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6. Spectral induced polarization imaging to monitor seasonal and annual dynamics of frozen ground at a mountain permafrost site in the Italian Alps

Author

T. Maierhofer, A. Flores Orozco, N. Roser, J. K. Limbrock, C. Hilbich, C. Moser, A. Kemna, E. Drigo, U. Morra di Cella, and C. Hauck

Subjects
Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract

We investigate the application of spectral induced polarization (SIP) monitoring to understand seasonal and annual variations in the freeze–thaw processes in permafrost by examining the frequency dependence of subsurface electrical properties. We installed a permanent SIP monitoring profile at a high-mountain permafrost site in the Italian Alps in 2019 and collected SIP data in the frequency range between 0.1–75 Hz over 3 years. The SIP imaging results were interpreted in conjunction with complementary seismic and borehole data sets. In particular, we investigated the phase frequency effect (ϕFE), i.e., the change in the resistivity phase with frequency. We observe that this parameter (ϕFE) is strongly sensitive to temperature changes and might be used as a proxy to delineate spatial and temporal changes in the ice content in the subsurface, providing information not accessible through electrical resistivity tomography (ERT) or single-frequency IP measurements. Temporal changes in ϕFE are validated through laboratory SIP measurements on samples from the site in controlled freeze–thaw experiments. We demonstrate that SIP is capable of resolving temporal changes in the thermal state and the ice / water ratio associated with seasonal freeze–thaw processes. We investigate the consistency between the ϕFE observed in field data and groundwater and ice content estimates derived from petrophysical modeling of ERT and seismic data.

Published
2024
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7. Predictors of symptom change in the mental health of refugees and asylum seekers (MEHIRA) study examining the effects of a stepped and collaborative care model – A multicentered rater-blinded randomized controlled trial

Author

Kemna, Solveig, Bringmann, Max, Karnouk, Carine, Hoell, Andreas, Tschorn, Mira, Kamp-Becker, Inge, Padberg, Frank, Übleis, Aline, Hasan, Alkomiet, Falkai, Peter, Salize, Hans-Joachim, Meyer-Lindenberg, Andreas, Banaschewski, Tobias, Schneider, Frank, Habel, Ute, Plener, Paul, Hahn, Eric, Wiechers, Maren, Strupf, Michael, Jobst, Andrea, Millenet, Sabina, Hoehne, Edgar, Sukale, Thorsten, Schuster, Martin, Dinauer, Raphael, Mehran, Nassim, Kaiser, Franziska, Lieb, Klaus, Heinz, Andreas, Rapp, Michael, Bajbouj, Malek, and Böge, Kerem

Published
2025
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9. Mental health literacy and the public perception of persons with depression and schizophrenia in Vietnam

Author

Mahan Mobashery, Thi Minh Tam Ta, Duc Tien Cao, Kerem Böge, Luisa Eilinghoff, Van Phi Nguyen, Selin Mavituna, Lukas Fuchs, Sebastian Weyn-Banningh, Solveig Kemna, Malek Bajbouj, and Eric Hahn

Subjects
schizophrenia, depression, Vietnam, causal beliefs, stigma and awareness, mental health literacy, Psychiatry, RC435-571
Abstract

BackgroundVietnam’s mental health care system is undergoing significant changes since the government has initiated large-scale programs to reform and develop the mental health care infrastructure. Cultural belief systems on mental illnesses influence help-seeking behavior and compliance. This study investigates the belief systems about people with schizophrenia and depression among people living in the Hanoi area.Method1077 Vietnamese participants answered two open-ended questions after reading an unlabeled vignette describing a character with the symptoms of schizophrenia or depression. The answers were analyzed using thematic analysis.ResultsOf all participants, 88,4% associated the presented cases with a mental illness, with 91,5% in the case of schizophrenia and 85,1% in the case of depression, so both disorders were conceptualized as mental illnesses. 18,6% mentioned depression when presented with the depression vignette, while only 3,6% recognized schizophrenia in the schizophrenia condition.ConclusionsAlmost 9 out of 10 participants considered the presented cases as an example of mental illness, suggesting a high mental health awareness among our participants. The majority did not identify the presented cases as examples of schizophrenia or depression, reflecting little familiarity with Western mental health concepts. It could be interpreted as a sign of relatively low mental health literacy among the study participants.

Published
2024
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14. Management of immune thrombotic thrombocytopenic purpura without therapeutic plasma exchange

Author

Albert, Annemarie, Bramstedt, Jörn, Brand, Marcus, Brinkkötter, Paul T., Cukoski, Sadrija, Eichenauer, Dennis A., Elitok, Saban, Felten, Helmut, Gäckler, Anja, Geuther, Gesa, Harth, Ana, Hausberg, Martin, Hermann, Matthias, Hinkel, Ulrich P., Jabs, Wolfram Johannes, Kaufeld, Jessica, Klein, Gilles, Klemm, Kristin, Kolbrink, Benedikt, Kühne, Lucas, Menne, Jan, Miesbach, Wolfgang, Mühlfeld, Anja Susanne, Özcan, Fedai, Osterholt, Thomas, Pfrepper, Christian, Potthoff, Sebastian A., Radermacher, Jörg, Ruhe, Johannes, Schmidt, Tilman, Schönermarck, Ulf, Schönfelder, Kristina, Schreiber, Adrian, Schulte, Kevin, Schulte-Kemna, Lena, Schwenger, Vedat, Seelow, Evelyn, Seibert, Felix S., Todorova, Polina, Tölle - Charité, Markus, Völker, Linus A., Walendy, Victor, Wendt, Ralph, Westhoff, Timm H., Knöbl, Paul, Eller, Kathrin, Thaler, Johannes, Sperr, Wolfgang R., Gleixner, Karoline, Buxhofer-Ausch, Veronika, Mühlfeld, Anja, Jabs, Wolfram J., Westhoff, Timm, and Brinkkoetter, Paul T.

Published
2024
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15. Trajectories of postoperative serum troponin concentrations following pediatric heart transplantation

Author

Alexander J. Kula, Erin Albers, Bora Hong, Mariska Kemna, Joshua Friedland-Little, and Yuk Law

Subjects
pediatric heart transplant, biomarkers, troponin, epidemiology, outcomes research, Surgery, RD1-811, Specialties of internal medicine, RC581-951
Abstract

Background: Troponin is a biomarker of myocardial injury and death but has not been well studied after pediatric heart transplants. The objective of this analysis is to describe the distribution and clinical determinants of serum troponin measured in the first week after pediatric heart transplantation. Methods: We included all patients who underwent heart transplantation at Seattle Children’s Hospital between 2012 and 2016. Serum Troponin-I (TnI) was measured daily in the first week after transplant. We described the distribution of serum TnI, and examined the relationship between peak TnI with known pre- peri-operative risk factors for myocardial injury including etiology of heart failure, ischemia time, and donor to recipient characteristics. Logistic regression models were used to test the association between peak TnI with incidence of death or rejection and formation of donor-specific antibodies (DSA) within 1 year. Adjusted models included age, HF etiology, crossmatch status, and panel reactive antibodies. Results: During the study period, 86 transplants were performed on 83 unique individuals. Serum TnI peaked at a median of 0.9 days after transplantation. In adjusted models, higher peak TnI was associated with death and/or rejection within 1-year post-transplant (odds ratio [95% confidence interval]: 1.10 [1.02, 1.19]). Peak TnI was not associated with de-novo DSA formation in adjusted models (OR [95%CI]: 1.01 [0.94, 1.09]). Post-transplant length of stay in the intensive care unit was positively correlated with peak TnI (r = 0.36, p

Published
2024
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16. Potential role of B- and NK-cells in the pathogenesis of pediatric aplastic anemia through deep phenotyping

Author

Lotte T. W. Vissers, Monique M. van Ostaijen-ten Dam, Janine E. Melsen, Yanna M. van der Spek, Koen P. Kemna, Arjan C. Lankester, Mirjam van der Burg, and Alexander B. Mohseny

Subjects
aplastic anemia, pediatric, B-cells, natural killer cells, flow cytometry, bone marrow, Immunologic diseases. Allergy, RC581-607
Abstract

IntroductionPediatric patients with unexplained bone marrow failure (BMF) are often categorized as aplastic anemia (AA). Based on the accepted hypothesis of an auto-immune mechanism underlying AA, immune suppressive therapy (IST) might be effective. However, due to the lack of diagnostic tools to identify immune AA and prognostic markers to predict IST response together with the unequaled curative potential of hematopoietic stem cell transplantation (HSCT), most pediatric severe AA patients are momentarily treated by HSCT if available. Although several studies indicate oligoclonal T-cells with cytotoxic activities towards the hematopoietic stem cells, increasing evidence points towards defective inhibitory mechanisms failing to inhibit auto-reactive T-cells.MethodsWe aimed to investigate the role of NK- and B-cells in seven pediatric AA patients through a comprehensive analysis of paired bone marrow and peripheral blood samples with spectral flow cytometry in comparison to healthy age-matched bone marrow donors. ResultsWe observed a reduced absolute number of NK-cells in peripheral blood of AA patients with a skewed distribution towards CD56bright NK-cells in a subgroup of patients. The enriched CD56bright NK-cells had a lower expression of CD45RA and TIGIT and a higher expression of CD16, compared to healthy donors. Functional analysis revealed no differences in degranulation. However, IFN-γ production and perforin expression of NK-cells were reduced in the CD56bright-enriched patient group. The diminished NK-cell function in this subgroup might underly the auto-immunity. Importantly, NK-function of AA patients with reduced CD56bright NK-cells was comparable to healthy donors. Also, B-cell counts were lower in AA patients. Subset analysis revealed a trend towards reduction of transitional B-cells in both absolute and relative numbers compared to healthy controls. As these cells were previously hypothesized as regulatory cells in AA, decreased numbers might be involved in defective inhibition of auto-reactive T-cells. Interestingly, even in patients with normal distribution of precursor B-cells, the transitional compartment was reduced, indicating partial differentiation failure from immature to transitional B-cells or a selective loss. DiscussionOur findings provide a base for future studies to unravel the role of transitional B-cells and CD56bright NK-cells in larger cohorts of pediatric AA patients as diagnostic markers for immune AA and targets for therapeutic interventions.

Published
2024
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17. Deep learning models for automatic tumor segmentation and total tumor volume assessment in patients with colorectal liver metastases

Author

Nina J. Wesdorp, J. Michiel Zeeuw, Sam C. J. Postma, Joran Roor, Jan Hein T. M. van Waesberghe, Janneke E. van den Bergh, Irene M. Nota, Shira Moos, Ruby Kemna, Fijoy Vadakkumpadan, Courtney Ambrozic, Susan van Dieren, Martinus J. van Amerongen, Thiery Chapelle, Marc R. W. Engelbrecht, Michael F. Gerhards, Dirk Grunhagen, Thomas M. van Gulik, John J. Hermans, Koert P. de Jong, Joost M. Klaase, Mike S. L. Liem, Krijn P. van Lienden, I. Quintus Molenaar, Gijs A. Patijn, Arjen M. Rijken, Theo M. Ruers, Cornelis Verhoef, Johannes H. W. de Wilt, Henk A. Marquering, Jaap Stoker, Rutger-Jan Swijnenburg, Cornelis J. A. Punt, Joost Huiskens, and Geert Kazemier

Subjects
Artificial intelligence, Deep learning, Colorectal cancer, Liver neoplasms, Tomography (x-ray computed), Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Background We developed models for tumor segmentation to automate the assessment of total tumor volume (TTV) in patients with colorectal liver metastases (CRLM). Methods In this prospective cohort study, pre- and post-systemic treatment computed tomography (CT) scans of 259 patients with initially unresectable CRLM of the CAIRO5 trial (NCT02162563) were included. In total, 595 CT scans comprising 8,959 CRLM were divided into training (73%), validation (6.5%), and test sets (21%). Deep learning models were trained with ground truth segmentations of the liver and CRLM. TTV was calculated based on the CRLM segmentations. An external validation cohort was included, comprising 72 preoperative CT scans of patients with 112 resectable CRLM. Image segmentation evaluation metrics and intraclass correlation coefficient (ICC) were calculated. Results In the test set (122 CT scans), the autosegmentation models showed a global Dice similarity coefficient (DSC) of 0.96 (liver) and 0.86 (CRLM). The corresponding median per-case DSC was 0.96 (interquartile range [IQR] 0.95–0.96) and 0.80 (IQR 0.67–0.87). For tumor segmentation, the intersection-over-union, precision, and recall were 0.75, 0.89, and 0.84, respectively. An excellent agreement was observed between the reference and automatically computed TTV for the test set (ICC 0.98) and external validation cohort (ICC 0.98). In the external validation, the global DSC was 0.82 and the median per-case DSC was 0.60 (IQR 0.29–0.76) for tumor segmentation. Conclusions Deep learning autosegmentation models were able to segment the liver and CRLM automatically and accurately in patients with initially unresectable CRLM, enabling automatic TTV assessment in such patients. Relevance statement Automatic segmentation enables the assessment of total tumor volume in patients with colorectal liver metastases, with a high potential of decreasing radiologist’s workload and increasing accuracy and consistency. Key points • Tumor response evaluation is time-consuming, manually performed, and ignores total tumor volume. • Automatic models can accurately segment tumors in patients with colorectal liver metastases. • Total tumor volume can be accurately calculated based on automatic segmentations. Graphical Abstract

Published
2023
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18. Prognostic value of total tumor volume in patients with colorectal liver metastases: A secondary analysis of the randomized CAIRO5 trial with external cohort validation

Author

Michiel Zeeuw, J., Wesdorp, Nina J., Ali, Mahsoem, Bakker, Anne-Joëlle J.J., Voigt, Kelly R., Starmans, Martijn P.A., Roor, Joran, Kemna, Ruby, van Waesberghe, Jan Hein T.M., van den Bergh, Janneke E., Nota, Irene M.G.C., Moos, Shira I., van Dieren, Susan, van Amerongen, Martinus J., Bond, Marinde J.G., Chapelle, Thiery, van Dam, Ronald M., Engelbrecht, Marc R.W., Gerhards, Michael F., van Gulik, Thomas M., Hermans, John J., de Jong, Koert P., Klaase, Joost M., Kok, Niels F.M., Leclercq, Wouter K.G., Liem, Mike S.L., van Lienden, Krijn P., Quintus Molenaar, I., Patijn, Gijs A., Rijken, Arjen M., Ruers, Theo M., de Wilt, Johannes H.W., Verpalen, Inez M., Stoker, Jaap, Grunhagen, Dirk J., Swijnenburg, Rutger-Jan, Punt, Cornelis J.A., Huiskens, Joost, Verhoef, Cornelis, and Kazemier, Geert

Published
2024
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20. Mental health assessment during the full-scale invasion within the general Ukrainian population: state, beliefs and behaviors, query to change (cross-sectional study)

Author

Y. Korniiko, M. Bajbouj, K. J. Jonas, J. Mueller, and S. Kemna

Subjects
Psychiatry, RC435-571
Abstract

Introduction The russian invasion in Ukraine has significantly affected the mental health (MH) of the local population while access to mental health support remains limited due to multiple reasons coming from both the provider and acceptor sides. The war obviously negatively impacts MH but has also paradoxically given an “open window” for shifting current practices both in the healthcare system and within society. Investigation of current people’s attitudes on this matter should be the primary step to address the issue and initiate any change. Objectives 5 main objectives identified to analyze within the convenience sample were: MH state and self-care behaviors during the full-scale invasion, MH stigma and self-stigma, intention to use professional MH support, beliefs on access to professional MH support, query to change current MH attitudes and practices. Methods This research was conducted using primary data collection. The online questionnaire consisted of 5 blocks and was designed based on PHQ-9, DASS-21, PCL-5, Brief-COPE and CAMI. 332 civilians underwent the survey in March-April 2023 and were divided by age, gender, location and situation; inclusion criteria were to be >16 y.o. being affected by war and capable of completing the survey in Ukrainian. Relevant ethical measures were applied. Descriptive and correlational analysis was used to analyze the data. Results The majority of respondents rated their mental health as good. Anxiety was the most prevalent emotion, particularly among younger age groups. Different genders and age groups exhibited varying combinations of emotions, such as fatigue, peace, anger, sadness etc. Many participants felt self-reproach for not doing enough; coping strategies varied among age groups. Females were 8.14 times more likely to seek mental health support, and those inside Ukraine were 0.32 times less inclined. 66.2% never seek any MH services, with older men leading; only 8.7% consult specialists during crises, showing gender differences. Distrust in specialist qualifications is one of the barriers on access in people’s beliefs and is more prevalent among older generations. The absence of self-mental health stigma makes individuals 1.91 times more open to accessing support. Location affects openness to change, with Ukraine-based individuals being less open. Lastly, 29.5% consider alternative stress-coping methods, with 40% open to future psychological help. Conclusions Our findings show differences in populational attitudes towards MH in Ukraine during the war and therefore the importance of any potential intervention to precisely tailor certain subgroups, beliefs behaviors and needs within them to have a higher chance of being accepted and increase MH support utilization in the population overall. Disclosure of Interest None Declared

Published
2024
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21. Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial

Author

Staplin, N, Haynes, R, Judge, PK, Wanner, C, Green, JB, Emberson, J, Preiss, D, Mayne, KJ, Ng, SYA, Sammons, E, Zhu, D, Hill, M, Stevens, W, Wallendszus, K, Brenner, S, Cheung, AK, Liu, ZH, Li, J, Hooi, LS, Liu, WJ, Kadowaki, T, Nangaku, M, Levin, A, Cherney, D, Maggioni, AP, Pontremoli, R, Deo, R, Goto, S, Rossello, X, Tuttle, KR, Steubl, D, Petrini, M, Seidi, S, Landray, MJ, Baigent, C, Herrington, WG, Abat, S, Abd Rahman, R, Abdul Cader, R, Abdul Hafidz, MI, Abdul Wahab, MZ, Abdullah, NK, Abdul-Samad, T, Abe, M, Abraham, N, Acheampong, S, Achiri, P, Acosta, JA, Adeleke, A, Adell, V, Adewuyi-Dalton, R, Adnan, N, Africano, A, Agharazii, M, Aguilar, F, Aguilera, A, Ahmad, M, Ahmad, MK, Ahmad, NA, Ahmad, NH, Ahmad, NI, Ahmad Miswan, N, Ahmad Rosdi, H, Ahmed, I, Ahmed, S, Aiello, J, Aitken, A, AitSadi, R, Aker, S, Akimoto, S, Akinfolarin, A, Akram, S, Alberici, F, Albert, C, Aldrich, L, Alegata, M, Alexander, L, Alfaress, S, Alhadj Ali, M, Ali, A, Alicic, R, Aliu, A, Almaraz, R, Almasarwah, R, Almeida, J, Aloisi, A, Al-Rabadi, L, Alscher, D, Alvarez, P, Al-Zeer, B, Amat, M, Ambrose, C, Ammar, H, An, Y, Andriaccio, L, Ansu, K, Apostolidi, A, Arai, N, Araki, H, Araki, S, Arbi, A, Arechiga, O, Armstrong, S, Arnold, T, Aronoff, S, Arriaga, W, Arroyo, J, Arteaga, D, Asahara, S, Asai, A, Asai, N, Asano, S, Asawa, M, Asmee, MF, Aucella, F, Augustin, M, Avery, A, Awad, A, Awang, IY, Awazawa, M, Axler, A, Ayub, W, Azhari, Z, Baccaro, R, Badin, C, Bagwell, B, Bahlmann-Kroll, E, Bahtar, AZ, Bains, D, Bajaj, H, Baker, R, Baldini, E, Banas, B, Banerjee, D, Banno, S, Bansal, S, Barberi, S, Barnes, S, Barnini, C, Barot, C, Barrett, K, Barrios, R, Bartolomei Mecatti, B, Barton, I, Barton, J, Basily, W, Bavanandan, S, Baxter, A, Becker, L, Beddhu, S, Beige, J, Beigh, S, Bell, S, Benck, U, Beneat, A, Bennett, A, Bennett, D, Benyon, S, Berdeprado, J, Bergler, T, Bergner, A, Berry, M, Bevilacqua, M, Bhairoo, J, Bhandari, S, Bhandary, N, Bhatt, A, Bhattarai, M, Bhavsar, M, Bian, W, Bianchini, F, Bianco, S, Bilous, R, Bilton, J, Bilucaglia, D, Bird, C, Birudaraju, D, Biscoveanu, M, Blake, C, Bleakley, N, Bocchicchia, K, Bodine, S, Bodington, R, Boedecker, S, Bolduc, M, Bolton, S, Bond, C, Boreky, F, Boren, K, Bouchi, R, Bough, L, Bovan, D, Bowler, C, Bowman, L, Brar, N, Braun, C, Breach, A, Breitenfeldt, M, Brettschneider, B, Brewer, A, Brewer, G, Brindle, V, Brioni, E, Brown, C, Brown, H, Brown, L, Brown, R, Brown, S, Browne, D, Bruce, K, Brueckmann, M, Brunskill, N, Bryant, M, Brzoska, M, Bu, Y, Buckman, C, Budoff, M, Bullen, M, Burke, A, Burnette, S, Burston, C, Busch, M, Bushnell, J, Butler, S, Büttner, C, Byrne, C, Caamano, A, Cadorna, J, Cafiero, C, Cagle, M, Cai, J, Calabrese, K, Calvi, C, Camilleri, B, Camp, S, Campbell, D, Campbell, R, Cao, H, Capelli, I, Caple, M, Caplin, B, Cardone, A, Carle, J, Carnall, V, Caroppo, M, Carr, S, Carraro, G, Carson, M, Casares, P, Castillo, C, Castro, C, Caudill, B, Cejka, V, Ceseri, M, Cham, L, Chamberlain, A, Chambers, J, Chan, CBT, Chan, JYM, Chan, YC, Chang, E, Chant, T, Chavagnon, T, Chellamuthu, P, Chen, F, Chen, J, Chen, P, Chen, TM, Chen, Y, Cheng, C, Cheng, H, Cheng, MC, Ching, CH, Chitalia, N, Choksi, R, Chukwu, C, Chung, K, Cianciolo, G, Cipressa, L, Clark, S, Clarke, H, Clarke, R, Clarke, S, Cleveland, B, Cole, E, Coles, H, Condurache, L, Connor, A, Convery, K, Cooper, A, Cooper, N, Cooper, Z, Cooperman, L, Cosgrove, L, Coutts, P, Cowley, A, Craik, R, Cui, G, Cummins, T, Dahl, N, Dai, H, Dajani, L, D'Amelio, A, Damian, E, Damianik, K, Danel, L, Daniels, C, Daniels, T, Darbeau, S, Darius, H, Dasgupta, T, Davies, J, Davies, L, Davis, A, Davis, J, Davis, L, Dayanandan, R, Dayi, S, Dayrell, R, De Nicola, L, Debnath, S, Deeb, W, Degenhardt, S, DeGoursey, K, Delaney, M, DeRaad, R, Derebail, V, Dev, D, Devaux, M, Dhall, P, Dhillon, G, Dienes, J, Dobre, M, Doctolero, E, Dodds, V, Domingo, D, Donaldson, D, Donaldson, P, Donhauser, C, Donley, V, Dorestin, S, Dorey, S, Doulton, T, Draganova, D, Draxlbauer, K, Driver, F, Du, H, Dube, F, Duck, T, Dugal, T, Dugas, J, Dukka, H, Dumann, H, Durham, W, Dursch, M, Dykas, R, Easow, R, Eckrich, E, Eden, G, Edmerson, E, Edwards, H, Ee, LW, Eguchi, J, Ehrl, Y, Eichstadt, K, Eid, W, Eilerman, B, Ejima, Y, Eldon, H, Ellam, T, Elliott, L, Ellison, R, Epp, R, Er, A, Espino-Obrero, M, Estcourt, S, Estienne, L, Evans, G, Evans, J, Evans, S, Fabbri, G, Fajardo-Moser, M, Falcone, C, Fani, F, Faria-Shayler, P, Farnia, F, Farrugia, D, Fechter, M, Fellowes, D, Feng, F, Fernandez, J, Ferraro, P, Field, A, Fikry, S, Finch, J, Finn, H, Fioretto, P, Fish, R, Fleischer, A, Fleming-Brown, D, Fletcher, L, Flora, R, Foellinger, C, Foligno, N, Forest, S, Forghani, Z, Forsyth, K, Fottrell-Gould, D, Fox, P, Frankel, A, Fraser, D, Frazier, R, Frederick, K, Freking, N, French, H, Froment, A, Fuchs, B, Fuessl, L, Fujii, H, Fujimoto, A, Fujita, A, Fujita, K, Fujita, Y, Fukagawa, M, Fukao, Y, Fukasawa, A, Fuller, T, Funayama, T, Fung, E, Furukawa, M, Furukawa, Y, Furusho, M, Gabel, S, Gaidu, J, Gaiser, S, Gallo, K, Galloway, C, Gambaro, G, Gan, CC, Gangemi, C, Gao, M, Garcia, K, Garcia, M, Garofalo, C, Garrity, M, Garza, A, Gasko, S, Gavrila, M, Gebeyehu, B, Geddes, A, Gentile, G, George, A, George, J, Gesualdo, L, Ghalli, F, Ghanem, A, Ghate, T, Ghavampour, S, Ghazi, A, Gherman, A, Giebeln-Hudnell, U, Gill, B, Gillham, S, Girakossyan, I, Girndt, M, Giuffrida, A, Glenwright, M, Glider, T, Gloria, R, Glowski, D, Goh, BL, Goh, CB, Gohda, T, Goldenberg, R, Goldfaden, R, Goldsmith, C, Golson, B, Gonce, V, Gong, Q, Goodenough, B, Goodwin, N, Goonasekera, M, Gordon, A, Gordon, J, Gore, A, Goto, H, Gowen, D, Grace, A, Graham, J, Grandaliano, G, Gray, M, Greene, T, Greenwood, G, Grewal, B, Grifa, R, Griffin, D, Griffin, S, Grimmer, P, Grobovaite, E, Grotjahn, S, Guerini, A, Guest, C, Gunda, S, Guo, B, Guo, Q, Haack, S, Haase, M, Haaser, K, Habuki, K, Hadley, A, Hagan, S, Hagge, S, Haller, H, Ham, S, Hamal, S, Hamamoto, Y, Hamano, N, Hamm, M, Hanburry, A, Haneda, M, Hanf, C, Hanif, W, Hansen, J, Hanson, L, Hantel, S, Haraguchi, T, Harding, E, Harding, T, Hardy, C, Hartner, C, Harun, Z, Harvill, L, Hasan, A, Hase, H, Hasegawa, F, Hasegawa, T, Hashimoto, A, Hashimoto, C, Hashimoto, M, Hashimoto, S, Haskett, S, Hauske, SJ, Hawfield, A, Hayami, T, Hayashi, M, Hayashi, S, Hazara, A, Healy, C, Hecktman, J, Heine, G, Henderson, H, Henschel, R, Hepditch, A, Herfurth, K, Hernandez, G, Hernandez Pena, A, Hernandez-Cassis, C, Herzog, C, Hewins, S, Hewitt, D, Hichkad, L, Higashi, S, Higuchi, C, Hill, C, Hill, L, Himeno, T, Hing, A, Hirakawa, Y, Hirata, K, Hirota, Y, Hisatake, T, Hitchcock, S, Hodakowski, A, Hodge, W, Hogan, R, Hohenstatt, U, Hohenstein, B, Hooi, L, Hope, S, Hopley, M, Horikawa, S, Hosein, D, Hosooka, T, Hou, L, Hou, W, Howie, L, Howson, A, Hozak, M, Htet, Z, Hu, X, Hu, Y, Huang, J, Huda, N, Hudig, L, Hudson, A, Hugo, C, Hull, R, Hume, L, Hundei, W, Hunt, N, Hunter, A, Hurley, S, Hurst, A, Hutchinson, C, Hyo, T, 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2024
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22. Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

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Judge, PK, Staplin, N, Mayne, KJ, Wanner, C, Green, JB, Hauske, SJ, Emberson, JR, Preiss, D, Ng, SYA, Roddick, AJ, Sammons, E, Zhu, D, Hill, M, Stevens, W, Wallendszus, K, Brenner, S, Cheung, AK, Liu, ZH, Li, J, Hooi, LS, Liu, WJ, Kadowaki, T, Nangaku, M, Levin, A, Cherney, D, Maggioni, AP, Pontremoli, R, Deo, R, Goto, S, Rossello, X, Tuttle, KR, Steubl, D, Massey, D, Landray, MJ, Baigent, C, Haynes, R, Herrington, WG, Abat, S, Abd Rahman, R, Abdul Cader, R, Abdul Hafidz, MI, Abdul Wahab, MZ, Abdullah, NK, Abdul-Samad, T, Abe, M, Abraham, N, Acheampong, S, Achiri, P, Acosta, JA, Adeleke, A, Adell, V, Adewuyi-Dalton, R, Adnan, N, Africano, A, Agharazii, M, Aguilar, F, Aguilera, A, Ahmad, M, Ahmad, MK, Ahmad, NA, Ahmad, NH, Ahmad, NI, Ahmad Miswan, N, Ahmad Rosdi, H, Ahmed, I, Ahmed, S, Aiello, J, Aitken, A, AitSadi, R, Aker, S, Akimoto, S, Akinfolarin, A, Akram, S, Alberici, F, Albert, C, Aldrich, L, Alegata, M, Alexander, L, Alfaress, S, Alhadj Ali, M, Ali, A, Alicic, R, Aliu, A, 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Tanabe, A, Tanabe, K, Tanaka, A, Tanaka, N, Tang, S, Tang, Z, Tanigaki, K, Tarlac, M, Tatsuzawa, A, Tay, JF, Tay, LL, Taylor, J, Taylor, K, Te, A, Tenbusch, L, Teng, KS, Terakawa, A, Terry, J, Tham, ZD, Tholl, S, Thomas, G, Thong, KM, Tietjen, D, Timadjer, A, Tindall, H, Tipper, S, Tobin, K, Toda, N, Tokuyama, A, Tolibas, M, Tomita, A, Tomita, T, Tomlinson, J, Tonks, L, Topf, J, Topping, S, Torp, A, Torres, A, Totaro, F, Toth, P, Toyonaga, Y, Tripodi, F, Trivedi, K, Tropman, E, Tschope, D, Tse, J, Tsuji, K, Tsunekawa, S, Tsunoda, R, Tucky, B, Tufail, S, Tuffaha, A, Turan, E, Turner, H, Turner, J, Turner, M, Tye, YL, Tyler, A, Tyler, J, Uchi, H, Uchida, H, Uchida, T, Udagawa, T, Ueda, S, Ueda, Y, Ueki, K, Ugni, S, Ugwu, E, Umeno, R, Unekawa, C, Uozumi, K, Urquia, K, Valleteau, A, Valletta, C, van Erp, R, Vanhoy, C, Varad, V, Varma, R, Varughese, A, Vasquez, P, Vasseur, A, Veelken, R, Velagapudi, C, Verdel, K, Vettoretti, S, Vezzoli, G, Vielhauer, V, Viera, R, Vilar, E, Villaruel, S, Vinall, L, Vinathan, J, Visnjic, M, Voigt, E, von-Eynatten, M, Vourvou, M, Wada, J, Wada, T, Wada, Y, Wakayama, K, Wakita, Y, Walters, T, Wan Mohamad, WH, Wang, L, Wang, W, Wang, X, Wang, Y, Wanninayake, S, Watada, H, Watanabe, K, Watanabe, M, Waterfall, H, Watkins, D, Watson, S, Weaving, L, Weber, B, Webley, Y, Webster, A, Webster, M, Weetman, M, Wei, W, Weihprecht, H, Weiland, L, Weinmann-Menke, J, Weinreich, T, Wendt, R, Weng, Y, Whalen, M, Whalley, G, Wheatley, R, Wheeler, A, Wheeler, J, Whelton, P, White, K, Whitmore, B, Whittaker, S, Wiebel, J, Wiley, J, Wilkinson, L, Willett, M, Williams, A, Williams, E, Williams, K, Williams, T, Wilson, A, Wilson, P, Wincott, L, Wines, E, Winkelmann, B, Winkler, M, Winter-Goodwin, B, Witczak, J, Wittes, J, Wittmann, M, Wolf, G, Wolf, L, Wolfling, R, Wong, C, Wong, E, Wong, HS, Wong, LW, Wong, YH, Wonnacott, A, Wood, A, Wood, L, Woodhouse, H, Wooding, N, Woodman, A, Wren, K, Wu, J, Wu, P, Xia, S, Xiao, H, Xiao, X, Xie, Y, Xu, C, Xu, Y, Xue, H, Yahaya, H, Yalamanchili, H, Yamada, A, Yamada, N, Yamagata, K, Yamaguchi, M, Yamaji, Y, Yamamoto, A, Yamamoto, S, Yamamoto, T, Yamanaka, A, Yamano, T, Yamanouchi, Y, Yamasaki, N, Yamasaki, Y, Yamashita, C, Yamauchi, T, Yan, Q, Yanagisawa, E, Yang, F, Yang, L, Yano, S, Yao, S, Yao, Y, Yarlagadda, S, Yasuda, Y, Yiu, V, Yokoyama, T, Yoshida, S, Yoshidome, E, Yoshikawa, H, Young, A, Young, T, Yousif, V, Yu, H, Yu, Y, Yuasa, K, Yusof, N, Zalunardo, N, Zander, B, Zani, R, Zappulo, F, Zayed, M, Zemann, B, Zettergren, P, Zhang, H, Zhang, L, Zhang, N, Zhang, X, Zhao, J, Zhao, L, Zhao, S, Zhao, Z, Zhong, H, Zhou, N, Zhou, S, Zhu, L, Zhu, S, Zietz, M, Zippo, M, Zirino, F, and Zulkipli, FH

Published
2024
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35. Design and operation of a long-term monitoring system for spectral electrical impedance tomography (sEIT)

Author

M. Weigand, E. Zimmermann, V. Michels, J. A. Huisman, and A. Kemna

Subjects
Geophysics. Cosmic physics, QC801-809
Abstract

Spectral electrical impedance tomography (sEIT) is increasingly used to characterise the structure of subsurface systems using measurements in the megahertz to kilohertz range. Additionally, hydrogeophysical and biogeophysical processes are characterised and monitored using sEIT. The method combines multiple, spatially distributed, spectroscopic measurements with tomographic inversion algorithms to obtain images of the complex electrical resistivity distribution in the subsurface at various frequencies. Spectral polarisation measurements provide additional information about the systems under investigation and can be used to reduce ambiguities that occur if only the in-phase resistivity values are analysed. However, spectral impedance measurements are very sensitive to details of the measurement setup as well as to external noise and error components. Despite promising technical progress in improving measurement quality as well as progress in the characterisation and understanding of static polarisation signatures of the subsurface, long-term (i.e. multi-month to multi-year) monitoring attempts with fixed setups are still rare. Yet, measurement targets often show inherent non-stationarity that would require monitoring for a proper system characterisation. With the aim of improving operating foundations for similar endeavours, we here report on the design and field deployment of a permanently installed monitoring system for sEIT data. The specific aim of this monitoring installation is the characterisation of crop root evolution over a full growing season, requiring multiple measurements per day over multiple months to capture relevant system dynamics. In this contribution, we discuss the general layout and design of the monitoring setup, including the data acquisition system, additional on-site equipment, required corrections to improve data quality for high frequencies, data management and remote-processing facilities used to analyse the measured data. The choice and installation of electrodes, cables and measurement configurations are discussed and quality parameters are used for the continuous assessment of system functioning and data quality. Exemplary analysis results of the first season of operation highlight the importance of continuous quality control. It is also found that proper cable elevation decreased capacitive leakage currents and in combination with the correction of inductive effects led to consistent tomographic results up to 1 kHz measurement frequency. Overall, the successful operation of an sEIT monitoring system over multiple months with multiple daily tomographic measurements was achieved.

Published
2022
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36. Customised display of large mineralogical (XRD) data: Geological advantages and applications

Author

Rute Coimbra, Kilian B. Kemna, Fernando Rocha, and Maurits Horikx

Subjects
3D mapping, big data, mineralogy, sedimentary geology, X‐ray diffraction, Geology, QE1-996.5
Abstract

Abstract X‐ray diffraction mineralogical analysis of geological sequences is a well‐established procedure in both academia and industry, rendering a large volume of data in short‐analytical time. Yet, standard data treatment and resulting interpretations present limitations related to the inherent complexities of natural geological materials (e.g. compositional variety, structural ordering), and are often time consuming and focussed on a very detailed inspection. Several alternatives were evaluated in terms of advantages and disadvantages to the main goal of generating a user‐friendly, fast and intuitive way of processing a large volume of X‐ray diffraction data. The potential of using raw X‐ray diffraction data to interpret mineralogical diversity and relative phase abundances along sedimentary successions is explored here. A Python based program was tailored to assist in raw data organisation. After this automated step, a 3D surface computation renders the final result within minutes. This single‐image representation can also be integrated with complementary information (sedimentary logs or other features of interest) for contrast and/or comparison in multi‐proxy studies. The proposed approach was tested on a set of 81 bulk and clay‐fraction diffractograms (intensity in counts per second—cps and respective angle—º2Ɵ) obtained from a Cenomanian mixed carbonate–siliciclastic stratigraphic succession, here explored by combining mineralogical (XY) and stratigraphic/geological information (Z). The main goal is to bypass preliminary data treatment, avoid time‐consuming interpretation and unintended, but common, user‐induced bias. Advantages of 3D modelling include fast processing and single‐image solutions for large volumes of XRD data, combining mineralogical and stratigraphic information. This representation adds value by incorporating field (stratigraphic/sedimentological) information that complements and contextualises obtained mineralogical data. Limitations of using raw intensity data were evaluated by comparison with the results obtained via other standard data interpretation methods (e.g. semi‐quantitative estimation). A visual and statistical contrast comparison confirmed a good equilibrium between computation speed and precision/utility of the final output.

Published
2022
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38. Influence of NaHCO3 diffusion-driven pH changes on the electrical relaxation behaviour of sandstones.

Author

Mansfeld, Arne Marvin and Kemna, Andreas

Subjects
*CARBON dioxide in water, *PORE fluids, *ROCK texture, *INDUCED polarization, *ROCK permeability, *ATMOSPHERIC carbon dioxide, *WATER salinization
Abstract

Fluid chemistry in the vadose zone absent of organic life is governed by the interactions between rock mineral surfaces, water and atmospheric carbon dioxide [CO |$_2$| ] since carbon and its aquatic species control the system pH. Even though the effects of high carbon concentrations in the pore fluids of rocks and soils can be controlled ex-situ , their non-invasive monitoring and control still face difficulty, due to the inaccessibility of pore spaces. We propose monitoring the effect of carbon-rich solutions via their influence on the electrical relaxation behaviour, using the spectral induced polarization (SIP) method. Generally, the SIP response is determined by the rock's texture and the chemical composition of the electrical double layer (EDL) forming at the mineral–water interface. The understanding of how the relaxation behaviour of rocks and soils is controlled by pore water salinity and pH and how fast the EDL adapts to changes in pore fluid chemistry, however, is still limited. In this study, we conducted a series of controlled experiments where the diffusion of sodium hydrogencarbonate solution into quartz-rich sandstones was monitored with SIP at high temporal resolution. To identify the underlying relaxation processes, we analysed the obtained complex conductivity spectra by performing a Debye decomposition, yielding the system's relaxation-time distribution. Our results show that increasing pH leads to increased imaginary conductivities and systematic shifts in the peak relaxation time of the system. The observed temporal dynamics of the peak relaxation time can be described with a diffusion-type equation. We find that the dynamics are not governed by the permeability or porosity of the rock. In one experiment, salinities high enough to diminish the polarization of the system were reached. This reduction in polarization at peak frequency cannot be explained through simple Stern layer polarization models alone, suggesting that diffusive layer polarization plays an important role with increasing pH. While polarization magnitude reduces significantly, peak spectral position shifts towards larger relaxation times suggesting a reduction in the mobilities of the surface ions. Due to the increased salinity, the double layer thickness decreases, in turn decreasing the relaxation length scale, and lowering the diffuse layers screening effect. This study shows that the SIP method can capture the dynamic changes at the mineral–water interfaces in rocks in response to changing pH over a broad range of salinities, making SIP a promising method for the monitoring of subsurface processes associated with changes in the inorganic carbon concentration of the pore fluid. [ABSTRACT FROM AUTHOR]

Published
2025
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39. Probabilistic geophysical inversion of complex resistivity measurements using the Hamiltonian Monte Carlo method.

Author

Hase, Joost, Wagner, Florian M, Weigand, Maximilian, and Kemna, Andreas

Subjects
MONTE Carlo method, INVERSE problems, COVARIANCE matrices, BAYESIAN field theory, NONLINEAR equations, MARKOV chain Monte Carlo
Abstract

In this work, we introduce the probabilistic inversion of tomographic complex resistivity (CR) measurements using the Hamiltonian Monte Carlo (HMC) method. The posterior model distribution on which our approach operates accounts for the underlying complex-valued nature of the CR imaging problem accurately by including the individual errors of the measured impedance magnitude and phase, allowing for the application of independent regularization on the inferred subsurface conductivity magnitude and phase, and incorporating the effects of cross-sensitivities. As the tomographic CR inverse problem is nonlinear, of high dimension and features strong correlations between model parameters, efficiently sampling from the posterior model distribution is challenging. To meet this challenge we use HMC, a Markov-chain Monte Carlo method that incorporates gradient information to achieve efficient model updates. To maximize the benefit of a given number of forward calculations, we use the No-U-Turn sampler (NUTS) as a variant of HMC. We demonstrate the probabilistic inversion approach on a synthetic CR tomography measurement. The NUTS succeeds in creating a sample of the posterior model distribution that provides us with the ability to analyse correlations between model parameters and to calculate statistical estimators of interest, such as the mean model and the covariance matrix. Our results provide a strong basis for the characterization of the posterior model distribution and uncertainty quantification in the context of the tomographic CR inverse problem. [ABSTRACT FROM AUTHOR]

Published
2025
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40. Mental health literacy and the public perception of persons with depression and schizophrenia in Vietnam.

Author

Mobashery, Mahan, Ta, Thi Minh Tam, Cao, Duc Tien, Böge, Kerem, Eilinghoff, Luisa, Nguyen, Van Phi, Mavituna, Selin, Fuchs, Lukas, Weyn-Banningh, Sebastian, Kemna, Solveig, Bajbouj, Malek, and Hahn, Eric

Subjects
MENTAL health services, PUBLIC health infrastructure, HEALTH literacy, MENTAL illness, MENTAL health
Abstract

Background: Vietnam's mental health care system is undergoing significant changes since the government has initiated large-scale programs to reform and develop the mental health care infrastructure. Cultural belief systems on mental illnesses influence help-seeking behavior and compliance. This study investigates the belief systems about people with schizophrenia and depression among people living in the Hanoi area. Method: 1077 Vietnamese participants answered two open-ended questions after reading an unlabeled vignette describing a character with the symptoms of schizophrenia or depression. The answers were analyzed using thematic analysis. Results: Of all participants, 88,4% associated the presented cases with a mental illness, with 91,5% in the case of schizophrenia and 85,1% in the case of depression, so both disorders were conceptualized as mental illnesses. 18,6% mentioned depression when presented with the depression vignette, while only 3,6% recognized schizophrenia in the schizophrenia condition. Conclusions: Almost 9 out of 10 participants considered the presented cases as an example of mental illness, suggesting a high mental health awareness among our participants. The majority did not identify the presented cases as examples of schizophrenia or depression, reflecting little familiarity with Western mental health concepts. It could be interpreted as a sign of relatively low mental health literacy among the study participants. [ABSTRACT FROM AUTHOR]

Published
2024
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41. Characterizing of dropouts in the mental health of refugees and asylum seekers (MEHIRA) study examining the effects of a stepped and collaborative care model – a multicentered rater-blinded randomized controlled trial.

Author

Kemna, Solveig, Bringmann, Max, Karnouk, Carine, Hoell, Andreas, Tschorn, Mira, Kamp-Becker, Inge, Padberg, Frank, Übleis, Aline, Hasan, Alkomiet, Falkai, Peter, Salize, Hans-Joachim, Meyer-Lindenberg, Andreas, Banaschewski, Tobias, Schneider, Frank, Habel, Ute, Plener, Paul, Hahn, Eric, Wiechers, Maren, Strupf, Michael, and Jobst, Andrea

Abstract

Background: Dropout from healthcare interventions can negatively affect patients and healthcare providers through impaired trust in the healthcare system and ineffective use of resources. Research on this topic is still largely missing on refugees and asylum seekers. The current study aimed to characterize predictors for dropout in the Mental Health in Refugees and Asylum Seekers (MEHIRA) study, one of the largest multicentered controlled trials investigating the effectiveness and cost-effectiveness of a nationwide stepped and collaborative care model. Methods: Predictors were multiply imputed and selected for descriptive modelling using backward elimination. The final variable set was entered into logistic regression. Results: The overall dropout rate was 41,7%. Dropout was higher in participants in group therapy (p = 0.001; OR = 10.7), with larger satisfaction with social relationships (p = 0.017; OR = 1.87), with difficulties in maintaining personal relationships (p = 0.005; OR = 4.27), and with higher depressive symptoms (p = 0.029; OR = 1.05). Participants living in refugee accommodation (p = 0.040; OR = 0.45), with a change in social status (p = 0.008; OR = 0.67) and with conduct (p = 0.020; OR = 0.24) and emotional problems (p = 0.013; OR = 0.31) were significantly less likely to drop out of treatment. Conclusion: Overall, the outcomes of this study suggest that predictors assessing social relationships, social status, and living conditions should be considered as topics of psychological treatment to increase adherence and as predictors for future research studies (including treatment type). [ABSTRACT FROM AUTHOR]

Published
2024
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42. Spectral induced polarization imaging to investigate an ice-rich mountain permafrost site in Switzerland

Author

T. Maierhofer, C. Hauck, C. Hilbich, A. Kemna, and A. Flores-Orozco

Subjects
Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract

Spectral induced polarization (SIP) measurements were collected at the Lapires talus slope, a long-term permafrost monitoring site located in the western Swiss Alps, to assess the potential of the frequency dependence (within the frequency range of 0.1–225 Hz) of the electrical polarization response of frozen rocks for an improved permafrost characterization. The aim of our investigation was to (a) find a field protocol that provides SIP imaging data sets less affected by electromagnetic coupling and easy to deploy in rough terrains, (b) cover the spatial extent of the local permafrost distribution, and (c) evaluate the potential of the spectral data to discriminate between different substrates and spatial variations in the volumetric ice content within the talus slope. To qualitatively assess data uncertainty, we analyse the misfit between normal and reciprocal (N&R) measurements collected for all profiles and frequencies. A comparison between different cable setups reveals the lowest N&R misfits for coaxial cables and the possibility of collecting high-quality SIP data in the range between 0.1–75 Hz. We observe an overall smaller spatial extent of the ice-rich permafrost body compared to its assumed distribution from previous studies. Our results further suggest that SIP data help to improve the discrimination between ice-rich permafrost and unfrozen bedrock in ambiguous cases based on their characteristic spectral behaviour, with ice-rich areas showing a stronger polarization towards higher frequencies in agreement with the well-known spectral response of ice.

Published
2022
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45. Megathrust Stress Drop as Trigger of Aftershock Seismicity: Insights From the 2011 Tohoku Earthquake, Japan

Author

A. Dielforder, G. M. Bocchini, K. Kemna, A. Hampel, R. M. Harrington, and O. Oncken

Subjects
Tohoku earthquake, aftershocks, stress, megathrust earthquake, stress drop, force balance, Geophysics. Cosmic physics, QC801-809
Abstract

Abstract Numerous normal‐faulting aftershocks in subduction forearcs commonly follow large megathrust earthquakes. Postseismic normal faulting has been explained by stress changes induced by the stress drop along the megathrust. However, details of forearc stress changes and aftershock triggering mechanisms remain poorly understood. Here, we use numerical force‐balance models combined with Coulomb failure analysis to show that the megathrust stress drop supports normal faulting, but that forearc‐wide aftershock triggering is feasible within a narrow range of megathrust stress drop values and preseismic stress states only. We determine this range for the 2011 Tohoku earthquake (Japan) and show that the associated stress changes explain the aftershock seismicity in unprecedented detail and are consistent with the stress released by forearc seismicity before and after the earthquake.

Published
2023
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49. Hematopoietic stem cell metabolism within the bone marrow niche – insights and opportunities.

Author

Kemna, Koen, Burg, Mirjam, Lankester, Arjan, and Giera, Martin

Subjects
*HEMATOPOIETIC stem cells, *BONE marrow, *CELL metabolism, *BLOOD cells, *STEM cell treatment
Abstract

Hematopoiesis unfolds within the bone marrow niche where hematopoietic stem cells (HSCs) play a central role in continually replenishing blood cells. The hypoxic bone marrow environment imparts peculiar metabolic characteristics to hematopoietic processes. Here, we discuss the internal metabolism of HSCs and describe external influences exerted on HSC metabolism by the bone marrow niche environment. Importantly, we suggest that the metabolic environment and metabolic cues are intertwined with HSC cell fate, and are crucial for hematopoietic processes. Metabolic dysregulation within the bone marrow niche during acute stress, inflammation, and chronic inflammatory conditions can lead to reduced HSC vitality. Additionally, we raise questions regarding metabolic stresses imposed on HSCs during implementation of stem cell protocols such as allo‐SCT and gene therapy, and the potential ramifications. Enhancing our comprehension of metabolic influences on HSCs will expand our understanding of pathophysiology in the bone marrow and improve the application of stem cell therapies. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Relationship between Cole–Cole model parameters in permittivity and conductivity formulation.

Author

Limbrock, Jonas K and Kemna, Andreas

Subjects
*ELECTRIC conductivity, *ELECTRICAL resistivity, *INDUCED polarization, *MATERIALS science, *ELECTROMAGNETIC theory
Abstract

For the analysis of spectral induced polarization (SIP) measurements and for the description of frequency-dependent electrical relaxation responses, so-called Cole–Cole models (CCMs) are widely used. Typically, CCM formulations in terms of complex electrical conductivity or complex electrical resistivity are used in geophysical applications. The differences between these model descriptions, in particular between the respective time constants, and their conversion have been studied. A third variant of the model is formulated in terms of complex permittivity, commonly used in materials science. In general, all these model formulations can be used equivalently for fitting SIP data, which, however, results in differing values for some of the model parameters. For a meaningful comparison of CCM parameters of different samples or measurements, it is necessary that they are based on the same model formulation. In this work, the relationships between the Debye model (DM) and CCM parameters in the formulation for complex permittivity and complex conductivity are studied. A direct analytical conversion is possible for generalized DM formulations, both in single- and multi-term model formulations, resulting in relationships between the respective relaxation time distributions (RTDs). Such a direct conversion for CCM formulations is not possible. We however derived an approximate relationship between |$\log$| -normal RTD and CCM formulations and respective permittivity and conductivity parameter values. Our study also highlights the significance of using consistent model formulations when experimental data are compared in terms of DM or CCM parameters, as parameters used to predict ice temperature are incorrect if the conductivity time constant is used to predict the temperature from interpolation of a permittivity time constant-temperature relationship. [ABSTRACT FROM AUTHOR]

Published
2024
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