Efficient traffic management requires an understanding of mobility patterns in the road network, where one important component is route choice. This study aims to analyze how route choice models can be adapted to efficient urban traffic management and intelligent transport systems (ITS), by constructing route sets and attributes from GPS and network data. With a route choice model that is responsive to traveltime changes in the network, travel behavior during incidents can be predicted to evaluate traffic management policies, such as traveler information and traffic control. The dataset consists of about 400,000 vehicle trips and is divided into a training dataset and a test dataset. The two datasets are compared, and the experiments show that the routes used are similar. Discrete route choice models are estimated with one data-driven path identification approach (DDPI) and one where the data-driven path set is augmented with routes from a network-based shortest path generation with link penalty (NBPA). The result suggests that the traveltime has a larger impact on the route choice when the model is trained on the NBPA route set and that the route's simplicity, length, and traveltime are important attributes for the route choice, which are useful insights in a traffic management context.

Traffic incidents on roads, defined as non-recurring events causing a temporary reduction in capacity, causes congestion, injuries and public costs. Knowledge about how travelers change their behavior, in particular how they adjust their route, during incidents can give important insights into how to manage traffic when incidents occur. This paper aims to analyze the impact of incidents on route choice to enable decision support systems during incidents. Reported incidents and GPS trajectories from road vehicles in Stockholm are used in the analysis. We propose a method to map incidents to network links using speed data. We also analyze incident impact on speed reduction, route choice at the network level, and route choice at the local level. A route choice model based on GPS data is evaluated on incident scenarios. The result shows that 5-12% of the incidents have a significant impact on the route choice. The impact of an incident on route choice appears to be influenced by the type and location of the incident, its duration, and the extent of the resulting speed reduction. Up to 22% of the travelers change their route to alternatives not passing the incident. The route choice model tends to overestimate this number.

Surgery for hip fractures is associated with high mortality and morbidity. The causes of poor outcome are not fully understood and may be related to other factors than the surgery itself. The relative contributions of patient, surgical, anaesthetic and structural factors have seldom been studied together. This study, a retrospective registry-based cohort study of 14 932 patients undergoing hip fracture surgery in Sweden from 1st of January 2014 to 31st of December 2016, aimed to identify important predictors of mortality post-surgery. The independent predictive power of our included variables was examined using Cox proportional hazards modeling with all-cause mortality at longest follow-up as the outcome. Twelve independent variables were considered as interrelated exposures and their individual adjusted effect within a single model were evaluated. Kaplan-Meier curves were also generated. Crude mortality rates were 8.2% at 30 days (95% CI 7.7-8.6%) and 23.6% at 365 days (95% CI 22.9-24.2%). Of the 12 factors entered into the Cox regression analysis, age (aHR1.06, p amp;lt; 0.001), male gender (aHR 1.45, p amp;lt; 0.001), ASA-PS-class (ASA 1amp;2 reference; ASA 3 aHR 2.12; ASA 4 aHR 4.79; ASA 5 aHR 12.57 respectively, p amp;lt; 0.001) and PACU-LOS (aHR 1.01, p amp;lt; 0.001) were significantly associated with mortality at longest follow-up (up to 3 years). University hospital status was protective (aHR 0.83, p amp;lt; 0.001) in the same model. Age, gender and ASA-PS-class were strong predictors of mortality after surgery for hip fractures in Sweden. University hospital status and length of stay in the postoperative care unit were also identified as modifiable risk factors after multivariable adjustment and require confirmation in future studies.

Background: Preoperative anaemia and red blood cell (RBC) transfusions are associated with poorer clinical outcomes. It is unknown whether perioperative RBC transfusions mediate the relationship between preoperative haemoglobin levels and postoperative outcomes. Methods: This was a prospective observational study among patients aged >= 50 yr undergoing elective major noncardiac surgery from four Swedish hospitals. The co-primary outcomes were 1-yr major adverse cardiovascular and cerebrovascular events (MACCEs) and all-cause mortality. The secondary outcome was a composite of 30-day mortality, MACCEs, acute kidney injury (AKI), pulmonary embolism, anastomotic leak, and postoperative infection. Mediation analyses were conducted with preoperative haemoglobin as the exposure and RBC transfusion as a mediator. Results: Among 1060 patients (mean age 70 [SD 9] yr; 472 [45%] women), 171 patients (16.1%) developed 1-yr MACCEs, and 105 patients (9.9%) died within 1 yr. Preoperative haemoglobin levels were significantly associated with both 1-yr MACCEs (b=-0.015, P=0.041) and all-cause mortality (b=-0.028, P<0.001). Volume of RBC transfusion was not directly associated with the outcomes and did not mediate the relationship between preoperative haemoglobin levels and 1-yr MACCEs (b=-0.001, P=0.451) or all-cause mortality (b=-0.002, P=0.293). For the secondary outcome, RBC transfusions had a significant mediating effect between preoperative haemoglobin and the composite 30-day outcome; however, no direct association was observed (b=0.006, P=0.554). Conclusions:<bold> </bold>Preoperative haemoglobin levels were significantly associated with 1-yr MACCEs and all-cause mortality. This effect was not mediated by perioperative RBC transfusions. Further research is needed to confirm these findings.

Background

The relationship between socioeconomic status and outcomes after hip fracture surgery remains unclear. We aimed to assess the association between individual-level socioeconomic status indicators and mortality after acute hip fracture surgery in Sweden.

Methods

Cross-linked registry-based cohort study of patients undergoing acute hip fracture surgery in Sweden 2015–20. Co-primary outcomes were 30-day and 2-yr all-cause mortality. Socioeconomic status was defined using four indicators: level of education, income, residential area, and receipt of social services. Attributable fractions were calculated to illustrate the potential population-level distribution of mortality differences across SES categories.

Results

There were 58 641 patients included (median age 83 [interquartile range 75–89] yr, 66.1% women). Crude 30-day and 2-yr mortalities were 7.9% (95% confidence interval [CI] 7.7–8.1) and 35.3% (95% CI 34.9–35.7). Level of education showed the strongest association, with a stepwise gradient most pronounced for 2-yr mortality: adjusted odds ratio 1.16 (95% CI 1.08–1.24) for 10–12 yr, 1.20 (95% CI 1.09–1.32) for 9 yr, and 1.25 (95% CI 1.16–1.34) for <9 yr vs >12 yr (all P<0.001). The attributal fraction for 2-yr mortality was 14.0% (standard error 0.022), with an increase in absolute risk of 6.3% (95% CI 4.3–8.2) for >12 yr vs <9 yr of education. Other socioeconomic status factors, except residential area, were also associated with mortality, although less substantially.

Conclusions

Individual socioeconomic status was associated with short- and long-term death after acute hip fracture surgery in Sweden, with education showing the strongest relationship. These findings support consideration of individual-level socioeconomic factors in perioperative hip fracture care at the population level.

Investigating magnetic materials at realistic conditions with first-principles methods is a challenging task due to the interplay of vibrational and magnetic degrees of freedom. The most difficult contribution to include in simulations is represented by the longitudinal magnetic degrees of freedom [longitudinal spin fluctuation (LSF)] due to their inherent many-body nature; nonetheless, schemes that enable to take into account this effect on a semiclassical level have been proposed and employed in the investigation of magnetic systems. However, assessment of the effect of vibrations on LSF is lacking in the literature. For this reason, in this work we develop a supercell approach within the framework of constrained density functional theory to calculate self-consistently the size of local-environment-dependent magnetic moments in the paramagnetic, high-temperature state in the presence of lattice vibrations and for liquid Fe in different conditions. First, we consider the case of bcc Fe at the Curie temperature and ambient pressure. Then, we perform a similar analysis on bcc Fe at Earths inner-core conditions, and we find that LSFs stabilize nonzero moments which affect atomic forces and the electronic density of states of the system. Finally, we employ the present scheme on liquid Fe at the melting point at ambient pressure and at Earths outer-core conditions (p approximate to 200 GPa, T approximate to 6000 K). In both cases, we obtain local magnetic moments of sizes comparable to the solid-state counterparts.

The Fe0.64Ni0.36 alloy exhibits an anomalously low thermal expansion at ambient conditions, an effect that is known as the invar effect. Other FexNi1-x alloys do not exhibit this effect at ambient conditions but upon application of pressure even Ni-rich compositions show low thermal expansion, thus called the pressure induced invar effect. We investigate the pressure induced invar effect for FexNi1-x for x = 0.64, 0.50, 0.25 by performing a large set of supercell calculations, taking into account noncollinear magnetic states. We observe anomalies in the equation of states for the three compositions. The anomalies coincide with magnetic transitions from a ferromagnetic state at high volumes to a complex magnetic state at lower volumes. Our results can be interpreted in the model of noncollinear magnetism which relates the invar effect to increasing contribution of magnetic entropy with pressure.

Inorganic ternary metal-C-N compounds with covalently bonded C-N anions encompass important classes of solids such as cyanides and carbodiimides, well known at ambient conditions and composed of [CN](-) and [CN2](2-) anions, as well as the high-pressure formed guanidinates featuring [CN3](5-) anion. At still higher pressures, carbon is expected to be 4-fold coordinated by nitrogen atoms, but hitherto, such CN4-built anions are missing. In this study, four polycarbonitride compounds (LaCN3, TbCN3, CeCN5, and TbCN5) are synthesized in laser-heated diamond anvil cells at pressures between 90 and 111 GPa. Synchrotron single-crystal X-ray diffraction (SCXRD) reveals that their crystal structures are built of a previously unobserved anionic single-bonded carbon-nitrogen three-dimensional (3D) framework consisting of CN4 tetrahedra connected via di- or oligo-nitrogen linkers. A crystal-chemical analysis demonstrates that these polycarbonitride compounds have similarities to lanthanide silicon phosphides. Decompression experiments reveal the existence of LaCN3 and CeCN5 compounds over a very large pressure range. Density functional theory (DFT) supports these discoveries and provides further insight into the stability and physical properties of the synthesized compounds.

This paper focuses on diffusion-oriented innovation intermediaries (“diffusion intermediaries”), i.e. actors that function as brokers between technology adopters and the providers of resources needed to implement a new technology that is available more or less “off-the-shelf”. It investigates how such actors create value for adopters of new technologies as well as the trade-offs they face. An interview-based, qualitative survey of 14 Swedish consultants and project developers involved in solar PV and wind power reveals that diffusion intermediaries create value mainly through technology transfer and coordination of various actors throughout the planning and implementation of turnkey projects. There is evidence of trade-offs related to value capture as well as between different value dimensions (e.g. between quality control and legitimacy). These findings have important implications for the design of strategies and policies to leverage value creation and handle trade-offs to avoid negative effects on projects, companies, and the overall diffusion of cleaner technologies. 

To limit the irreversible consequences of global warming, it is crucial that new actors adopt renewable electricity technologies. This type of innovation is, however, complex to implement, which is the reason adopters often contract with intermediaries for support services, e.g., project developers or installers. Previous studies have underlined that it is difficult for intermediaries to provide services that fully satisfy different types of adopters. Contributing to the previous research on customer satisfaction of services and innovation intermediaries, this article identifies adopters' expectations when adopting photovoltaic technology and analyzes whether such expectations match with the services provided by intermediaries. A cross-case analysis of photovoltaic projects was performed. Results underline that motives and driving forces for adopting the technology influences how adopters select intermediaries as well as what they expect from the services provided by intermediaries. The study finally contributes with some recommendations for intermediary organizations that want to improve and adapt their services to match their clients’ expectations and demands. 

PurposeThis case study explores a high-tech defence company, focusing on procurement's mediating role in enabling supply chain integration (SCI) within complex engineer-to-order (ETO) projects. The study aims to examine how procurement strategically responds to varying complexities to facilitate internal and external integration.Design/methodology/approachAn exploratory cross-case study examined procurement's role in ETO SCI. Semi-structured interviews with procurement professionals and key stakeholders, including project managers, design engineers and other central project members, provided a multifaceted perspective. These interviews provided insights into high-tech ETO-projects' structural and dynamic complexities.FindingsThis study shows how procurement mediates SCI dimensions in response to varying structural and dynamic complexities. It develops a framework that links SCI responses to complexity types, offering a more nuanced understanding of procurement's integrative role in ETO-defence projects.Originality/valueAddressing research gaps in the way in which procurement can respond to structural and dynamic complexity to facilitate SCI in ETO defence projects, the paper introduces a supply chain and technical complexity matrix, a framework tailored to high technology defence ETO-projects, by contributing to the SCI, ETO and procurement literature streams. Specifically, it positions procurement at the nexus of SCI dimensions and conceptualises its role in mediating structural and dynamic complexities. The framework offers both theoretical insight into procurement's integrative function and practical guidance for managing integration challenges in complex project-based environments.

PurposeThis study aims to examine supply chain resilience (SCR) in the defence industry by mapping supply-side, demand-side and internal risk dimensions and corresponding mitigation strategies disclosed by seven publicly listed defence firms over 2014-2024. Drawing on Resource Dependence Theory (RDT), the study introduces the Strategic Risk and Resilience Roadmap (S3R) to explain how firms use bridging and buffering to manage evolving resource dependencies.Design/methodology/approachThe study uses a longitudinal qualitative content analysis of annual reports. It combines artificial intelligence (AI)-assisted extraction using large language models (LLMs), iterative prompt engineering and manual cross-validation against source reports to categorise risks, trace mitigation strategies and track shifts in disclosed mitigation postures across three disruption eras: Baseline (2014-2019), Pandemic (2020-2021) and Emerging Risk (2022-2024).FindingsFirms adapt SCR by rebalancing bridging and buffering as resource dependencies change across disruption eras. In the Baseline era, firms rely mainly on bridging to stabilise external dependencies; during the Pandemic, they scale buffering to protect continuity under acute shocks; from 2022, they combine to adopt a hybrid posture as constraints persist and multiply. Supplier capacity and availability dominate post-2022 and customer-side risk reorients from funding uncertainty to delivery-performance exposure during ramp-ups. S3R traces a path-dependent process in which shifts in resource dependence drive risk reassessment, posture recalibration and learning that strengthens SCR over time.Research limitations/implicationsWhile based on publicly available reports and AI-extracted content, the analysis may omit informal or undisclosed practices. Future research should triangulate findings with interviews and firm-level performance metrics to deepen the insights.Originality/valueThis paper applies a longitudinal, AI-assisted qualitative content analysis of annual reports across supply-side, demand-side and internal risk dimensions, and it extends RDT into SCR by revealing dynamic bridging and buffering cycles across three disruption eras. It offers theoretical insight into the temporal evolution of defence SCR and a practical, multi-dimensional diagnostic framework.

BACKGROUND: The intense ischemic pain of acute compartment syndrome can be difficult to discriminate from the pain related to an associated fracture. Lacking objective measures, the decision to perform fasciotomy is often only based on clinical findings and performed at a low threshold. Biomarkers of muscle cell damage might help to identify and monitor patients at risk. In patients with fractures, however, markers of muscle cell damage could be elevated because of other reasons associated with the trauma, which would make interpretation difficult. In a review of all patients who underwent emergency fasciotomy in our health care district we aimed to investigate the decision-making process and specifically the use of biomarkers in patients with and without fractures.

METHODS: In the southeast health care region of Sweden 79 patients (60 men) with fractures (median age 26 years) and 42 patients (34 men) without associated fractures (median age 44 years) were treated with emergency fasciotomy of the lower leg between 2007 and 2016. Differences in clinical findings, p-myoglobin and p-creatine phosphokinase as well as pressure measurements were investigated.

RESULTS: P-myoglobin was analyzed preoperatively in 20% of all cases and p-creatine phosphokinase in 8%. Preoperative levels of p-myoglobin were lower in patients with fractures (median 1065 μg/L, range 200-3700 μg/L) compared with those without fractures (median 7450 μg/L, range 29-31,000 μg/L), p < 0.05. Preoperative intracompartmental pressure was lower in the fracture group (median 45 mmHg, range 25-90 mmHg) compared with those without fractures (median 83 mmHg, range 18-130 mmHg), p < 0.05.

CONCLUSIONS: Biomarkers are seldom used in the context of acute fasciotomy of the lower leg. Contrary to our expectations, preoperative levels of p-myoglobin and intracompartmental pressures were lower in fracture patients. These findings support differences in the underlying pathomechanism between the groups and indicate that biomarkers of muscle cell necrosis might play a more important role in the diagnosis of acute compartment syndrome than previously thought.

Circulating microRNAs (miRNAs) have become increasingly popular biomarker candidates in various diseases. However, heparin-based anticoagulants might affect the detection of target miRNAs in blood samples during quantitative polymerase chain reaction (qPCR)-based analysis of miRNAs involving RNA extraction, cDNA synthesis and the polymerase catalyzed reaction. Because low-molecular-weight heparins (LMWH) are widely used in routine healthcare, we aimed to investigate whether a prophylactic dose of the LMWH tinzaparin influences qPCR-based quantification of circulating miRNAs. A total of 30 subjects were included: 16 fracture patients with tinzaparin treatment and 14 non-fracture controls without anticoagulation therapy. To control for the effect of tinzaparin on miRNA analysis an identical concentration of synthetic miRNAs was added to plasma, isolated RNA and prepared complementary DNA (cDNA) from all samples in both groups. No significant difference was observed for cDNA synthesis or qPCR when comparing tinzaparin-treated patients with untreated controls. Among the tinzaparin-treated patients, plasma levels of six endogenous miRNAs (hsa-let-7i-5p, hsa-miR-30e-5p, hsa-miR-222-3p, hsa-miR-1-3p, hsa-miR-133a-3p, hsa-miR-133b) were measured before and one to six hours after a subcutaneous injection of tinzaparin 4500IU. No significant effect was observed for any of the investigated miRNAs. A prophylactic dose of 4500IU tinzaparin does not seem to affect cDNA synthesis or qRT-PCR-based quantification of circulating miRNAs.

Introduction The ischaemic pain of acute compartment syndrome (ACS) can be difficult to discriminate from the pain linked to an associated fracture. Lacking objective measures, the decision to perform fasciotomy is based on clinical findings and performed at a low level of suspicion. Biomarkers of muscle cell damage may help to identify and monitor patients at risk, similar to current routines for patients with acute myocardial infarction. This study will test the hypothesis that biomarkers of muscle cell damage can predict ACS in patients with tibial fractures. Methods and analysis Patients aged 15-65 years who have suffered a tibial fracture will be included. Plasma (P)-myoglobin and P-creatine phosphokinase will be analysed at 6-hourly intervals after admission to the hospital (for 48 hours) and-if applicable-after surgical fixation or fasciotomy (for 24 hours). In addition, if ACS is suspected at any other point in time, blood samples will be collected at 6-hourly intervals. An independent expert panel will assess the study data and will classify those patients who had undergone fasciotomy into those with ACS and those without ACS. All primary comparisons will be perforated between fracture patients with and without ACS. The area under the receiver operator characteristics curves will be used to identify the success of the biomarkers in discriminating between fracture patients who develop ACS and those who do not. Logistic regression analyses will be used to assess the discriminative abilities of the biomarkers to predict ACS corrected for prespecified covariates. Ethics and dissemination The study has been approved by the Regional Ethical Review Boards in Linkoping (2017/514-31) and Helsinki/Uusimaa (HUS/2500/2000). The BioFACTS study will be reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology recommendations.

Using the 1991 cyclone in Bangladesh as a natural experiment, this paper examines the long-term educational impacts of early-life disaster exposure. We employ a differences-in-differences approach with data from the 2019 Multiple Indicator Cluster Survey to compare educational outcomes between disaster-affected and unaffected districts across birth cohorts with varying exposure timing. The results reveal substantial and persistent negative effects of early-life cyclone exposure on educational attainment. Children exposed during critical early developmental periods (ages 0–3) experience approximately one year reduction in completed schooling, with secondary completion falling by 12–19 percentage points and higher secondary completion by 10–17 percentage points. Mechanism analysis reveals economic hardship as the primary transmission channel, operating through household budget constraints that force reductions in educational investment. Infrastructure damage creates additional barriers through reduced access, while maternal psychological stress extends impacts to post-disaster birth cohorts. Disaster impacts exacerbate existing inequalities: girls experience roughly double the educational losses of boys, while rural populations face consistently larger impacts. The concentration of effects at secondary and higher secondary education levels suggests that disasters may perpetuate intergenerational poverty by blocking access to the formal labor market, where secondary education is often the minimum requirement. Robustness checks, including threats to identification and placebo tests, confirmed that these results reflected a genuine impact of the cyclone rather than coincidental patterns. These findings are urgent given projected increases in extreme weather frequency under climate change, providing strong justification for integrating disaster resilience into human capital development strategies in vulnerable developing countries.

Bangladesh still has one of the highest rates of child marriage globally, despite nearly a century of legal restrictions. While previous research has identified various drivers of child marriage, the causal impact of natural disasters remains poorly understood. This study provides a causal analysis of how environmental shocks affect child marriage by examining Cyclone Sidr in Bangladesh in 2007. Using a difference-in-differences approach, we find that cyclone exposure substantially increased child marriage rates among 14-18-year-olds. The effects were largest for the youngest girls, with the probability of marrying before age 14 increasing by more than 60% among those who married during the study period. Event-study results indicate that child marriage rates tended to rise about six months after a disaster struck. This is typically when families begin to experience prolonged economic hardship. The increase in child marriages was most evident in severely affected and poverty-prone districts. This study underscores the importance of robust social protection measures for helping households absorb environmental shocks and mitigate adverse effects on child welfare.

Aniridia is a rare congenital condition of abnormal eye development arising principally from heterozygous mutation of the PAX6 gene. Among the multiple complications arising in the eye, aniridia-associated keratopathy (AAI() is a severe vision-impairing condition of the cornea associated with a progressive limbal stem cell deficiency that lacks suitable treatment options. Current mouse models of aniridia do not accurately represent the onset and progression dynamics of human AAI(, hindering therapy development. Here, we performed deep phenotyping of a haploinsufficient Pax6 +/- small-eye (Sey) mouse model on the 129S1/SvImJ background, which exhibits key features of mild presentation at birth and progressive AAI( with aging, mimicking human disease. The model exhibits a slowly progressing AAI( phenotype and provides insights into the disease, including disturbed basal epithelial cell organization, function, and marker expression; persistent postnatal lymphangiogenesis; disrupted corneal innervation patterns; and persisting yet altered limbal stem cell marker expression with age. The model recapitulates many of the known features of human disease, enabling investigation of underlying disease mechanisms and, importantly, access to a well-defined temporal window for evaluating future therapeutics.

PURPOSE. Aniridia-associated keratopathy (AAK) leads to loss of corneal transparency because of epithelial, inflammatory, and pathological vascular changes. Here, we sought to understand this process at the transcriptomic level while evaluating an experimental pharmacotherapy for potential modulatory effects. METHOD. 17 Pax6+/- Small-eye (Sey) heterozygous mice with p.Gly208* Pax6 mutation and 10 wild-type 129S1/SvImJ mice at four months of age were examined to identify dysregulated genes and pathways in established AAK. We next evaluated the potential efficacy of 10 mu M duloxetine administered as eye drops twice daily for 90 days, assessing outcomes at the transcriptomic level via microarray and protein level with Western blot and immunostaining. RESULTS. Transcriptomic analysis of the cornea revealed enrichment of Ccl21 gene family members associated with lymphangiogenesis, along with upregulation of genes involved in inflammation, cell adhesion, differentiation, motility, and keratinization, and downregulation of drug metabolism with significantly dysregulated genes emerging as potential therapeutic targets, including Gpha2, Chrnb3, Epgn, Cnfn, kallikreins and inflammation mediators Il18r1 and classical complement factors. Duloxetine therapy failed to regress AAK in adult corneas; however, transcriptomic profiling indicated duloxetine suppressed inflammatory genes and promoted anti-inflammatory and protective activity while modulating drug metabolism, suggesting potential beneficial effects in the cornea. CONCLUSIONS. Transcriptomics reveals multiple unexplored pathways and genes altered in the AAK mouse model. Although clinical results with duloxetine are promising, our current regimen and delivery method did not improve established disease. Duloxetine's therapeutic potential requires further study.

The epithelial layer of the cornea is a critical physical and ocular immune barrier. Corneal injury can trigger inflammation and an aggressive wound healing response that can compromise immune privilege and avascularity, leading to vision loss. The effects of chronic inflammation on limbal stem cell (LSC) function and its ability to renew the epithelium, however, remain unclear. Here, we use a corneal suture model in C57Bl/6 male mice to induce epithelial damage, inflammation and neovascularization, to examine the impact on LSCs. Using single-cell transcriptomics, we evaluate corneal cell state changes and the potential of duloxetine, an FDA-approved medicine, to promote corneal homeostasis. We show with single-cell RNA-seq analysis a loss of homeostatic LSCs, basal, and differentiated epithelial cells, and an increase in transformed LSC, conjunctival, inflammatory, and vascular cell states following cornea injury, suggesting a coordinated wound healing response in different tissue layers. We show duloxetine promotes epithelial homeostasis, LSC identity maintenance, epithelial and stromal repair, and suppression of immune and vascular responses. The current treatment regimen is, however, insufficient to improve the corneal phenotype in the short term. Single-cell level dynamics reveal detailed drug modes of action, highlighting key aspects of LSC and corneal cell plasticity during tissue repair.

Introduction: In this article, we explore to what extent it is possible to leverage on very small data to build machine learning (ML) models that predict acute exacerbations of chronic obstructive pulmonary disease (AECOPD).Methods: We build ML models using the small data collected during the eHealth Diary telemonitoring study between 2013 and 2017 in Sweden. This data refers to a group of multimorbid patients, namely 18 patients with chronic obstructive pulmonary disease (COPD) as the major reason behind previous hospitalisations. The telemonitoring was supervised by a specialised hospital-based home care (HBHC) unit, which also was responsible for the medical actions needed.Results: We implement two different ML approaches, one based on time-dependent covariates and the other one based on time-independent covariates. We compare the first approach with standard COX Proportional Hazards (CPH). For the second one, we use different proportions of synthetic data to build models and then evaluate the best model against authentic data.Discussion: To the best of our knowledge, the present ML study shows for the first time that the most important variable for an increased risk of future AECOPDs is "maintenance medication changes by HBHC". This finding is clinically relevant since a sub-optimal maintenance treatment, requiring medication changes, puts the patient in risk for future AECOPDs.Conclusion: The experiments return useful insights about the use of small data for ML.

Background: GOLD 2023 defines an exacerbation of COPD (ECOPD) by a deterioration of breathlessness at rest (BaR), mucus and cough. The severity of an ECOPD is determined by the degree of BaR, ranging from 0 to 10. However, it is not known which symptom is the most important one to detect early of an ECOPD, and which symptom that predicts future ECOPDs best. Thus, the purpose of the present study was to find out which symptom is the most important one to monitor.Methods: We analysed data on COPD symptoms from the telehealth study The eHealth Diary. Frequent exacerbators (n = 27) were asked to daily monitor BaR and breathlessness at physical activity (BaPA), mucus and cough, employing a digital pen and symptom scales (0-10). Twenty-seven patients with 105 ECOPDs were analysed. The association between symptom development and the occurrence of exacerbations was evaluated using the Andersen-Gill formulation of the Cox proportional hazards model for the analysis of recurrent time-to-event data with time-varying predictors.Results: According to the criteria proposed by GOLD 2023, 42% ECOPDs were mild, 48% were moderate and 5% were severe, while 6% were undefinable. Mucus and cough improved over study time, while BaR and BaPA deteriorated. Mucus appeared earliest, which was the most prominent feature of the average exacerbation, and worsening of mucus increased the risk for a future ECOPD. There was a 58% increase in the risk of exacerbation per unit increase in mucus score.Conclusion: This study suggests that mucus worsening is the most important COPD symptom to monitor to detect ECOPDs early and to predict future risk for ECOPDs. In the present study, we also noticed a pronounced difference between GOLD 2022 and 2023. Hence, GOLD 2023 defined the ECOPD severity much lower than GOLD 2022 did.

Background: Chronic heart failure (CHF) is a common comorbidity among patients with chronic obstructive pulmonary disease (COPD). Both exacerbations of COPD (ECOPDs) and exacerbations of CHF (ECHFs) display worsening of breathlessness at rest (BaR) and breathlessness at physical activity (BaPA). Comorbid CHF may have an impact on the vital signs assessed, when the Rome proposal (adopted by GOLD 2023) is applied on ECOPDs. Thus, the aim of the present study was to investigate the impact of comorbid CHF on ECOPDs severity, particularly focusing on the influence of comorbid CHF on BaR and BaPA. Methods: We analysed data on COPD symptoms collected from the telehealth study The eHealth Diary. Patients with COPD (n = 43) and patients with CHF (n = 41) were asked to daily monitor BaR and BaPA, employing a digital pen and scales for BaR and BaPA (from 0 to 10). Twenty-eight patients of the COPD patients presented with comorbid CHF. Totally, 125 exacerbations were analysed. Results: Exacerbations in the group with COPD patients and comorbid CHF were compared to the group with COPD patients without comorbid CHF and the group with CHF patients. Compared with GOLD 2022, the GOLD 2023 (the Rome proposal) significantly downgraded the ECOPD severity. Comorbid CHF did not interfere significantly on the observed difference. Comorbid CHF did not worsen BaR scores, assessed at inclusion and at the symptom peak of the exacerbations. Conclusion: In the present study, we find no evidence that comorbid CHF would interfere significantly with the parameters included in the Rome proposal (GOLD 2023). We conclude that the Rome proposal can be safely applied even on COPD patients with very advanced comorbid CHF.

Background Chronic obstructive pulmonary disease (COPD) in never-smokers may have other clinical characteristics than tobacco smoking-related COPD.Research question What are the risk factors, biomarkers, respiratory symptoms and health status in never-smoking individuals with COPD?Study design and methods We investigated never-smokers with COPD (n=154, mean age 60 years) from the population-based Swedish CArdioPulmonary bioImage Study (SCAPIS), and compared them with four control groups: never-smokers with normal lung function (n=281), current smokers with normal lung function (n=97), ex-smokers with COPD (n=103) and current smokers with COPD (n=55). COPD was defined as forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) less than the lower limit of normal (LNN) after bronchodilation. We examined fractional exhaled nitric oxide (FeNO), blood biomarkers, respiratory symptoms, health status, medical history and living conditions.Results The never-smoker COPD group reported more respiratory symptoms and worse health status than never-smokers with normal lung function, but fewer symptoms, milder airflow limitation and better health status compared with ex-smokers and smokers with COPD. Never-smokers with COPD had more self-reported asthma. Moreover, never-smokers with COPD had higher Immunoglobulin E sensitisations to a mix of aeroallergens, higher geometrical mean FeNO levels and blood eosinophil counts than never-smokers with normal lung function. When participants with self-reported asthma were excluded, never-smokers with COPD still had more wheeze, cough and higher FeNO.Conclusion Never-smokers with COPD had more respiratory symptoms and elevated markers of type-2 inflammation, suggesting they might represent a distinct clinical phenotype which may differ from smoking-related COPD. They may therefore need to be treated and followed differently.Trial registration number NCT03049202.

Life's Essential 8 (LE8) is a score that includes modifiable risk factors for cardiovascular disease. Four health behaviors (diet, physical activity, nicotine exposure and sleep health) and four health factors (non-HDL cholesterol, blood glucose, blood pressure and body mass index) are included. These modifiable risk factors promote inflammation, and inflammation is one of the biological mechanisms of cardiovascular disease development. Thus, we examined the relationship between cardiovascular health measured by LE8 and low-grade inflammation measured by high-sensitivity C-reactive protein (hs-CRP) in the cross-sectional population-based Swedish CArdioPulmonary bioImage Study (SCAPIS). The study consisted of 28,010 participants between 50 and 64 years (51.5% women, mean age 57.5 years). All individual LE8 components were assigned a score between 0 (unhealthy) and 100 (healthy) points, and a global score was calculated. The association between LE8 scores and high-risk hs-CRP (defined as &gt; 3.0 mg/L) was analyzed using adjusted logistic regression with spline analyses. There was a strong, dose response and inverse association between LE8 scores and levels of hs-CRP. Thus, those with a low LE8 score (= 50.0 points) had 5.8 higher (95% confidence interval [CI] 5.2-6.4) odds ratio (OR) of having high hs-CRP as compared to those with a high LE8 score (= 80.0 points). In conclusion, our findings show strong inverse associations between LE8 scores and levels of hs-CRP.

Background Digital tools and self-administered home blood tests offer a flexible approach to research data collection, biological sample management, and informed consent but require evaluation in relevant study settings. This study explored user experiences with a web-based digital tool for trial management, symptom reporting, and home blood testing.Methods Forty-three middle-aged participants took part in a 12-week mixed-method study, using digital tools for trial management, self-reported health data, and self-administered glycated hemoglobin A1c home blood tests. Usability was assessed through the validated mHealth App Usability Questionnaire (MAUQ) with additional study-specific items. Every second participant completed a semi-structured interview, analyzed using qualitative content analysis.Results The MAUQ responses (scale 1-7) indicated that digital consent (94.7% agreed), and home blood tests (100% agreed) were well-received. However, finding information on digital tools was challenging (52.9% disagreed it was easy), and participants did not perceive the tools highly effective for managing health (52.9% disagreed they were helpful). Interviews with 20 participants reinforced these findings, emphasizing motivation, support, efficient resource use, and the importance of clarity, usability, safety, and security.Conclusion While self-administered blood tests and online consent were considered user-friendly, improvements are needed in digital tool navigation and information accessibility to enhance usability in decentralized trials, especially for participants who find them difficult or unhelpful.

Objectives: To assess whether levels of physical activity can be modified and sustained for 2 years in postmenopausal women with initially low physical activity levels participating in a randomised controlled trial. Study design: Postmenopausal women with vasomotor symptoms and low activity levels were randomised to a 15week supervised full-body resistance training program three times/week or a control group maintaining low activity. After the intervention, controls were offered an introductory resistance training session and 15-week gym membership. Both groups received informative and encouraging emails every six months during 2-year follow-up. Main outcome: Change in level of physical activity. Measures: Physical activity was assessed via the International Physical Activity Questionnaire short form (IPAQ) at baseline, 15 weeks, six months, and two years. Data were analysed with Wilcoxon's signed rank, Friedman, and Mann-Whitney U tests. Results: Of 65 women randomised, 58 (89 %) completed the 2-year follow-up study. At baseline, 21 in the intervention and 15 in the control group were inactive according to IPAQ scores. After two years, this was reduced to four in each group (14 % and 16 %, respectively). Both groups significantly increased moderate to vigorous activity from baseline to two years (intervention group: median 0 to 180 min, p &lt; 0.001; control group: median 0 to 125 min, p = 0.004). Conclusions: Both groups significantly increased their level of physical activity (intervention group during the 15week intervention, control group between 15-week and 6-month follow-ups) and maintained this for two years. A resistance training session, gym membership, training diary, and supportive emails form a feasible strategy to improve physical activity among postmenopausal women with low activity levels.

Background: Vasomotor symptoms (VMS) are common around menopause. Menopausal hormone therapy is the most effective treatment for VMS. Physical exercise has been proposed as an alternative treatment since physically active women have previously been found to experience fewer VMS than inactive women. In our randomised controlled trial on resistance training to treat VMS, sympoms were reduced by 50% in the intervention group compared with the control group.

Objectives: To propose a mechanism to explain how resistance training reduced VMS and to assess if luteinizing hormone (LH) and follicle stimulating hormone (FSH) were affected in accordance with the proposed mechanism.

Trial design and methods: A substudy of a randomized controlled trial on 65 postmenopausal women with VMS and low physical activity who were randomised to 15 weeks of resistance training three times per week (n = 33) or to a control group (n = 32). To be regarded compliant to the intervention we predecided a mean of two training sessions per week. The daily number of VMS were registered before and during the 15 weeks. Blood samples were drawn for analysis of LH and FSH at baseline and after 15 weeks.

Results: LH decreased significantly in the compliant intervention group compared with the control group (-4.0±10.6 versus 2.9±9.0, p = 0.028 with Mann-Whitney U test). FSH also decreased in the compliant intervention group compared with the control group, however not enough to reach statistical significance (-3.5±16.3 versus 3.2±18.2, p = 0.063 with Mann-Whitney U test). As previously published the number of hot flushes decreased significantly more in the intervention group than in the control group but there was no association between change in LH or FSH and in number of VMS.

Conclusions: We propose that endogenous opiods such as β-endorphin or dynorphin produced during resistance training decreased VMS by stimulating KNDγ-neurons to release neurokinin B to the hypothalamic thermoregulatory centre. Through effects on KNDγ-neurons, β-endorphin could also inhibit GnRH and thereby decrease the production of LH and FSH. The significanty decreased LH in the compliant intervention group compared with the control group was in accordance with the proposed mechanism.

Packing products into a pallet or other medium is an unavoidable activity for producing companies. In many cases, packing is based on operator experience and training using packing patterns that have worked before. Automated packing, on the other hand, requires a systematic procedure for devising packing solutions. In the scientific literature, this problem is known as 3D bin packing (3DBP) and many authors have proposed exact and heuristic solutions for many variations of the problem. There is, however, a lack of datasets that can be used to test and validate such solutions. Many of the available datasets use randomly generated products with extremely limited connection to real practice. Furthermore, they contain a reduced number of product configurations and ignore that packing relates to customers orders, which have specific relative mixes of products. This paper proposes a software toolbox for generating arbitrarily large datasets for 3DBPP based on real industry data. The toolbox was developed in connection with the analysis of a real dataset from the food and beverages sector, which enabled the creation of several synthetic datasets. The toolbox and the synthetic datasets are publicly available and can be used to generate additional data for testing and validating 3DBP solutions. The industry is increasingly becoming data dependent and driven. The ability to generate good quality synthetic data to support the development of solutions to real industry problems is of extreme importance. This work is a step in that direction in a domain where open data are scarce.

With the growing demand for sustainable and optimal packaging solutions, this study proposes a novel two-stage algorithm for the multi-container three-dimensional bin packing problem. The research addresses this problem within the context of a real-world industrial scenario and implements several practical constraints including: full shipment, customer positioning requirements, and product geometric interlocking, for increased stability and with the purpose of minimizing the use of plastic wrapping and/or additional supporting surfaces. The main optimization target is to minimize the total number of containers used in the palletization process of custom orders with varying degrees of complexity. The proposed algorithm includes two stages/phases of processing. In the first phase, the algorithm uses constructive heuristics to generate homogeneous product layers. The layers are then stacked to produce blocks, which are then placed on individual containers or pallets. The second phase packs the leftover items using a genetic algorithm. The performance of the proposed solution is benchmarked using real-world industrial data, as well as a more classic academic benchmark. It is demonstrated, across a very large set of orders, that the algorithm always achieves solutions for full palletization of the orders. The analysis shows that the approach is generic and the quality of the solutions generated is relatively even for both small and large, homogeneous and heterogeneous problem instances.

This paper presents a digital model-driven optimization framework for addressing real-world constraints in robot-assisted palletization, focusing on applications in warehousing. The proposed approach integrates 3D Bin Packing Problem with robotic placement constraints, ensuring feasible and optimal palletization solutions. By leveraging a digital model of the robotic system, the method captures critical factors such as reachability, collision avoidance, and dynamic stability, which are often overlooked in traditional optimization models. A custom genetic algorithm drives the optimization process, balancing space utilization and operational feasibility. Experimental results demonstrate the robustness of the framework in handling complex, real-world logistics scenarios while ensuring compatibility with robotic systems. This research bridges the gap between theoretical optimization and industrial implementation, offering a scalable solution for resilient and efficient warehousing automation. Copyright (c) 2025 The Authors.

Food products must increasingly satisfy multiple, often conflicting requirements related to cost, sensory quality, nutritional value, and sustainability. Conventional recipe optimization studies in food engineering typically treat these aspects in isolation or restrict attention to at most two or three objectives, which limits the ability to explore realistic trade-offs. In this work the authors present a cross-disciplinary optimization framework that treats recipe design as a many-objective problem and integrates three domains: process, operation, and nutrition. The framework is demonstrated on the development of a protein-rich meatball recipe. Four ingredients are combined under compositional and process constraints, and six objectives are optimized simultaneously: production cost, production time, overall taste, acidity, energy density, and protein density. Sensory attributes are modeled by surrogate functions trained on data from a designed experiment and sensory evaluation, allowing rapid scoring of candidate recipes during optimization. System and nutritional attributes are linked to a Digital Food Identity Card (DFIC), which provides ingredient-specific information such as cost, cooking time, and nutritional composition. This enables dynamic ingredient substitution and adaptation of recipes to changing prices and availability. A custom multi-objective evolutionary algorithm is used to generate a six-dimensional Pareto set, which is then visualized with a novel representation based on a ring of congruent quadrilaterals (Quad2Quad). This advanced Pareto front visualization enhances the interpretability of the trade-offs between objectives visually interpretable and supports the identification of balanced solutions that satisfy requirements across all three domains (i.e., process, operation and nutrition). The case study illustrates how the proposed framework can help food developers design recipes that are nutritionally dense, sensorially acceptable, economically viable, and robust to fluctuations in the supply chain.

The intrinsically disordered MYC proteins are master regulators of cellular growth and function, but when deregulated they become cancer drivers. MYC-protein interactions are key to oncogenesis, and while disrupting such interactions would be of significant therapeutic benefit, the intrinsically disordered properties of MYC have dramatically hampered their characterization. Here, we apply an integrated structural biology approach to describe the structure and dynamics of the N-Myc-Aurora A complex, which is critical in neuroendocrine tumor progression. We reveal a functional interaction where multiple binding sites on N-Myc interact with the Aurora A N-lobe. The interaction is governed by aromatic clusters within the conserved MB0 and MBI motifs in N-Myc that interact with Aurora A in a dynamic binding mode that allosterically promotes kinase activation. We show that N-Myc binding to the Aurora A N-lobe can be inhibited by the small-molecule AurkinA, providing opportunity for therapeutical strategies to disrupt this interaction.

This scoping review mapped school-based interventions for K-12 students with intellectual disability (ID; IQ &lt;= 75 or a diagnosed intellectual disability), focusing on outcomes, theoretical frameworks, study designs, and research transparency. A systematic search across six databases identified 952 studies, published 2000-2023. The most common interventions were assistive or instructional, primarily targeting academic outcomes. Multiple probe designs were the most prevalent study method, with frequent reliance on non-standardized measures. Reporting on theoretical frameworks was limited, and adherence to open science practices, including data sharing and ethics statement reporting, was minimal. The findings highlight the need for improved methods to synthesize prevalent single-case evidence in this field. Furthermore, the limited engagement with open science practices warrants exploration of barriers to and support for their implementation.