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Mechanistic drug release from cellulose acetate butyrate–palmitic acid-based in situ gels for targeted periodontal therapy via UV–vis imaging
No full textSolvent exchange-induced in situ gels (ISGs) composed of cellulose acetate butyrate (CAB) and palmitic acid (PAL) as matrix forming agents were developed by dissolving in dimethyl sulfoxide (DMSO) and N -methyl pyrrolidone (NMP) for localized moxifloxacin HCl (Mox) delivery in periodontal treatment. The formulations were characterized in terms of viscosity, injectability, mechanical properties, matrix formation, drug release, and antimicrobial activity. UV–Vis imaging was employed to investigate the dynamic processes of solvent transport, drug release, and matrix formation. Combination of CAB and PAL provided acceptable injectability and prolonged drug release. Phase inversion dynamics via UV–vis imaging showed that DMSO based formulations exhibited faster solvent exchange as well as faster drug diffusion as compared to NMP based formulations, which exhibited slower solvent diffusion, leading to more sustained drug release and aligned with matrix formation. Mox-loaded combined CAB and PAL-based ISG demonstrated notable antimicrobial activity against Staphylococcus aureus , Candida albicans , and Porphyromonas gingivalis associated with periodontitis, confirming their potential for periodontitis therapy. This study highlights the critical role of matrix composition, solvent selection, and phase inversion in influencing mechanistic drug release from CAB–PAL ISG for targeted periodontitis therapy as demonstrated through UV–Vis imaging.</p
Diagnostic algorithms for tuberculosis in Europe:insights from the European Reference Laboratory Network for Tuberculosis (ERLTB-Net)
No full textThe reported poor treatment outcomes for extensively drug-resistant tuberculosis (TB) in the European region highlight the urgent need for effective and context-appropriate diagnostic strategies. While the World Health Organisation (WHO) provides model algorithms, these require adaptation to the European Union/European Economic Area (EU/EEA) context, a setting with low TB incidence but high resources. This viewpoint from the European Reference Laboratory Network for TB (ERLTB-Net) proposes a tailored diagnostic algorithm that prioritises the universal use of WHO-recommended molecular rapid diagnostic tests, systematic culture, and whole genome sequencing (WGS). This approach integrates phenotypic drug susceptibility testing strategically and outlines the possible role of targeted next-generation sequencing (tNGS) in the EU/EEA setting. The algorithm also addresses the importance of diagnostic harmonisation, cross-border collaboration, and sustained investment in sequencing capacity. By aligning diagnostic practices with the regional epidemiology and laboratory infrastructure, this stepwise, resource-sensitive approach aims to strengthen TB control, improve treatment outcomes, and guide public health action in the EU/EEA.The reported poor treatment outcomes for extensively drug-resistant tuberculosis (TB) in the European region highlight the urgent need for effective and context-appropriate diagnostic strategies. While the World Health Organisation (WHO) provides model algorithms, these require adaptation to the European Union/European Economic Area (EU/EEA) context, a setting with low TB incidence but high resources. This viewpoint from the European Reference Laboratory Network for TB (ERLTB-Net) proposes a tailored diagnostic algorithm that prioritises the universal use of WHO-recommended molecular rapid diagnostic tests, systematic culture, and whole genome sequencing (WGS). This approach integrates phenotypic drug susceptibility testing strategically and outlines the possible role of targeted next-generation sequencing (tNGS) in the EU/EEA setting. The algorithm also addresses the importance of diagnostic harmonisation, cross-border collaboration, and sustained investment in sequencing capacity. By aligning diagnostic practices with the regional epidemiology and laboratory infrastructure, this stepwise, resource-sensitive approach aims to strengthen TB control, improve treatment outcomes, and guide public health action in the EU/EEA.</p
Non-inferiority of Rituximab versus OCrelizumab in Multiple Sclerosis (ROC-MS)-an individual participant data meta-analysis
No full textBackgroundOcrelizumab (OCR) is widely and effectively used to treat multiple sclerosis (MS). Available evidence suggests that rituximab (RTX), another anti-CD20 monoclonal antibody used off-label in some countries, may be equally effective and safe. However, current data comparing RTX and OCR come from retrospective observational cohorts with conflicting conclusions. Higher-quality evidence is needed to guide treatment decisions when choosing between RTX and OCR for MS. To address this high priority research question, four randomized controlled trials (OVERLORD-MS, DanNORMS, Noisy Rebels, TRIO) are evaluating the non-inferiority of RTX compared to OCR and have formed a collaborative initiative (ROC-MS) to conduct an individual participant data (IPD) prospective meta-analysis (PMA).MethodsIn the PMA, core outcomes are harmonized across the four trials. IPD will be obtained from active relapsing-remitting MS (RRMS) patients. Primary outcome is relapse in a re-baselined period from month 6 to month 24 and a non-inferiority hypothesis will be tested. Secondary outcomes include other clinical, patient-reported, radiological, blood biomarkers, and safety measures. Collectively, the studies in the collaboration will provide data from 1109 RRMS patients: 660 receiving RTX and 449 receiving OCR. Patient recruitment has started at all sites and has been completed at two sites, as of October 2025.ConclusionThis ROC-MS collaboration will improve the precision of the estimates, increase statistical power for outcomes and assessment of rare events and facilitate subgroup analyses, ultimately providing robust evidence on the efficacy and safety of RTX compared to OCR in RRMS treatment. Results are expected in 2028.BACKGROUND: Ocrelizumab (OCR) is widely and effectively used to treat multiple sclerosis (MS). Available evidence suggests that rituximab (RTX), another anti-CD20 monoclonal antibody used off-label in some countries, may be equally effective and safe. However, current data comparing RTX and OCR come from retrospective observational cohorts with conflicting conclusions. Higher-quality evidence is needed to guide treatment decisions when choosing between RTX and OCR for MS. To address this high priority research question, four randomized controlled trials (OVERLORD-MS, DanNORMS, Noisy Rebels, TRIO) are evaluating the non-inferiority of RTX compared to OCR and have formed a collaborative initiative (ROC-MS) to conduct an individual participant data (IPD) prospective meta-analysis (PMA).METHODS: In the PMA, core outcomes are harmonized across the four trials. IPD will be obtained from active relapsing-remitting MS (RRMS) patients. Primary outcome is relapse in a re-baselined period from month 6 to month 24 and a non-inferiority hypothesis will be tested. Secondary outcomes include other clinical, patient-reported, radiological, blood biomarkers, and safety measures. Collectively, the studies in the collaboration will provide data from 1109 RRMS patients: 660 receiving RTX and 449 receiving OCR. Patient recruitment has started at all sites and has been completed at two sites, as of October 2025.CONCLUSION: This ROC-MS collaboration will improve the precision of the estimates, increase statistical power for outcomes and assessment of rare events and facilitate subgroup analyses, ultimately providing robust evidence on the efficacy and safety of RTX compared to OCR in RRMS treatment. Results are expected in 2028.</p
Incorporating insights from global production network and value chain research into the sustainability transitions field
No full textThe sustainability transitions (ST) field has benefited from the integration of theories and insights from various fields. In this perspective, we argue that the time is ripe to consider how insights from global production network (GPN) and global value chain (GVC) research can contribute to a new understanding and explanation of complex and multi-scalar transition processes and outcomes. With a modular theory building point of departure, we discuss three ST research areas in which elements from GPN/GVC’s meso‑level analytical toolkit can be integrated: industrial transformation, multi-system interactions, and just transitions
Linking Crystal Structure to Solubility and Hygroscopicity in Oxytetracycline Hydrochloride Forms
No full textThe present study was motivated by the unusually large differences in solubility observed between two polymorphic forms of an antibiotic active pharmaceutical ingredient, oxytetracycline hydrochloride. These differences significantly exceed typical polymorphic solubility variations. Through detailed structural analysis, we demonstrate that forms I and II are not true polymorphs but pseudopolymorphs: anhydrous salt of oxytetracycline hydrochloride (OxyCl) and its hydrate (2OxyCl<middle dot>3H 2 O). In the course of this work, we also crystallized and characterized three new structures of hydrates, as well as one methanol and one ethanol solvate of oxytetracycline hydrochloride. Having determined the crystal structures of all known forms and supplemented this data with XRPD measurements at different humidity levels, we provide new insight into structure-property relationships within this system. Our analysis reveals that solubility and hygroscopicity are closely related to specific features of crystal packing - particularly the thickness of alternating organic and inorganic layers formed through characteristic intermolecular interactions
Preheating-driven structural changes enhance acid-induced gelation of pea and faba bean protein ingredients
No full textThis work explores the role of preheating in modulating the properties of acid-induced gels produced from commercial pea protein isolate (PPI), pea protein concentrate (PPC), and faba protein concentrate (FPC). Protein dispersions (5 % w/w) were preheated under various temperature-time combinations (65–95 °C for 5–60 min) before acid-induced gelation. Small and large amplitude oscillatory shear (SAOS and LAOS) tests revealed that preheating significantly enhanced gel strength (higher storage modulus, G′) and deformability (higher critical strain, γc) across all ingredients, with FPC exhibiting the greatest improvement. The influence of preheating temperature on gel properties was more pronounced than that of heating time. The mechanisms responsible for these improvements were distinct in isolates and concentrates. For PPI, produced by wet fractionation, the particle size decreased after preheating, while the solubility and hydrodynamic size (z-average) increased. Considering its highly denatured status, preheating dissociated larger insoluble aggregates into smaller, soluble forms, thus contributing to the gelation. In contrast, in PPC and FPC produced by dry fractionation, protein remained largely native. Preheating unfolded protein structures and promoted aggregation of convicilin and legumin subunits. For these samples, particle size and z-average increased while solubility decreased. A strong correlation between z-average and G′ highlighted the role of soluble aggregates in enhancing the gel strength. These findings demonstrate that preheating can effectively functionalize commercial legume protein intended for acid-induced gelation, offering a better texture for foods like vegan/hybrid cheese alternatives while ensuring food safety.</p
Transforming Healthcare with State-of-the-Art Medical-LLMs:A Comprehensive Evaluation of Current Advances Using Benchmarking Framework
No full textThe emergence of Medical Large Language Models has significantly transformed healthcare. Medical Large Language Models (Med-LLMs) serve as transformative tools that enhance clinical practice through applications in decision support, documentation, and diagnostics. This evaluation examines the performance of leading Med-LLMs, including GPT-4Med, Med-PaLM, MEDITRON, PubMedGPT, and MedAlpaca, across diverse medical datasets. It provides graphical comparisons of their effectiveness in distinct healthcare domains. The study introduces a domain-specific categorization system that aligns these models with optimal applications in clinical decision-making, documentation, drug discovery, research, patient interaction, and public health. The paper addresses deployment challenges of Medical-LLMs, emphasizing trustworthiness and explainability as essential requirements for healthcare AI. It presents current evaluation techniques that improve model transparency in high-stakes medical contexts and analyzes regulatory frameworks using benchmarking datasets such as MedQA, MedMCQA, PubMedQA, and MIMIC. By identifying ongoing challenges in bias mitigation, reliability, and ethical compliance, this work serves as a resource for selecting appropriate Med-LLMs and outlines future directions in the field. This analysis offers a roadmap for developing Med-LLMs that balance technological innovation with the trust and transparency required for clinical integration, a perspective often overlooked in existing literature.</p
Characterization of butter and margarine oil composition using benchtop NMR and FTIR:A comparative study of products from Uzbekistan and Denmark
No full textThis study presents an optimized workflow for rapid quantification of core quality traits in edible oils, including trans-fatty acids (TFA), saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), and selected additives, by combining 80 MHz benchtop 1H NMR and Fourier transform infrared (FTIR) spectroscopy. Seventy commercial margarine and butter products from Denmark and Uzbekistan were analyzed. FTIR-based TFA quantification showed that nearly 50 % of the Uzbek margarines exceeded the 2 % regulatory threshold, while all Danish samples remained below 1.3 %. Butter, which naturally contains rumen-derived TFA, exhibited greater variability (up to 6 %) but no country-specific differences. NMR analysis revealed clear compositional contrasts between butters and margarines, and between the same product types across the two countries. Butter consistently contained more SFA and less PUFA than margarine, while MUFA and PUFA showed the greatest geographical variation. Benchtop NMR also enabled detection of additives, such as stanol esters and sorbic acid, in several butter samples. Overall, this work demonstrates a workflow based on green analytical technologies that provides robust chemical insights into core quality traits of edible oils, enabling efficient monitoring in both research and quality control laboratories.</p
Hverdagslivsanalyse: Hvordan kan man anlaysere feriefotografier som kulturhistorie?
No full textmetodeartikel om at analysere personlige/familiefotos som kulturhistori