Browsing by Subject "217 Medical engineering"

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  • Al-Sa'd, Mohammad; Kiranyaz, Serkan; Ahmad, Iftikhar; Sundell, Christian; Vakkuri, Matti; Gabbouj, Moncef (2022)
    Social distancing is crucial to restrain the spread of diseases such as COVID-19, but complete adherence to safety guidelines is not guaranteed. Monitoring social distancing through mass surveillance is paramount to develop appropriate mitigation plans and exit strategies. Nevertheless, it is a labor-intensive task that is prone to human error and tainted with plausible breaches of privacy. This paper presents a privacy-preserving adaptive social distance estimation and crowd monitoring solution for camera surveillance systems. We develop a novel person localization strategy through pose estimation, build a privacy-preserving adaptive smoothing and tracking model to mitigate occlusions and noisy/missing measurements, compute inter-personal distances in the real-world coordinates, detect social distance infractions, and identify overcrowded regions in a scene. Performance evaluation is carried out by testing the system's ability in person detection, localization, density estimation, anomaly recognition, and high-risk areas identification. We compare the proposed system to the latest techniques and examine the performance gain delivered by the localization and smoothing/tracking algorithms. Experimental results indicate a considerable improvement, across different metrics, when utilizing the developed system. In addition, they show its potential and functionality for applications other than social distancing.
  • Raevuori, Anu; Vahlberg, Tero; Korhonen, Tellervo; Hilgert, Outi; Aittakumpu-Hyden, Raija; Forman-Hoffman, Valerie (2021)
    Background: Meru Health Program (MHP) is a therapist-guided, 8-week intervention for depression delivered via smartphone. The aim was to test its efficacy in patients with clinical depression in a Finnish university student health service.& nbsp; Methods: Patients (n=124, women 72.6%, mean age 25y) were stratified based on antidepressant status, and randomized into intervention group receiving MHP plus treatment as usual (TAU), and control group receiving TAU only. Depression, measured by the Patient Health Questionnaire-9 (PHQ-9) scale, was the primary outcome. After baseline (T0), follow-ups were at mid-intervention (T4), immediately post-intervention (T8); 3 months (T20), and 6 months (T32) post-intervention.& nbsp; Results: The intervention group and control group did not have significant differences in depression outcomes throughout end of treatment and follow-up. Among secondary outcomes, increase in resilience (d=0.32, p=0.03) and mindfulness (d=0.57, p=0.002), and reduction in perceived stress (d=-0.52, p=0.008) were greater in MHP+TAU versus TAU at T32; no differences were found in anxiety, sleep disturbances, and quality of life between groups. Post-hoc comparisons of patients on antidepressants showed significantly greater reduction in depression at T32 for MHP+TAU versus TAU (d=-0.73, p=0.01); patients not on antidepressants showed no between-group differences.& nbsp; Limitations: Limitations include unknown characteristics of TAU, potential bias from patients and providers not being blinded to treatment group, and failure to specify examination of differences by antidepressant status in the protocol.& nbsp; & nbsp;Conclusions: Most outcomes, including depression, did not significantly differ between MHP+TAU and TAU. Exploratory analysis revealed intervention effect at the end of the 6-month follow-up among patients on anti-depressant medication.
  • Kortesniemi, Mika; Siiskonen, Teemu; Kelaranta, Anna; Lappalainen, Kimmo (2017)
    Radiation worker categorization and exposure monitoring are principal functions of occupational radiation safety. The aim of this study was to use the actual occupational exposure data in a large university hospital to estimate the frequency and magnitude of potential exposures in radiology. The additional aim was to propose a revised categorization and exposure monitoring practice based on the potential exposures. The cumulative probability distribution was calculated from the normalized integral of the probability density function fitted to the exposure data. Conformity of the probabilistic model was checked against 16 years of national monitoring data. The estimated probabilities to exceed annual effective dose limits of 1 mSv, 6 mSv and 20 mSv were 1:1000, 1:20 000 and 1:200 000, respectively. Thus, it is very unlikely that the class A categorization limit of 6 mSv could be exceeded, even in interventional procedures, with modern equipment and appropriate working methods. Therefore, all workers in diagnostic and interventional radiology could be systematically categorized into class B. Furthermore, current personal monitoring practice could be replaced by use of active personal dosemeters that offer more effective and flexible means to optimize working methods.
  • Paalasmaa, Joonas; Toivonen, Hannu; Partinen, Markku (2015)
  • Jönsson, Emma H.; Kotilahti, Kalle; Heiskala, Juha; Backlund Wasling, Helena; Olausson, Håkan; Croy, Ilona; Mustaniemi, Hanna; Hiltunen, Petri; Tuulari, Jetro J.; Scheinin, Noora M.; Karlsson, Linnea; Karlsson, Hasse; Nissilä, Ilkka (2018)
    Caressing touch is an effective way to communicate emotions and to create social bonds. It is also one of the key mediators of early parental bonding. The caresses are generally thought to represent a social form of touching and indeed, slow, gentle brushing is encoded in specialized peripheral nerve fibers, the C-tactile (CT) afferents. In adults, areas such as the posterior insula and superior temporal sulcus are activated by affective, slow stroking touch but not by fast stroking stimulation. However, whether these areas are activated in infants, after social tactile stimulation, is unknown. In this study, we compared the total hemoglobin responses measured with diffuse optical tomography (DOT) in the left hemisphere following slow and fast stroking touch stimulation in 16 2-month-old infants. We compared slow stroking (optimal CT afferent stimulation) to fast stroking (non-optimal CT stimulation). Activated regions were delineated using two methods: one based on contrast between the two conditions, and the other based on voxel-based statistical significance of the difference between the two conditions. The first method showed a single activation cluster in the temporal cortex with center of gravity in the middle temporal gyrus where the total hemoglobin increased after the slow stroking relative to the fast stroking (p = 0.04 uncorrected). The second method revealed a cluster in the insula with an increase in total hemoglobin in the insular cortex in response to slow stroking relative to fast stroking (p = 0.0005 uncorrected; p = 0.04 corrected for multiple comparisons). These activation clusters encompass areas that are involved in processing of affective, slow stroking touch in the adult brain. We conclude that the infant brain shows a pronounced and adult-like response to slow stroking touch compared to fast stroking touch in the insular cortex but the expected response in the primary somatosensory cortex was not found at this age. The results imply that emotionally valent touch is encoded in the brain in adult-like manner already soon after birth and this suggests a potential for involvement of touch in bonding with the caretaker.
  • Moura, Fernando S.; Beraldo, Roberto G.; Ferreira, Leonardo A.; Siltanen, Samuli (2021)
    Objective. The objective of this work is to develop a 4D (3D+T) statistical anatomical atlas of the electrical properties of the upper part of the human head for cerebral electrophysiology and bioimpedance applications. Approach. The atlas was constructed based on 3D magnetic resonance images (MRI) of 107 human individuals and comprises the electrical properties of the main internal structures and can be adjusted for specific electrical frequencies. T1w+T2w MRI images were used to segment the main structures of the head while angiography MRI was used to segment the main arteries. The proposed atlas also comprises a time-varying model of arterial brain circulation, based on the solution of the Navier-Stokes equation in the main arteries and their vascular territories. Main results. High-resolution, multi-frequency and time-varying anatomical atlases of resistivity, conductivity and relative permittivity were created and evaluated using a forward problem solver for EIT. The atlas was successfully used to simulate electrical impedance tomography measurements indicating the necessity of signal-to-noise between 100 and 125 dB to identify vascular changes due to the cardiac cycle, corroborating previous studies. The source code of the atlas and solver are freely available to download. Significance. Volume conductor problems in cerebral electrophysiology and bioimpedance do not have analytical solutions for nontrivial geometries and require a 3D model of the head and its electrical properties for solving the associated PDEs numerically. Ideally, the model should be made with patient-specific information. In clinical practice, this is not always the case and an average head model is often used. Also, the electrical properties of the tissues might not be completely known due to natural variability. Anatomical atlases are important tools for in silico studies on cerebral circulation and electrophysiology that require statistically consistent data, e.g. machine learning, sensitivity analyses, and as a benchmark to test inverse problem solvers.
  • Webb, Lachlan; Kauppila, Minna; Roberts, James A.; Vanhatalo, Sampsa; Stevenson, Nathan J. (2021)
    Background and objective: To develop a computational algorithm that detects and identifies different arte-fact types in neonatal electroencephalography (EEG) signals. Methods: As part of a larger algorithm, we trained a Residual Deep Neural Network on expert human annotations of EEG recordings from 79 term infants recorded in a neonatal intensive care unit (112 h of 18-channel recording). The network was trained using 10 fold cross validation in Matlab. Artefact types included: device interference, EMG, movement, electrode pop, and non-cortical biological rhythms. Per-formance was assessed by prediction statistics and further validated on a separate independent dataset of 13 term infants (143 h of 3-channel recording). EEG pre-processing steps, and other post-processing steps such as averaging probability over a temporal window, were also included in the algorithm. Results: The Residual Deep Neural Network showed high accuracy (95%) when distinguishing periods of clean, artefact-free EEG from any kind of artefact, with a median accuracy for individual patient of 91% (IQR: 81%-96%). The accuracy in identifying the five different types of artefacts ranged from 57%-92%, with electrode pop being the hardest to detect and EMG being the easiest. This reflected the proportion of artefact available in the training dataset. Misclassification as clean was low for each artefact type, ranging from 1%-11%. The detection accuracy was lower on the validation set (87%). We used the algorithm to show that EEG channels located near the vertex were the least susceptible to artefact. Conclusion: Artefacts can be accurately and reliably identified in the neonatal EEG using a deep learning algorithm. Artefact detection algorithms can provide continuous bedside quality assessment and support EEG review by clinicians or analysis algorithms. (c) 2021 Elsevier B.V. All rights reserved.
  • Airaksinen, Manu; Räsänen, Okko; Ilen, Elina; Häyrinen, Taru; Tuiskula, Anna T; Marchi, Viviana; Gallen, Anastasia; Blom, Sonja; Varhe, Anni Maria; Kaartinen, Nico; Haataja, Leena Marjatta; Vanhatalo, Sampsa (2020)
    Infants' spontaneous and voluntary movements mirror developmental integrity of brain networks since they require coordinated activation of multiple sites in the central nervous system. Accordingly, early detection of infants with atypical motor development holds promise for recognizing those infants who are at risk for a wide range of neurodevelopmental disorders (e.g., cerebral palsy, autism spectrum disorders). Previously, novel wearable technology has shown promise for offering efficient, scalable and automated methods for movement assessment in adults. Here, we describe the development of an infant wearable, a multi-sensor smart jumpsuit that allows mobile accelerometer and gyroscope data collection during movements. Using this suit, we first recorded play sessions of 22 typically developing infants of approximately 7 months of age. These data were manually annotated for infant posture and movement based on video recordings of the sessions, and using a novel annotation scheme specifically designed to assess the overall movement pattern of infants in the given age group. A machine learning algorithm, based on deep convolutional neural networks (CNNs) was then trained for automatic detection of posture and movement classes using the data and annotations. Our experiments show that the setup can be used for quantitative tracking of infant movement activities with a human equivalent accuracy, i.e., it meets the human inter-rater agreement levels in infant posture and movement classification. We also quantify the ambiguity of human observers in analyzing infant movements, and propose a method for utilizing this uncertainty for performance improvements in training of the automated classifier. Comparison of different sensor configurations also shows that four-limb recording leads to the best performance in posture and movement classification.
  • Paukkunen, Mikko; Parkkila, Petteri; Hurnanen, Tero; Pankaala, Mikko; Koivisto, Tero; Nieminen, Tuomo; Kettunen, Raimo; Sepponen, Raimo (2016)
    The vibrations produced by the cardiovascular system that are coupled to the precordium can be noninvasively detected using accelerometers. This technique is called seismocardiography. Although clinical applications have been proposed for seismocardiography, the physiology underlying the signal is still not clear. The relationship of seismocardiograms of on the back-to-front axis and cardiac events is fairly well known. However, the 3-D seismocardiograms detectable with modern accelerometers have not been quantified in terms of cardiac cycle events. A major reason for this might be the degree of intersubject variability observed in 3-D seismocardiograms. We present a method to quantify 3-D seismocardiography in terms of cardiac cycle events. First, cardiac cycle events are identified from the seismocardiograms, and then, assigned a number based on the location in which the corresponding event was found. 396 cardiac cycle events from 9 healthy subjects and 120 cardiac cycle events from patients suffering from atrial flutter were analyzed. Despite the weak intersubject correlation of the waveforms (0.05, 0.27, and 0.15 for the x-, y-, and z-axes, respectively), the present method managed to find latent similarities in the seismocardiograms of healthy subjects. We observed that in healthy subjects the distribution of cardiac cycle event coordinates was centered on specific locations. These locations were different in patients with atrial flutter. The results suggest that spatial distribution of seismocardiographic cardiac cycle events might be used to discriminate healthy individuals and those with a failing heart.
  • Ahonen, Lauri; Cowley, Benjamin Ultan; Hellas, Arto; Puolamäki, Kai (2018)
    Collaboration is a complex phenomenon, where intersubjective dynamics can greatly affect the productive outcome. Evaluation of collaboration is thus of great interest, and can potentially help achieve better outcomes and performance. However, quantitative measurement of collaboration is difficult, because much of the interaction occurs in the intersubjective space between collaborators. Manual observation and/or self-reports are subjective, laborious, and have a poor temporal resolution. The problem is compounded in natural settings where task-activity and response-compliance cannot be controlled. Physiological signals provide an objective mean to quantify intersubjective rapport (as synchrony), but require novel methods to support broad deployment outside the lab. We studied 28 student dyads during a self-directed classroom pair-programming exercise. Sympathetic and parasympathetic nervous system activation was measured during task performance using electrodermal activity and electrocardiography. Results suggest that (a) we can isolate cognitive processes (mental workload) from confounding environmental effects, and (b) electrodermal signals show role-specific but correlated affective response profiles. We demonstrate the potential for social physiological compliance to quantify pair-work in natural settings, with no experimental manipulation of participants required. Our objective approach has a high temporal resolution, is scalable, non-intrusive, and robust.
  • Montazeri Moghadam, Saeed; Pinchefsky, Elana; Tse, Ilse; Marchi, Viviana; Kohonen, Jukka; Kauppila, Minna; Airaksinen, Manu; Tapani, Karoliina; Nevalainen, Päivi; Hahn, Cecil; W. Y. Tam, Emily; Stevenson, Nathan J.; Vanhatalo, Sampsa (2021)
    Neonatal brain monitoring in the neonatal intensive care units (NICU) requires a continuous review of the spontaneous cortical activity, i.e., the electroencephalograph (EEG) background activity. This needs development of bedside methods for an automated assessment of the EEG background activity. In this paper, we present development of the key components of a neonatal EEG background classifier, starting from the visual background scoring to classifier design, and finally to possible bedside visualization of the classifier results. A dataset with 13,200 5-minute EEG epochs (8–16 channels) from 27 infants with birth asphyxia was used for classifier training after scoring by two independent experts. We tested three classifier designs based on 98 computational features, and their performance was assessed with respect to scoring system, pre- and post-processing of labels and outputs, choice of channels, and visualization in monitor displays. The optimal solution achieved an overall classification accuracy of 97% with a range across subjects of 81–100%. We identified a set of 23 features that make the classifier highly robust to the choice of channels and missing data due to artefact rejection. Our results showed that an automated bedside classifier of EEG background is achievable, and we publish the full classifier algorithm to allow further clinical replication and validation studies.
  • Björkman, Kajsa; Mustonen, Harri; Kaprio, Tuomas; Kekki, Henna; Pettersson, Kim; Haglund, Caj; Böckelman, Camilla (2021)
    OBJECTIVES: The tumor stage represents the single most important prognostic factor for colorectal cancer (CRC), although more accurate prognostics remain much needed. Previously, we identified CA125 as an independent significant prognostic factor, which we have further validated along with CEA, CA19-9, and CA242 in a large cohort of CRC patients. METHODS: Using enzyme-linked immunosorbent assays, we analyzed preoperative serum samples in 322 CRC patients operated on between 1998 and 2003. RESULTS: Using the Spearman's rho model, we calculated the correlation between our previous findings on MUC16 and CA125, for which the correlation coefficient was 0.808 (p < 0.001). The Cox regression analysis of the linear and logarithmic values of CEA, CA125, CA242, and CA19-9 identified only CA125 (hazard ratio [HR] 1.03; 95% confidence interval [95% CI] 1.02-1.04; p < 0.001) as significant when using the linear values. Survival among CRC patients with a high CA125 level was poor compared with CRC patients with a low CA125 level (HR 2.48; 95% CI 1.68-3.65; p < 0.001). In subgroup analyses, patients with high CA125 levels and aged ≤67 or >67, with stage I-II or III-IV, and both colon and rectal cancer exhibited poor prognoses. In the multivariate analysis, we used clinical pathological variables in the model, where age, gender, and stage served as the background characteristics. We dichotomized CA125 using the Youden maximal cutoff point, and the median values for CEA, CA19-9, and CA242. CA125 emerged as the only marker remaining significant and independent together with stage, location, and age (HR 1.91; 95% CI 1.24-2.95; p 0.003). CONCLUSIONS: CA125 represents a significant and independent prognostic factor in CRC patients, superior to CEA. Furthermore, CA242 served as a better prognostic marker than both CEA and CA19-9. We recommend including both CA125 and CA242 in prognostic clinical trials among CRC patients.
  • Rasinkangas, Pia; Tytgat, Hanne L. P.; Ritari, Jarmo; Reunanen, Justus; Salminen, Seppo; Palva, Airi; Douillard, Francois P.; de Vos, Willem M. (2020)
    Lacticaseibacillus rhamnosusGG is one of the best studied lactic acid bacteria in the context of probiotic effects.L. rhamnosusGG has been shown to prevent diarrhea in children and adults and has been implicated to have mitigating or preventive effects in several disorders connected to microbiota dysbiosis. The probiotic effects are largely attributed to its adhesive heterotrimeric sortase-dependent pili, encoded by thespaCBA-srtC1gene cluster. Indeed, the strain-specific SpaCBA pili have been shown to contribute to adherence, biofilm formation and host signaling. In this work we set out to generate non-GMO derivatives ofL. rhamnosusGG that adhere stronger to mucus compared to the wild-type strain using chemical mutagenesis. We selected 13 derivatives that showed an increased mucus-adherent phenotype. Deep shotgun resequencing of the strains enabled division of the strains into three classes, two of which revealed SNPs (single nucleotide polymorphisms) in thespaAandspaCgenes encoding the shaft and tip adhesive pilins, respectively. Strikingly, the other class derivatives demonstrated less clear genotype - phenotype relationships, illustrating that pili biogenesis and structure is also affected by other processes. Further characterization of the different classes of derivatives was performed by PacBio SMRT sequencing and RNAseq analysis, which resulted in the identification of molecular candidates driving pilin biosynthesis and functionality. In conclusion, we report on the generation and characterization of three classes of strongly adherentL. rhamnosusGG derivatives that show an increase in adhesion to mucus. These are of special interest as they provide a window on processes and genes driving piliation and its control inL. rhamnosusGG and offer a variety of non-GMO derivatives of this key probiotic strain that are applicable in food products.
  • Yeung, Dennis; Guerra, Irene Mendez; Barner-Rasmussen, Ian; Siponen, Emilia; Farina, Dario; Vujaklija, Ivan (2022)
    Objective: In this work, we present a myoelectric interface that extracts natural motor synergies from multi-muscle signals and adapts in real-time with new user inputs. With this unsupervised adaptive myocontrol (UAM) system, optimal synergies for control are continuously co-adapted with changes in user motor control, or as a function of perturbed conditions via online non-negative matrix factorization guided by physiologically informed sparseness constraints in lieu of explicit data labelling. Methods: UAM was tested in a set of virtual target reaching tasks completed by able-bodied and amputee subjects. Tests were conducted under normative and electrode perturbed conditions to gauge control robustness with comparisons to non-adaptive and supervised adaptive myocontrol schemes. Furthermore, UAM was used to interface an amputee with a multi-functional powered hand prosthesis during standardized Clothespin Relocation Tests, also conducted in normative and perturbed conditions. Results: In virtual tests, UAM effectively mitigated performance degradation caused by electrode displacement, affording greater resilience over an existing supervised adaptive system for amputee subjects. Induced electrode shifts also had negligible effect on the real world control performance of UAM with consistent completion times (23.91 +/- 1.33 s) achieved across Clothespin Relocation Tests in the normative and electrode perturbed conditions. Conclusion: UAM affords comparable robustness improvements to existing supervised adaptive myocontrol interfaces whilst providing additional practical advantages for clinical deployment. Significance: The proposed system uniquely incorporates neuromuscular control principles with unsupervised online learning methods and presents a working example of a freely co-adaptive bionic interface.
  • Autio, Reija; Kilpinen, Sami; Saarela, Matti; Kallioniemi, Olli; Hautaniemi, Sampsa; Astola, Jaakko (2009)
  • Akmal, Jan Sher; Salmi, Mika; Hemming, Björn; Teir, Linus; Suomalainen, Anni; Kortesniemi, Mika; Partanen, Jouni; Lassila, Antti (2020)
    Featured Application Accuracy of additively manufactured implants for clinical surgery. Abstract In craniomaxillofacial surgical procedures, an emerging practice adopts the preoperative virtual planning that uses medical imaging (computed tomography), 3D thresholding (segmentation), 3D modeling (digital design), and additive manufacturing (3D printing) for the procurement of an end-use implant. The objective of this case study was to evaluate the cumulative spatial inaccuracies arising from each step of the process chain when various computed tomography protocols and thresholding values were independently changed. A custom-made quality assurance instrument (Phantom) was used to evaluate the medical imaging error. A sus domesticus (domestic pig) head was analyzed to determine the 3D thresholding error. The 3D modeling error was estimated from the computer-aided design software. Finally, the end-use implant was used to evaluate the additive manufacturing error. The results were verified using accurate measurement instruments and techniques. A worst-case cumulative error of 1.7 mm (3.0%) was estimated for one boundary condition and 2.3 mm (4.1%) for two boundary conditions considering the maximum length (56.9 mm) of the end-use implant. Uncertainty from the clinical imaging to the end-use implant was 0.8 mm (1.4%). This study helps practitioners establish and corroborate surgical practices that are within the bounds of an appropriate accuracy for clinical treatment and restoration.
  • Leino, Akseli; Korkalainen, Henri; Kalevo, Laura; Nikkonen, Sami; Kainulainen, Samu; Ryan, Alexander; Duce, Brett; Sipila, Kirsi; Ahlberg, Jari; Sahlman, Johanna; Miettinen, Tomi; Westeren-Punnonen, Susanna; Mervaala, Esa; Toyras, Juha; Myllymaa, Sami; Leppanen, Timo; Myllymaa, Katja (2022)
    We have previously developed an ambulatory electrode set (AES) for the measurement of electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG). The AES has been proven to be suitable for manual sleep staging and self-application in in-home polysomnography (PSG). To further facilitate the diagnostics of various sleep disorders, this study aimed to utilize a deep learning-based automated sleep staging approach for EEG signals acquired with the AES. The present neural network architecture comprises a combination of convolutional and recurrent neural networks previously shown to achieve excellent sleep scoring accuracy with a single standard EEG channel (F4-M1). In this study, the model was re-trained and tested with 135 EEG signals recorded with AES. The recordings were conducted for subjects suspected of sleep apnea or sleep bruxism. The performance of the deep learning model was evaluated with 10-fold cross-validation using manual scoring of the AES signals as a reference. The accuracy of the neural network sleep staging was 79.7% (kappa = 0.729) for five sleep stages (W, N1, N2, N3, and R), 84.1% (kappa = 0.773) for four sleep stages (W, light sleep, deep sleep, R), and 89.1% (kappa = 0.801) for three sleep stages (W, NREM, R). The utilized neural network was able to accurately determine sleep stages based on EEG channels measured with the AES. The accuracy is comparable to the inter-scorer agreement of standard EEG scorings between international sleep centers. The automatic AES-based sleep staging could potentially improve the availability of PSG studies by facilitating the arrangement of self-administrated in-home PSGs.
  • Worm, A.-M.; Sinisalo, H.; Eilertsen, G.; Ahren, E.; Meyer, I. (2018)
    Background: The art of producing and acquiring dermatological wax models, moulages, flourished all over Europe in the beginning of the twentieth century, whereas very little is known about the existence of moulage collections in the Nordic countries. Objective: The aim of this study was to elucidate the presence, the origin, the production place, the use and the condition of dermatological moulage collections in the Nordic countries. Methods: In each Nordic country, an extensive survey was undertaken during spring 2016. Dermatological departments, museums with medical collections, persons assumed to have specific information about wax moulages as well as secondary sources were contacted and interviewed. ResultsSeveral hitherto undescribed collections have survived in each country, most, however, damaged and in disrepair. One Danish and part of a Finnish collection have been restored. Only few moulages are exhibited and some have been photographed and digitalized. Denmark and Sweden have had a local moulage production. Responses to the survey indicate that the result covers all collections of dermatological moulages in the Nordic countries, though some moulages may remain in private collections unknown to the authors, or uncatalogued in museums. Conclusion: Moulages are medical gems from bygone days before modern technology facilitated new means of communication. Restoration and appropriate storing should be considered for at least selected items from the Nordic collections.
  • Ajdary, Rubina; Reyes, Guillermo; Kuula, Jani; Raussi-Lehto, Eija; Mikkola, Tomi S.; Kankuri, Esko; Rojas, Orlando J. (2022)
    Direct ink writing via single or multihead extrusion is used to synthesize layer-by-layer (LbL) meshes comprising renewable polysaccharides. The best mechanical performance (683 ± 63 MPa modulus and 2.5 ± 0.4 MPa tensile strength) is observed for 3D printed structures with full infill density, given the role of electrostatic complexation between the oppositely charged components (chitosan and cellulose nanofibrils). The LbL structures develop an unexpectedly high wet stability that undergoes gradual weight loss at neutral and slightly acidic pH. The excellent biocompatibility and noncytotoxicity toward human monocyte/macrophages and controllable shrinkage upon solvent exchange make the cellular meshes appropriate for use as biomedical implants.
  • Aalto-Setälä, Laura; Uppstu, Peter; Sinitsyna, Polina; Lindfors, Nina C.; Hupa, Leena (2021)
    The silicate-based bioactive glass S53P4 is clinically used in bone regenerative applications in granule form. However, utilization of the glass in scaffold form has been limited by the high tendency of the glass to crystallize during sintering. Here, careful optimization of sintering parameters enabled the manufacture of porous amorphous S53P4 scaffolds with a strength high enough for surgical procedures in bone applications (5 MPa). Sintering was conducted in a laboratory furnace for times ranging from 25 to 300 min at 630 degrees C, i.e., narrowly below the commencement of the crystallization. The phase composition of the scaffolds was verified with XRD, and the ion release was tested in vitro and compared with granules in continuous flow of Tris buffer and simulated body fluid (SBF). The amorphous, porous S53P4 scaffolds present the possibility of using the glass composition in a wider range of applications.