cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10559511
title: Evaluation of cardiovascular and cerebrovascular control mechanisms in postural orthostatic tachycardia syndrome via conditional transfer entropy the impact of the respiratory signal type

description: Gelpi F, Bari V, Cairo B, De Maria B, Wells R, Baumert M, Porta A. Evaluation of cardiovascular and cerebrovascular control mechanisms in postural orthostatic tachycardia syndrome via conditional transfer entropy: the impact of the respiratory signal type. Physiol Meas. 2023 Jun 19;44(6). doi: 10.1088/1361-6579/acdb47. PMID: 37267989.

Abstract



Objective.Closed loop cardiovascular (CV) and cerebrovascular (CBV) variability interactions are assessed via transfer entropy (TE) from systolic arterial pressure (SAP) to heart period (HP) and vice versa and from mean arterial pressure (MAP) to mean cerebral blood velocity (MCBv) and vice versa. This analysis is exploited to assess the efficiency of baroreflex and cerebral autoregulation. This study aims at characterizing CV and CBV controls in postural orthostatic tachycardiac syndrome (POTS) subjects experiencing exaggerated sympathetic response during orthostatic challenge via unconditional TE and TE conditioned on respiratory activity (R).Approach.In 18 healthy controls (age: 28 ± 13 yrs; 5 males, 13 females) and 15 POTS individuals (age: 29 ± 11 yrs; 3 males, 12 females) we acquired beat-to-beat variability of HP, SAP, MAP and MCBv and twoRsignals, namely respiratory chest movement (RCM) and capnogram (CAP). Recordings were made at sitting rest and during active standing (STAND). TE was computed via vector autoregressive approach.Main results.We found that: (i) when assessing CV interactions, the increase of the TE from SAP to HP during STAND, indicating baroreflex activation, is detected solely when conditioning on RCM; (ii) when assessing CBV interactions, the impact ofRon the TE computation is negligible; (iii) POTS shows baroreflex impairment during STAND; (iv) POTS exhibits a normal CBV response to STAND.Significance.TE is useful for detecting the impairment of specific regulatory mechanisms in POTS. Moreover, using differentRsignals highlights the sensitivity of CV and CBV controls to specificRaspects.
DOI: 10.5281/zenodo.10559512
title: Evaluation of cardiovascular and cerebrovascular control mechanisms in postural orthostatic tachycardia syndrome via conditional transfer entropy the impact of the respiratory signal type

description: Gelpi F, Bari V, Cairo B, De Maria B, Wells R, Baumert M, Porta A. Evaluation of cardiovascular and cerebrovascular control mechanisms in postural orthostatic tachycardia syndrome via conditional transfer entropy: the impact of the respiratory signal type. Physiol Meas. 2023 Jun 19;44(6). doi: 10.1088/1361-6579/acdb47. PMID: 37267989.

Abstract



Objective.Closed loop cardiovascular (CV) and cerebrovascular (CBV) variability interactions are assessed via transfer entropy (TE) from systolic arterial pressure (SAP) to heart period (HP) and vice versa and from mean arterial pressure (MAP) to mean cerebral blood velocity (MCBv) and vice versa. This analysis is exploited to assess the efficiency of baroreflex and cerebral autoregulation. This study aims at characterizing CV and CBV controls in postural orthostatic tachycardiac syndrome (POTS) subjects experiencing exaggerated sympathetic response during orthostatic challenge via unconditional TE and TE conditioned on respiratory activity (R).Approach.In 18 healthy controls (age: 28 ± 13 yrs; 5 males, 13 females) and 15 POTS individuals (age: 29 ± 11 yrs; 3 males, 12 females) we acquired beat-to-beat variability of HP, SAP, MAP and MCBv and twoRsignals, namely respiratory chest movement (RCM) and capnogram (CAP). Recordings were made at sitting rest and during active standing (STAND). TE was computed via vector autoregressive approach.Main results.We found that: (i) when assessing CV interactions, the increase of the TE from SAP to HP during STAND, indicating baroreflex activation, is detected solely when conditioning on RCM; (ii) when assessing CBV interactions, the impact ofRon the TE computation is negligible; (iii) POTS shows baroreflex impairment during STAND; (iv) POTS exhibits a normal CBV response to STAND.Significance.TE is useful for detecting the impairment of specific regulatory mechanisms in POTS. Moreover, using differentRsignals highlights the sensitivity of CV and CBV controls to specificRaspects.
DOI: 10.6084/m9.figshare.24564829
title: REFSQ_2024_Tertiary_Study_AI4RE.xlsx

description: Conducting a tertiary study to explore the current state-of-the-art in the implementation and adoption of AI technologies to assist RE activities.
DOI: 10.6084/m9.figshare.24564829.v1
title: REFSQ_2024_Tertiary_Study_AI4RE.xlsx

description: Conducting a tertiary study to explore the current state-of-the-art in the implementation and adoption of AI technologies to assist RE activities.
DOI: 10.5281/zenodo.10559490
title: COVID-19 Vaccine Hesitancy in Italian Adults with Marfan Syndrome: Insights from a Secondary Analysis of a Cross-Sectional Study

description: Udugampolage NS, Pini A, Magon A, Conte G, Callus E, Taurino J, Caruso R. COVID-19 Vaccine Hesitancy in Italian Adults with Marfan Syndrome: Insights from a Secondary Analysis of a Cross-Sectional Study. Vaccines (Basel). 2023 Mar 26;11(4):734. doi: 10.3390/vaccines11040734. PMID: 37112646; PMCID: PMC10143721.

Abstract



Although vaccine hesitancy has been reported in many patient groups and countries, there is a lack of data on vaccine hesitancy in patients with Marfan syndrome (MFS). MFS is a rare genetic disorder that can lead to cardiovascular, ocular, and musculoskeletal issues. Because MFS patients may face an increased risk of COVID-19 complications, vaccination is crucial for this population. This brief report aims to describe vaccine hesitancy rates in MFS patients and compare the characteristics of patients who are hesitant and those who are not to gain a better understanding of this specific population. This study analyzes previously published cross-sectional data that examined mental health, sociodemographic, and clinical factors associated with PTSD, depression, anxiety, and insomnia in MFS patients during the third wave of the COVID-19 pandemic in Lombardy, Italy. Of the 112 MFS patients who participated, 26 (23.9%) reported vaccine hesitancy. Vaccine hesitancy may be associated mainly with younger age and not be related to other patient characteristics. Therefore, this report found no differences in individual-level variables, such as sex, education, comorbidities, and mental health symptoms, between those who were hesitant and those who were not. The study findings are insightful and suggest that interventions to address vaccine hesitancy in this population may need to focus on attitudes and beliefs related to vaccination rather than targeting specific sociodemographic or clinical factors.
DOI: 10.5281/zenodo.10559491
title: COVID-19 Vaccine Hesitancy in Italian Adults with Marfan Syndrome: Insights from a Secondary Analysis of a Cross-Sectional Study

description: Udugampolage NS, Pini A, Magon A, Conte G, Callus E, Taurino J, Caruso R. COVID-19 Vaccine Hesitancy in Italian Adults with Marfan Syndrome: Insights from a Secondary Analysis of a Cross-Sectional Study. Vaccines (Basel). 2023 Mar 26;11(4):734. doi: 10.3390/vaccines11040734. PMID: 37112646; PMCID: PMC10143721.

Abstract



Although vaccine hesitancy has been reported in many patient groups and countries, there is a lack of data on vaccine hesitancy in patients with Marfan syndrome (MFS). MFS is a rare genetic disorder that can lead to cardiovascular, ocular, and musculoskeletal issues. Because MFS patients may face an increased risk of COVID-19 complications, vaccination is crucial for this population. This brief report aims to describe vaccine hesitancy rates in MFS patients and compare the characteristics of patients who are hesitant and those who are not to gain a better understanding of this specific population. This study analyzes previously published cross-sectional data that examined mental health, sociodemographic, and clinical factors associated with PTSD, depression, anxiety, and insomnia in MFS patients during the third wave of the COVID-19 pandemic in Lombardy, Italy. Of the 112 MFS patients who participated, 26 (23.9%) reported vaccine hesitancy. Vaccine hesitancy may be associated mainly with younger age and not be related to other patient characteristics. Therefore, this report found no differences in individual-level variables, such as sex, education, comorbidities, and mental health symptoms, between those who were hesitant and those who were not. The study findings are insightful and suggest that interventions to address vaccine hesitancy in this population may need to focus on attitudes and beliefs related to vaccination rather than targeting specific sociodemographic or clinical factors.
DOI: 10.17863/cam.95162.3
title: Research Database of All Publicly Available Samples of Gandharan Palettes/Toilet Trays

description: A CSV, xlsx and Accdb file containing an inventory list with all public records of Gandhara Palettes with associated data such as recorded provenance based on publications and museum catalogues, general descriptions of the material involved in each palette's construction, as well as periodization based on said publications. In addition, phasing is provided to enable for comparative analysis of various descriptions. In addition, links to museum catalogues are povided, as are citations and descriptions of the data itself. All data was collected from relevant bibliography such as excavation reports, previously compiled lists and museum catalogues to provide a new and updated list of the palettes, alongside important contextual information for future studies. Updated in May 2023 with added information on the regional and local provenance of the palettes at hand. It also contains further qualitative information in terms of the fragmentation of the palettes, as well as possible religious and mythological interpretations. The chronology has been streamlined and re-organized to make it more usable for statistical analysis, as well as providing a column describing the nature of compartments as well as additional information on the nature of the scenes (whether they show a narrative or an event). The third update (Jan 2024) has added new entries from existing literature, as well as their descriptions and citations. In addition, updates on the citations where they are found have been updated, and these citations have been fixed to make navigation in the database easier.
DOI: 10.5281/zenodo.10556282
title: A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning

description: Saitta S, Sturla F, Gorla R, Oliva OA, Votta E, Bedogni F, Redaelli A. A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning. Comput Biol Med. 2023 Sep;163:107147. doi: 10.1016/j.compbiomed.2023.107147. Epub 2023 Jun 7. PMID: 37329622.

Abstract



Accurate planning of transcatheter aortic valve implantation (TAVI) is important to minimize complications, and it requires anatomic evaluation of the aortic root (AR), commonly performed through 3D computed tomography (CT) image analysis. Currently, there is no standard automated solution for this process. Two convolutional neural networks with 3D U-Net architectures (model 1 and model 2) were trained on 310 CT scans for AR analysis. Model 1 performs AR segmentation and model 2 identifies the aortic annulus and sinotubular junction (STJ) contours. After training, the two models were integrated into a fully automated pipeline for geometric analysis of the AR. Results were validated against manual measurements of 178 TAVI candidates. The trained CNNs segmented the AR, annulus, and STJ effectively, resulting in mean Dice scores of 0.93 for the AR, and mean surface distances of 0.73 mm and 0.99 mm for the annulus and STJ, respectively. Automatic measurements were in good agreement with manual annotations, yielding annulus diameters that differed by 0.52 [-2.96, 4.00] mm (bias and 95% limits of agreement for manual minus algorithm). Evaluating the area-derived diameter, bias, and limits of agreement were 0.07 [-0.25, 0.39] mm. STJ and sinuses diameters computed by the automatic method yielded differences of 0.16 [-2.03, 2.34] and 0.1 [-2.93, 3.13] mm, respectively. The proposed tool is a fully automatic solution to quantify morphological biomarkers for pre-TAVI planning. The method was validated against manual annotation from clinical experts and showed to be quick and effective in assessing AR anatomy, with potential for time and cost savings.
DOI: 10.5281/zenodo.10556283
title: A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning

description: Saitta S, Sturla F, Gorla R, Oliva OA, Votta E, Bedogni F, Redaelli A. A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning. Comput Biol Med. 2023 Sep;163:107147. doi: 10.1016/j.compbiomed.2023.107147. Epub 2023 Jun 7. PMID: 37329622.

Abstract



Accurate planning of transcatheter aortic valve implantation (TAVI) is important to minimize complications, and it requires anatomic evaluation of the aortic root (AR), commonly performed through 3D computed tomography (CT) image analysis. Currently, there is no standard automated solution for this process. Two convolutional neural networks with 3D U-Net architectures (model 1 and model 2) were trained on 310 CT scans for AR analysis. Model 1 performs AR segmentation and model 2 identifies the aortic annulus and sinotubular junction (STJ) contours. After training, the two models were integrated into a fully automated pipeline for geometric analysis of the AR. Results were validated against manual measurements of 178 TAVI candidates. The trained CNNs segmented the AR, annulus, and STJ effectively, resulting in mean Dice scores of 0.93 for the AR, and mean surface distances of 0.73 mm and 0.99 mm for the annulus and STJ, respectively. Automatic measurements were in good agreement with manual annotations, yielding annulus diameters that differed by 0.52 [-2.96, 4.00] mm (bias and 95% limits of agreement for manual minus algorithm). Evaluating the area-derived diameter, bias, and limits of agreement were 0.07 [-0.25, 0.39] mm. STJ and sinuses diameters computed by the automatic method yielded differences of 0.16 [-2.03, 2.34] and 0.1 [-2.93, 3.13] mm, respectively. The proposed tool is a fully automatic solution to quantify morphological biomarkers for pre-TAVI planning. The method was validated against manual annotation from clinical experts and showed to be quick and effective in assessing AR anatomy, with potential for time and cost savings.
DOI: 10.34740/kaggle/dsv/7485552
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.18746/bmth.data.00000325
title: Personalisation through pricing co-creation: Customer’s willingness to pay and pricing strategies in the B2C context of hospitality
DOI: 10.5517/ccdc.csd.cc293bc4
title: CCDC 2118365: Experimental Crystal Structure Determination

description: Related Article: Baolei Tang, Mengjuan Li, Xu Yu, Hongyu Zhang|2022|J.Mater.Chem.C|10|3894|doi:10.1039/D1TC06124K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc293bd5
title: CCDC 2118366: Experimental Crystal Structure Determination

description: Related Article: Baolei Tang, Mengjuan Li, Xu Yu, Hongyu Zhang|2022|J.Mater.Chem.C|10|3894|doi:10.1039/D1TC06124K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10556256
title: Changes of the cardiac baroreflex bandwidth during postural challenges

description: Porta A, Gelpi F, Bari V, Cairo B, De Maria B, Takahashi ACM, Catai AM, Colombo R. Changes of the cardiac baroreflex bandwidth during postural challenges. Am J Physiol Regul Integr Comp Physiol. 2023 Apr 1;324(4):R601-R612. doi: 10.1152/ajpregu.00305.2022. Epub 2023 Mar 6. PMID: 36878488.

Abstract



Baroreflex is commonly typified from heart period (HP) and systolic arterial pressure (SAP) spontaneous variations in the frequency domain mainly by estimating its sensitivity. However, an informative parameter linked to the rapidity of the HP response to SAP changes, such as the baroreflex bandwidth, remains unquantified. We propose a model-based parametric approach for estimating the baroreflex bandwidth from the impulse response function (IRF) of the HP-SAP transfer function (TF). The approach accounts explicitly for the action of mechanisms modifying HP regardless of SAP changes. The method was tested during graded baroreceptor unloading induced by head-up tilt (HUT) at 15°, 30°, 45°, 60°, and 75° (T15, T30, T45, T60, and T75) in 17 healthy individuals (age: 21-36 yr; 9 females and 8 males) and during baroreceptor loading obtained via head-down tilt (HDT) at -25° in 13 healthy men (age: 41-71 yr). The bandwidth was estimated as the decay constant of the monoexponential IRF fitting. The method was robust because the monoexponential fitting described adequately the HP dynamics following an impulse of SAP. We observed that 1) baroreflex bandwidth is reduced during graded HUT and this narrowing is accompanied by the reduction of the bandwidth of mechanisms that modify HP regardless of SAP changes and 2) baroreflex bandwidth is not affected by HDT but that of SAP-unrelated mechanisms becomes wider. This study provides a method for estimating a baroreflex feature that provides different information compared with the more usual baroreflex sensitivity while accounting explicitly for the action of mechanisms changing HP irrespective of SAP.
DOI: 10.5281/zenodo.10556257
title: Changes of the cardiac baroreflex bandwidth during postural challenges

description: Porta A, Gelpi F, Bari V, Cairo B, De Maria B, Takahashi ACM, Catai AM, Colombo R. Changes of the cardiac baroreflex bandwidth during postural challenges. Am J Physiol Regul Integr Comp Physiol. 2023 Apr 1;324(4):R601-R612. doi: 10.1152/ajpregu.00305.2022. Epub 2023 Mar 6. PMID: 36878488.

Abstract



Baroreflex is commonly typified from heart period (HP) and systolic arterial pressure (SAP) spontaneous variations in the frequency domain mainly by estimating its sensitivity. However, an informative parameter linked to the rapidity of the HP response to SAP changes, such as the baroreflex bandwidth, remains unquantified. We propose a model-based parametric approach for estimating the baroreflex bandwidth from the impulse response function (IRF) of the HP-SAP transfer function (TF). The approach accounts explicitly for the action of mechanisms modifying HP regardless of SAP changes. The method was tested during graded baroreceptor unloading induced by head-up tilt (HUT) at 15°, 30°, 45°, 60°, and 75° (T15, T30, T45, T60, and T75) in 17 healthy individuals (age: 21-36 yr; 9 females and 8 males) and during baroreceptor loading obtained via head-down tilt (HDT) at -25° in 13 healthy men (age: 41-71 yr). The bandwidth was estimated as the decay constant of the monoexponential IRF fitting. The method was robust because the monoexponential fitting described adequately the HP dynamics following an impulse of SAP. We observed that 1) baroreflex bandwidth is reduced during graded HUT and this narrowing is accompanied by the reduction of the bandwidth of mechanisms that modify HP regardless of SAP changes and 2) baroreflex bandwidth is not affected by HDT but that of SAP-unrelated mechanisms becomes wider. This study provides a method for estimating a baroreflex feature that provides different information compared with the more usual baroreflex sensitivity while accounting explicitly for the action of mechanisms changing HP irrespective of SAP.
DOI: 10.5281/zenodo.10556148
title: On the Different Abilities of Cross-Sample Entropy and K-Nearest-Neighbor Cross-Unpredictability in Assessing Dynamic Cardiorespiratory and Cerebrovascular Interactions

description: Porta A, Bari V, Gelpi F, Cairo B, De Maria B, Tonon D, Rossato G, Faes L. On the Different Abilities of Cross-Sample Entropy and K-Nearest-Neighbor Cross-Unpredictability in Assessing Dynamic Cardiorespiratory and Cerebrovascular Interactions. Entropy (Basel). 2023 Apr 1;25(4):599. doi: 10.3390/e25040599. PMID: 37190390; PMCID: PMC10137562.

Abstract



Nonlinear markers of coupling strength are often utilized to typify cardiorespiratory and cerebrovascular regulations. The computation of these indices requires techniques describing nonlinear interactions between respiration (R) and heart period (HP) and between mean arterial pressure (MAP) and mean cerebral blood velocity (MCBv). We compared two model-free methods for the assessment of dynamic HP-R and MCBv-MAP interactions, namely the cross-sample entropy (CSampEn) and k-nearest-neighbor cross-unpredictability (KNNCUP). Comparison was carried out first over simulations generated by linear and nonlinear unidirectional causal, bidirectional linear causal, and lag-zero linear noncausal models, and then over experimental data acquired from 19 subjects at supine rest during spontaneous breathing and controlled respiration at 10, 15, and 20 breaths·minute-1 as well as from 13 subjects at supine rest and during 60° head-up tilt. Linear markers were computed for comparison. We found that: (i) over simulations, CSampEn and KNNCUP exhibit different abilities in evaluating coupling strength; (ii) KNNCUP is more reliable than CSampEn when interactions occur according to a causal structure, while performances are similar in noncausal models; (iii) in healthy subjects, KNNCUP is more powerful in characterizing cardiorespiratory and cerebrovascular variability interactions than CSampEn and linear markers. We recommend KNNCUP for quantifying cardiorespiratory and cerebrovascular coupling.