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PROTOCOL FOR DEVELOPMENT OF A QUESTIONNAIRE MAPPING GENDER AND PAIN DYNAMICS
No full textBackground and aims: Binominal sex differences have been extensively examined in pain research, revealing a trend wherein individuals categorized as female exhibit heightened sensitivity to pain compared to those categorized as male. However, the gender context model of pain proposes several intrapersonal relationships between pain and gender (i.e. attitudes, feelings and behaviors) as well. Hence, it is important that comprehensive tools are developed to map these interactions.Methods: An English questionnaire will be developed containing statements regarding gender conceptualization, gender identity and gender roles in pain, which are scored on a Likert scale. Based on preliminary considerations the authors will develop a first version of the questionnaire, which will be revised based on the input of an international multidisciplinary expert committee. Afterwards, online sequential funnel- based focus groups existing of participants with different profiles will go back and forth with the expert committee, to revise until data saturation is achieved. This finished questionnaire will then undergo preliminary pilot testing in a small group of respondents. Finally, the questionnaire’s reliability and validity will be tested.Results: The result will be a questionnaire with items that can be organized into various continua which we hypothesize to be interrelated. In a data-driven approach we will then be able to construct different profiles related to intrapersonal gender and pain dynamics.Conclusions: This new assessment tool will be useful for clinical pain practice and pain research and has the potential to provide valuable insights into the underlying mechanisms of the interaction between pain and gender.Background and aims: Binominal sex differences have been extensively examined in pain research, revealing a trend wherein individuals categorized as female exhibit heightened sensitivity to pain compared to those categorized as male. However, the gender context model of pain proposes several intrapersonal relationships between pain and gender (i.e. attitudes, feelings and behaviors) as well. Hence, it is important that comprehensive tools are developed to map these interactions.Methods: An English questionnaire will be developed containing statements regarding gender conceptualization, gender identity and gender roles in pain, which are scored on a Likert scale. Based on preliminary considerations the authors will develop a first version of the questionnaire, which will be revised based on the input of an international multidisciplinary expert committee. Afterwards, online sequential funnel- based focus groups existing of participants with different profiles will go back and forth with the expert committee, to revise until data saturation is achieved. This finished questionnaire will then undergo preliminary pilot testing in a small group of respondents. Finally, the questionnaire’s reliability and validity will be tested.Results: The result will be a questionnaire with items that can be organized into various continua which we hypothesize to be interrelated. In a data-driven approach we will then be able to construct different profiles related to intrapersonal gender and pain dynamics.Conclusions: This new assessment tool will be useful for clinical pain practice and pain research and has the potential to provide valuable insights into the underlying mechanisms of the interaction between pain and gender.
Benchmarking tree species classification from proximally sensed laser scanning data : introducing the FOR-species20K dataset
No full textoai:search.ugent.be:pug01:01JMEN0KQN0264FCMFQ5SDBTKB1. Proximally sensed laser scanning presents new opportunities for automated forest ecosystem data capture. However, a gap remains in deriving ecologically pertinent information, such as tree species, without additional ground data. Artificial intelligence approaches, particularly deep learning (DL), have shown promise towards automation. Progress has been limited by the lack of large, diverse, and, most importantly, openly available labelled single-tree point cloud datasets. This has hindered both (1) the robustness of the DL models across varying data types (platforms and sensors) and (2) the ability to effectively track progress, thereby slowing the convergence towards best practice for species classification.2. To address the above limitations, we compiled the FOR-species20K benchmark dataset, consisting of individual tree point clouds captured using proximally sensed laser scanning data from terrestrial (TLS), mobile (MLS) and drone laser scanning (ULS). Compiled collaboratively, the dataset includes data collected in forests mainly across Europe, covering Mediterranean, temperate and boreal biogeographic regions. It includes scattered tree data from other continents, totaling over 20,000 trees of 33 species and covering a wide range of tree sizes and forms. Alongside the release of FOR-species20K, we benchmarked seven leading DL models for individual tree species classification, including both point cloud (PointNet++, MinkNet, MLP-Mixer, DGCNNs) and multi-view 2D-based methods (SimpleView, DetailView, YOLOv5).3. 2D Image-based models had, on average, higher overall accuracy (0.77) than 3D point cloud-based models (0.72). Notably, the performance was consistently >0.8 across scanning platforms and sensors, offering versatility in deployment. The top-scoring model, DetailView, demonstrated robustness to training data imbalances and effectively generalized across tree sizes.4. The FOR-species20K dataset represents an important asset for developing and benchmarking DL models for individual tree species classification using proximally sensed laser scanning data. As such, it serves as a crucial foundation for future efforts to classify accurately and map tree species at various scales using laser scanning technology, as it provides the complete code base, dataset, and an initial baseline representative of the current state-of-the-art of point cloud tree species classification methods.1. Proximally sensed laser scanning presents new opportunities for automated forest ecosystem data capture. However, a gap remains in deriving ecologically pertinent information, such as tree species, without additional ground data. Artificial intelligence approaches, particularly deep learning (DL), have shown promise towards automation. Progress has been limited by the lack of large, diverse, and, most importantly, openly available labelled single-tree point cloud datasets. This has hindered both (1) the robustness of the DL models across varying data types (platforms and sensors) and (2) the ability to effectively track progress, thereby slowing the convergence towards best practice for species classification.2. To address the above limitations, we compiled the FOR-species20K benchmark dataset, consisting of individual tree point clouds captured using proximally sensed laser scanning data from terrestrial (TLS), mobile (MLS) and drone laser scanning (ULS). Compiled collaboratively, the dataset includes data collected in forests mainly across Europe, covering Mediterranean, temperate and boreal biogeographic regions. It includes scattered tree data from other continents, totaling over 20,000 trees of 33 species and covering a wide range of tree sizes and forms. Alongside the release of FOR-species20K, we benchmarked seven leading DL models for individual tree species classification, including both point cloud (PointNet++, MinkNet, MLP-Mixer, DGCNNs) and multi-view 2D-based methods (SimpleView, DetailView, YOLOv5).3. 2D Image-based models had, on average, higher overall accuracy (0.77) than 3D point cloud-based models (0.72). Notably, the performance was consistently >0.8 across scanning platforms and sensors, offering versatility in deployment. The top-scoring model, DetailView, demonstrated robustness to training data imbalances and effectively generalized across tree sizes.4. The FOR-species20K dataset represents an important asset for developing and benchmarking DL models for individual tree species classification using proximally sensed laser scanning data. As such, it serves as a crucial foundation for future efforts to classify accurately and map tree species at various scales using laser scanning technology, as it provides the complete code base, dataset, and an initial baseline representative of the current state-of-the-art of point cloud tree species classification methods.A
Digital PCR-based gene expression analysis using a highly multiplexed assay with universal detection probes to study induced pluripotent stem cell differentiation into cranial neural crest cells
No full textInduced pluripotent stem cells (iPSCs) have the potential to differentiate into any cell type, offering a valuable tool for research in developmental biology, regenerative medicine, and disease modeling. In this study, iPSCs were differentiated into cranial neural crest cells (CNCCs) over a 14-day period. RNA was extracted from these cells at day 0 (iPSCs), day 7, and day 14 to evaluate successful differentiation through the expression analysis of pluripotency and CNCC marker genes.A key focus was the conversion of existing qPCR assays into multiplexed RT-dPCR assays utilizing universal detection probes for precise gene expression analysis during the differentiation of induced pluripotent stem cells (iPSCs) into cranial neural crest cells (CNCCs). We aimed to leverage the superior precision, sensitivity, and multiplexing-degree of dPCR, particularly in quantifying low-abundance targets. We conducted a comparative analysis of the temporal expression patterns of crucial marker genes using both qPCR and dPCR.Our experiments revealed that the four five-plex dPCR assays could successfully detect and quantify the pluripotency and CNCC marker genes and evaluate CNCC differentiation. We observed the expected downregulation of pluripotency genes during differentiation. Conversely, the upregulation of CNCC markers validates the successful differentiation process. In conclusion, SYBR Green I gene expression qPCR assays can be readily converted into multiplex dPCR assays using universal detection probes.Overall, this work underscores the potential of dPCR as a valuable tool for molecular profiling in stem cell research, offering robust, precise, and efficient gene expression analysis. The findings suggest that while qPCR remains a reliable method for routine applications, dPCR provides particular advantages for high-precision, low-sample input studies, expanding the analytical toolbox for stem cell differentiation and gene expression research.Induced pluripotent stem cells (iPSCs) have the potential to differentiate into any cell type, offering a valuable tool for research in developmental biology, regenerative medicine, and disease modeling. In this study, iPSCs were differentiated into cranial neural crest cells (CNCCs) over a 14-day period. RNA was extracted from these cells at day 0 (iPSCs), day 7, and day 14 to evaluate successful differentiation through the expression analysis of pluripotency and CNCC marker genes.A key focus was the conversion of existing qPCR assays into multiplexed RT-dPCR assays utilizing universal detection probes for precise gene expression analysis during the differentiation of induced pluripotent stem cells (iPSCs) into cranial neural crest cells (CNCCs). We aimed to leverage the superior precision, sensitivity, and multiplexing-degree of dPCR, particularly in quantifying low-abundance targets. We conducted a comparative analysis of the temporal expression patterns of crucial marker genes using both qPCR and dPCR.Our experiments revealed that the four five-plex dPCR assays could successfully detect and quantify the pluripotency and CNCC marker genes and evaluate CNCC differentiation. We observed the expected downregulation of pluripotency genes during differentiation. Conversely, the upregulation of CNCC markers validates the successful differentiation process. In conclusion, SYBR Green I gene expression qPCR assays can be readily converted into multiplex dPCR assays using universal detection probes.Overall, this work underscores the potential of dPCR as a valuable tool for molecular profiling in stem cell research, offering robust, precise, and efficient gene expression analysis. The findings suggest that while qPCR remains a reliable method for routine applications, dPCR provides particular advantages for high-precision, low-sample input studies, expanding the analytical toolbox for stem cell differentiation and gene expression research.B
Can Campylobacter jejuni form biofilm on uncoated plastic polymers?
No full textBiofilm formation is one the major strategies developed by bacteria to survive under extreme conditions. In the food industry, foodborne pathogens are able to adhere to and colonize diverse surfaces, such as plastic, stainless steel and glass, leading to biofilm formation, which endangers the effectivity of the cleaning and disinfection procedures. Among them, Campylobacter jejuni poses a significant food safety risk for causing most of the foodborne bacterial infectious gastroenteritis cases reported worldwide. However, their survival strategies are poorly understood. Previous studies have focused on evaluating the effect of (plasma‐)treated plastic surfaces with improved hydrophilicity on the ability of C. jejuni to form biofilm (Ortega-Sanz et al., 2024). However, little is known about the impact of pristine (micro)plastics with strong hydrophobic properties in the survival of the pathogen. In this study, we analysed the ability of 5 C. jejuni strains to form biofilm on flat-bottomed, non-treated 96-well microtiter plates made of polypropylene (PP) and polystyrene (PS) for 96 h at 22 °C and 37 °C under aerobiosis following the crystal violet staining method. Based on the formula of Stepanović et al. (2007), that classifies the isolates as non-, weak, moderate or strong biofilm formers, only 3 isolates (including the two isolates from human origin) were able to form biofilm on PP at both temperatures, although weakly, showing optical density values at 590 nm ranging between 0.098 and 0.103 (Figure 1). However, their ability to form biofilm showed no significant difference compared to the negative control (0.092 ± 0.002) (p > 0.05). The findings indicate that C. jejuni is not really capable of forming biofilm on the hydrophobic plastic materials tested, highlighting the relevance of the surface coating on the attachment and colonization of the pathogen.Biofilm formation is one the major strategies developed by bacteria to survive under extreme conditions. In the food industry, foodborne pathogens are able to adhere to and colonize diverse surfaces, such as plastic, stainless steel and glass, leading to biofilm formation, which endangers the effectivity of the cleaning and disinfection procedures. Among them, Campylobacter jejuni poses a significant food safety risk for causing most of the foodborne bacterial infectious gastroenteritis cases reported worldwide. However, their survival strategies are poorly understood. Previous studies have focused on evaluating the effect of (plasma‐)treated plastic surfaces with improved hydrophilicity on the ability of C. jejuni to form biofilm (Ortega-Sanz et al., 2024). However, little is known about the impact of pristine (micro)plastics with strong hydrophobic properties in the survival of the pathogen. In this study, we analysed the ability of 5 C. jejuni strains to form biofilm on flat-bottomed, non-treated 96-well microtiter plates made of polypropylene (PP) and polystyrene (PS) for 96 h at 22 °C and 37 °C under aerobiosis following the crystal violet staining method. Based on the formula of Stepanović et al. (2007), that classifies the isolates as non-, weak, moderate or strong biofilm formers, only 3 isolates (including the two isolates from human origin) were able to form biofilm on PP at both temperatures, although weakly, showing optical density values at 590 nm ranging between 0.098 and 0.103 (Figure 1). However, their ability to form biofilm showed no significant difference compared to the negative control (0.092 ± 0.002) (p > 0.05). The findings indicate that C. jejuni is not really capable of forming biofilm on the hydrophobic plastic materials tested, highlighting the relevance of the surface coating on the attachment and colonization of the pathogen.C
Do filled pauses serve a …um… communicative function? A comparison of self-directed and social speech
No full textSome authors argue that filled pauses serve a communicative function in speech. The current study aims to test this function by analyzing the difference in filler-use in a self-directed and social speech condition. Additionally, the influence of Autism Spectrum Disorder (ASD) traits and stress on the difference in filler-use between the two conditions were examined. In the first condition, participants described a series of different tangrams to themselves. In the second condition, participants described tangrams to another participant. More words and filled pauses were used when talking to someone else, but there were no more filled pauses per word. This suggests that filled pauses do not primarily serve as communicative signals. Instead they indicate that at least to some extent, they appear involuntary and automatically as a result of errors in the language production system. Furthermore, no significant correlation was found between the score on the ASD questionnaire or stress and the difference in fillers used in both speech conditions. Future research should consider experimental designs that more clearly differentiate between the presence or absence of a communicative goal, as the context of a monologue may still provide speakers with reasons to use communicative signals.Some authors argue that filled pauses serve a communicative function in speech. The current study aims to test this function by analyzing the difference in filler-use in a self-directed and social speech condition. Additionally, the influence of Autism Spectrum Disorder (ASD) traits and stress on the difference in filler-use between the two conditions were examined. In the first condition, participants described a series of different tangrams to themselves. In the second condition, participants described tangrams to another participant. More words and filled pauses were used when talking to someone else, but there were no more filled pauses per word. This suggests that filled pauses do not primarily serve as communicative signals. Instead they indicate that at least to some extent, they appear involuntary and automatically as a result of errors in the language production system. Furthermore, no significant correlation was found between the score on the ASD questionnaire or stress and the difference in fillers used in both speech conditions. Future research should consider experimental designs that more clearly differentiate between the presence or absence of a communicative goal, as the context of a monologue may still provide speakers with reasons to use communicative signals.A
A functional evaluation of the rotator cuff length after reverse total shoulder arthroplasty
No full textBackgroundA biomechanical result of the reverse total shoulder arthroplasty (rTSA) design is the medialization and inferiorization of the greater tuberosity, which influences the length of the cuff muscles. A well-known complication after rTSA is a lack of external rotation force. The purpose of this study was to investigate the difference in the length of the cuff muscles in a native shoulder and in shoulders treated with six commercial rTSA designs.MethodsSix implant systems were implanted on identical sawbones. A robotic setup was used to perform and control the shoulder’s position and measurements. The muscle lengths were measured by draw wire encoders.ResultsIn the three functional positions, the length of the cuff muscles was significantly lower in the Delta Xtend. In all measured positions, there was a strong negative correlation between the medialization of the humerus and the length of the cuff muscles. A lower position of the humerus after rTSA had a positive impact on the length of the infraspinatus and subscapularis.DiscussionThis study found a distinct difference in the slackening of the cuff muscles. Still, in the commercial reverse shoulder arthroplasty designs studied, this slackening never exceeded 15% in the above-mentioned maneuvers, which is functional and safe for the remnants of the muscles.BackgroundA biomechanical result of the reverse total shoulder arthroplasty (rTSA) design is the medialization and inferiorization of the greater tuberosity, which influences the length of the cuff muscles. A well-known complication after rTSA is a lack of external rotation force. The purpose of this study was to investigate the difference in the length of the cuff muscles in a native shoulder and in shoulders treated with six commercial rTSA designs.MethodsSix implant systems were implanted on identical sawbones. A robotic setup was used to perform and control the shoulder’s position and measurements. The muscle lengths were measured by draw wire encoders.ResultsIn the three functional positions, the length of the cuff muscles was significantly lower in the Delta Xtend. In all measured positions, there was a strong negative correlation between the medialization of the humerus and the length of the cuff muscles. A lower position of the humerus after rTSA had a positive impact on the length of the infraspinatus and subscapularis.DiscussionThis study found a distinct difference in the slackening of the cuff muscles. Still, in the commercial reverse shoulder arthroplasty designs studied, this slackening never exceeded 15% in the above-mentioned maneuvers, which is functional and safe for the remnants of the muscles.A
Genetic architecture of idiopathic inflammatory myopathies from meta‐analyses
No full textObjectiveIdiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome-wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome-wide myositis studies and analyzed the largest myositis data set to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes.MethodsWe performed association analyses on 14,903 individuals (3,206 patients and 11,697 controls) with genotypes and imputed data from the Trans-Omics for Precision Medicine reference panel. Fine-mapping and expression quantitative trait locus colocalization analyses in myositis-relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities.ResultsOur analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1, IRF4, DCAKD, and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti-histidyl-transfer RNA synthetase autoantibodies (anti-Jo-1). We also characterized effects of HLA region variants and the role of C4. Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in Epstein-Barr virus (EBV)-transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74, CIITA, NR1H4, and TXNIP, for future investigation.ConclusionOur study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.ObjectiveIdiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome-wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome-wide myositis studies and analyzed the largest myositis data set to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes.MethodsWe performed association analyses on 14,903 individuals (3,206 patients and 11,697 controls) with genotypes and imputed data from the Trans-Omics for Precision Medicine reference panel. Fine-mapping and expression quantitative trait locus colocalization analyses in myositis-relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities.ResultsOur analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1, IRF4, DCAKD, and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti-histidyl-transfer RNA synthetase autoantibodies (anti-Jo-1). We also characterized effects of HLA region variants and the role of C4. Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in Epstein-Barr virus (EBV)-transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74, CIITA, NR1H4, and TXNIP, for future investigation.ConclusionOur study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.A
The impact of weather and climate change on maize prices and yields
No full textPublic defense: 2025-06-24D