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Hair analysis has been known for its role in forensic science. However, it may also have an important role in the clinical approach of various exposures, for example drugs and heavy metals. In the Netherlands, it is used infrequently probably because clinicians are not familiar with this diagnostic possibility. In this article, we present two cases in which hair analysis proved to be crucial in the diagnosis of two different exposures (tobacco smoking and arsenic). We provide an overview of the various clinical applications of hair analysis and important factors affecting the results of hair analysis.

Supplemental material, sj-pptx-1-tpp-10.1177_20451253211065857 for Population pharmacokinetic model and limited sampling strategy for clozapine using plasma and dried blood spot samples by Lisanne M. Geers, Dan Cohen, Laura M. Wehkamp, Hans J. van Wattum, Jos G.W. Kosterink, Anton J.M. Loonen and Daan J. Touw in Therapeutic Advances in Psychopharmacology

Additional file 1. Relationship between the window size (sec) and detection accuracy (%) for the SD algorithm.

Additional file 2. Calculated alarm delays in minutes for combinations of administration rates and pressure limits assuming a clinical baseline counter pressure of 150 mmHg.

Purpose: Smart medication adherence monitoring devices can provide objective and granular drug utilization data and help patients engaging with their treatment. In this proof-of-concept study, the acceptability and technical robustness of a novel smart pill bottle prototype (SPBP) were assessed in order to allow further optimization. Methods: The SPBP is an app-controlled automatic dispense system, capturing real-time data on a web-based platform, which sends text reminders and measures storage conditions. A heterogeneous group of ten volunteers was asked to dispense placebo capsules with the SPBP and to follow a predefined dosing schedule for a trial period of 2 weeks. Afterwards, a questionnaire was filled out during a short interview. Primary outcome was dispense adherence as measured by the bottle. Other study outcomes included system acceptability (System Usability Scale [SUS]), self-reported adherence (MARS) and technical robustness of the bottle’s mechanics (electronic pill dispenser) and sensors (bottle temperature). Results: The overall dispense adherence rate as measured by the SPBP was 88%. All participants completed the study and four participants had an adherence rate of 100% during the study. The dispense adherence rates corresponded well with participants’ self-reported adherence with an average MARS total score of 23.6 (out of 25). Participants judged the system easy to use, with a mean SUS score of 79.3 (range: 57.5– 97.5). The overall mean temperature difference between the bottle sensor and calibrated external sensor was − 0.82°C (range: − 1.37°C to − 0.21°C). Conclusion: The SPBP was well accepted and this study provides data for further optimization and follow-up studies. Smart adherence technologies such as these may change the way healthcare professionals, trialists and patients manage medication adherence.

Additional file 4. Relation between levels of LCONV, the corresponding values of LMX and the reduction in lumens where Ddrugs = 2 min.

Additional file 1. Compatibility chart.

Supplemental material, Reviewer_2_v.1 for Eradication of Pseudomonas aeruginosa in cystic fibrosis patients with inhalation of dry powder tobramycin by Anne M. Akkerman-Nijland, Mina Yousofi, Bart L. Rottier, Hester Van der Vaart, Johannes G. M. Burgerhof, Henderik W. Frijlink, Daan J. Touw, Gerard H. Koppelman and Onno W. Akkerman in Therapeutic Advances in Respiratory Disease

Additional file 8. Number of IV lumens required by multiplex scheduling (LMX; panels A-E and G-K) and by conventional scheduling (Lconv; panels F and L). Values of Lconv and Lmx were determined over 1 h periods (panels A-F) and the maximal values of Lconv and Lmx aggregated over 24 h periods from midnight to midnight (panels G and L). Note that for Ddrugs = 1, 2, and 5 a maximum of 4 lm is required, whereas for Ddrugs = 10 and 20 a maximum number of 6 lm is required.

Supplemental material, Supplementary_material for Quantitative assessment of required separator fluid volume in multi-infusion settings by Frank Doesburg, Daniek Middendorp, Willem Dieperink, Wouter Bult, Maarten W Nijsten and Daan J Touw in The Journal of Vascular Access

Additional file 3. Relation between levels of LCONV, the corresponding values of LMX and the reduction in lumens where Ddrugs = 1 min.

Additional file 6. Relation between levels of LCONV, the corresponding values of LMX and the reduction in lumens where Ddrugs = 10 min.

Additional file 1: Additional figures, tables and appendices.

Additional file 9. Relation between the multiplex administration rate (QMX) and the conventional rate (QCONV) for different values of Ddrugs.

Additional file 7. Relation between levels of LCONV, the corresponding values of LMX and the reduction in lumens where Ddrugs = 20 min.

Additional file 5. Relation between levels of LCONV, the corresponding values of LMX and the reduction in lumens where Ddrugs = 5 min.

Additional file 2. Flow of study data.