenario-based scheduling framework for a photovoltaic-battery energy storage (PV-BES) system participating in day-ahead energy arbitrage markets. The proposed framework accounts for uncertainties in both PV generation and electricity prices. A hybrid optimization approach is developed, combining a genetic algorithm (GA) with a linear programming (LP) model. The optimization problem is decomposed into two layers. In the first layer, the GA determines the BES commitment schedule, while in the second layer, a coupled LP is solved to obtain the shared BES dispatch schedule, held fixed across all scenarios, with the grid exchange power varying per scenario. A robustness weight is incorporated to control the trade-off between profitability and robustness. Solving the problem across multiple values of robustness weight yields a Pareto frontier, enabling operators to select a scheduling strategy aligned with their risk preference. A case study based on real PV generation and electricity price data is conducted to validate the effectiveness of the proposed framework. The results are further compared with those obtained from three benchmark approaches: deterministic MILP, a naive rule-based method, and classical robust optimization.
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The ability to understand proteins and their behaviors has been drastically improved by major successes in structure prediction and the appearance of Large Protein Language Models. The speed with which Deep Learning and Artificial Intelligence are now affecting computational protein studies is remarkable, but there are now many opportunities for further rapid progress with applications of these methods. Rapid gains are likely to come from studies using the approaches identified in this perspective. Addressing and predicting ligand-binding sites in protein structures, as well as the prediction of reliable structures of proteins interacting with other proteins, will be pivotal for fully details of structural mechanisms and dynamics. The prediction of multi-state protein ensembles, conformational transitions, dynamics of large protein complexes, and integration with experimental data is likely to happen quickly.
Lung transplantation (LTx) remains the only definitive treatment for end-stage lung disease. Throughout 2025, the global transplant community has made notable progress in addressing persistent challenges in the field, ranging from policy-level improvements in graft allocation to deeper biological insights into post-transplant complications. This review aims to synthesize the pivotal literature published in 2025 across four core areas: optimizing allocation, advancing perioperative care, defining the mechanisms of graft injury, and exploring translational frontiers. We conducted a structured literature search focused primarily on studies published in 2025 that highlight major advancements in LTx. In addition, the search was supplemented with key society guidelines, consensus statements, and relevant early 2026 publications. Selected articles were critically analyzed and categorized into clinical advancements, and basic/translational findings. In clinical research, the refinement of allocation strategies and the expansion of donor criteria, have effectively broadened access. Perioperative management has evolved with the integration of artificial intelligence to predict complications such as primary graft dysfunction (PGD) and chronic lung allograft dysfunction (CLAD). In basic and translational research, studies have dissected the molecular basis of complications. Additionally, new insights into the evolution of drug-resistant pathogens and macrophage plasticity have deepened our understanding of infection and rejection. In 2025, significant progress has been achieved in the field of LTx research. Strategies for clinical donor allocation and perioperative management, along with the understanding of molecular mechanisms underlying complications, have also been greatly improved. These advancements are essential to further optimize outcomes and address the complex challenges in LTx.
The FIFA World Cup™ 2026 in Mexico will be a major public health challenge worldwide. Large gatherings can facilitate the spread of diseases, raise the number of cardiovascular emergencies caused by stress, and require careful monitoring of vaccine-preventable illnesses, particularly given ongoing concerns about measles and pertussis. This editorial article reviews lessons learned from past events and highlights the need to improve food safety, mental health support, and active disease surveillance. The healthcare system's success will depend on how well it can respond and plan to manage the risks that come with people traveling from around the world. La Copa Mundial FIFA™ 2026 en México será un reto importante para la salud pública a nivel mundial. Los eventos masivos pueden ser favorecedores de la propagación de enfermedades, aumentar las emergencias cardiovasculares por el estrés, así como las enfermedades prevenibles por vacunación, principalmente sarampión y tos ferina, por el contexto epidemiológico actual. En este manuscrito se revisan las lecciones aprendidas en eventos previos y se destaca la importancia de reforzar la seguridad alimentaria, la atención a la salud mental y la vigilancia epidemiológica activa. El éxito del sistema de salud dependerá de su capacidad de respuesta y de una buena planeación para controlar los riesgos asociados con la llegada de personas de todo el mundo.
Objectives. To evaluate worker well-being in the US governmental public health workforce using data from the 2024 Public Health Workforce Interests and Needs Survey (PH WINS). Methods. We analyzed data from 48 949 respondents (weighted n = 204 823) working in 48 state health agencies and 1178 local health departments. Worker well-being was measured using the validated Thriving From Work Questionnaire. We conducted weighted analyses examining group differences across demographic, occupational, and organizational characteristics. Results. Mean thriving scores were 35.6 (SD = 7.4) out of 48, indicating moderate levels of work-related well-being. Older workers (aged ≥ 55 years) and those with 0 to 5 years tenure reported highest thriving; midcareer workers (6-15 years) reported lowest levels. Fully remote workers reported highest thriving. Supervisors and managers reported lower thriving than nonsupervisors and executives. Small and medium-sized local health departments showed higher thriving than large departments and state agencies. Conclusions. This first national assessment of public health workforce thriving identifies critical intervention priorities: midcareer support, workplace flexibility, fairness and inclusion, and enhanced supervisor support. Though effect sizes were small, these patterns have meaningful implications for workforce retention across more than 200 000 employees. (Am J Public Health. Published online ahead of print July 16, 2026:e1-e12. https://doi.org/10.2105/AJPH.2026.308602).
Since its inception at the end of the last century, 2D-IR spectroscopy has undergone continuous development into an established method for studying the structure, dynamics and intermolecular interactions of biomolecules. Thanks to parallel advances in lasers and related technology, 2D-IR data sets can now be acquired in minutes, using minimal sample quantities and under physiologically relevant conditions. This progress has opened the door for 2D-IR spectroscopy to play a role as an analytical tool, making measurements that characterize samples and inform decisions in arenas ranging from drug design to biomedical diagnostics. Here, we briefly review the pioneering developments that have brought about this scenario before discussing the current state of the art in analytical applications of 2D-IR spectroscopy. We consider the implementation of 2D-IR spectroscopy to measure label free protein structure, biomolecular interactions and the use of 2D-IR to interrogate complex mixtures and biological tissues. We include strategies that have extended the reach of 2D-IR spectroscopy through advances in measurement sensitivity and data quality and highlight the potential impact that emerging methods such as machine learning could have on the development of 2D-IR. Finally, we look ahead to the challenges and opportunities facing 2D-IR on its path toward a robust and widely used bioanalytical tool.
Objectives. To describe how community engagement combined with respondent-driven sampling (RDS) enabled timely documentation of the mental health and socioeconomic impacts of COVID-19 on California's Native Hawaiian and Pacific Islander (NHPI) adult population. Methods. The California Pacific Islander Well-Being and COVID-19 Economic Survey (CAPIWAVES) was a collaboration between NHPI community-based organizations and academic researchers who sampled 929 NHPI adults in California from January to May 2024. The initial respondents were composed of a convenience sample of 58 CHamoru, Fijian, Marshallese, Native Hawaiian, Sāmoan, and Tongan respondents in Northern, Central, and Southern California, who referred up to 4 others. Results. Compared with the American Community Survey, CAPIWAVES RDS estimates differed. We reported initial data findings to NHPI community members in June 2024 in an online webinar. In April 2025, we released a report with the analyzed CAPIWAVES data, with community-generated recommendations for policy, programming, and research. Conclusions. Although data were not population-representative, community-engaged RDS was an efficient method for collecting and disseminating needed data for minoritized populations. (Am J Public Health. Published online ahead of print July 16, 2026:e1-e12. https://doi.org/10.2105/AJPH.2026.308517).
Pharmaceutical manufacturing is changing rapidly as new therapeutic modalities, advanced manufacturing approaches, modern analytical tools, and novel drug-delivery technologies continue to emerge. While the scientific and technical potential of these innovations is clear, their adoption has often lagged due to regulatory challenges. Differences in regulatory expectations across regions, lengthy review timelines, and limited opportunities for coordinated engagement can slow or discourage the implementation of meaningful chemistry, manufacturing, and controls (CMC) advances. This review considers these barriers from an industry perspective, drawing attention to how cautious regulatory paradigms, fragmented guidance, and market-specific interpretations can reduce the incentive to introduce innovation, even when patient benefit is evident. Recent surveys, regulatory initiatives, and collaborative experiences suggest that progress is being made, particularly through innovation programs and reliance-based mechanisms; however, gaps remain in achieving consistent alignment and efficient lifecycle management. Looking ahead, greater use of cloud-based platforms to support real-time information sharing and collaborative regulatory review offers a practical path forward. Such approaches can improve transparency, reduce duplicate interactions, and encourage convergence without compromising regulatory rigor. By aligning regulatory practices more closely with scientific progress and the demands of today's advanced manufacturing, digital, and other 21st-century technologies, these collaborative models have the potential to accelerate innovation, support continuous improvement, and enable more timely global access to medicines.
Aiming at the problems of single participation mode of existing hydrogen production and refueling integrated stations (HPRSs) in the electricity market, and the lack of multi-station aggregated trading mechanism, this paper proposes a market trading method for HPRS operator under hydrogen sharing mechanism. First, a trading mechanism is constructed for the HPRS operator to aggregate multiple HPRSs to participate in the day-ahead joint electricity energy and peak-regulation market. Second, based on the hydrogen sharing mechanism, a trading model for the HPRS operator and a day-ahead joint electricity energy-peak-regulation market clearing model are established. Then, a trading strategy solution method based on Differentially Private Consensus Alternating Direction Method of Multipliers (DP-C-ADMM) is proposed to ensure trading privacy and computational efficiency. Finally, simulations based on an improved IEEE 141-node distribution network verify that the proposed method can effectively enhance the operational revenue and peak-regulation potential of HPRSs, providing decision support for aggregated participation of HPRSs in electricity market trading.
Postoperative delirium (POD) affects 20-60% of elderly orthopedic surgery patients, yet most cases go unrecognized-over 70% in some reports. This gap between what we know and what we do in daily practice is frustrating, but also hopeful: because POD is largely preventable. Early identification and evidence-based prevention remain urgent priorities. This review brings together recent insights into why POD happens and what bedside nurses and surgical teams can actually do about it. We focus on actionable, non-pharmacological strategies that work in real-world settings. We searched PubMed and Google Scholar for peer-reviewed studies published between 2022 and 2025, focusing on POD mechanisms, risk prediction, and non-drug interventions. Given the heterogeneity of study designs and outcomes, we used a narrative synthesis approach rather than formal meta-analysis. Twenty high-quality articles were selected for critical appraisal. POD arises from a tangled web of causes, with neuroinflammation and neurotransmitter imbalance at its core. Newer risk tools can now flag high-risk patients before surgery. The eCASH bundle-Early mobilization, Cognitive stimulation, Adequate sleep, Social support, and Homelike environment-consistently cuts POD rates. Multidisciplinary teamwork works far better than any single discipline going it alone. And while implementation barriers like understaffing and knowledge gaps are real, structured training and simple protocols can overcome them. A three-part strategy-risk-stratified screening, eCASH bundled interventions, and multidisciplinary collaboration-offers the best shot at reducing POD in elderly orthopedic patients. Looking ahead, biomarkers, remote monitoring, and implementation science will take us further.