bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing pulmonary chest x-ray classification with stacked feature ensemble and swin transformer integration
Authors: Mohanty Manas Ranjan , Mallick Pradeep Kumar , Reddy Annapareddy V N
Published: October 2024

This research presents an integrated framework designed to automate the classification of pulmonary chest x-ray images. Leveraging convolutional neural networks (CNNs) with a focus on transformer architectures, the aim is to improve both the accuracy and efficiency of pulmonary chest x-ray image analysis. A central aspect of this approach involves utilizing pre-trained networks such as VGG16, ResNet50, and MobileNetV2 to create a feature ensemble. A notable innovation is the adoption of a stacked ensemble technique, which combines outputs from multiple pre-trained models to generate a comprehensive feature representation. In the feature ensemble approach, each image undergoes individual processing through the three pre-trained networks, and pooled images are extracted just before the flatten layer of each model. Consequently, three pooled images in 2D grayscale format are obtained for each original image. These pooled images serve as samples for creating 3D images resembling RGB images through stacking, intended for classifier input in subsequent analysis stages. By incorporating stacked pooling layers to facilitate feature ensemble, a broader range of features is utilized while effectively managing complexities associated with processing the augmented feature pool. Moreover, the study incorporates the Swin Transformer architecture, known for effectively capturing both local and global features. The Swin Transformer architecture is further optimized using the artificial hummingbird algorithm (AHA). By fine-tuning hyperparameters such as patch size, multi-layer perceptron (MLP) ratio, and channel numbers, the AHA optimization technique aims to maximize classification accuracy. The proposed integrated framework, featuring the AHA-optimized Swin Transformer classifier utilizing stacked features, is evaluated using three diverse chest x-ray datasets—VinDr-CXR, PediCXR, and MIMIC-CXR. The observed accuracies of 98.874%, 98.528%, and 98.958% respectively, underscore the robustness and generalizability of the developed model across various clinical scenarios and imaging conditions.
Aligning the Western Balkans power sectors with the European Green Deal
Authors: Fejzić Emir , Niet Taco , Wade Cameron , Usher Will
Published: October 2024

Located in Southern Europe, the Drina River Basin is shared between Bosnia and Herzegovina, Montenegro, and Serbia. The power sectors of the three countries have an exceptionally high dependence on coal for power generation. In this paper, we analyse different development pathways for achieving climate neutrality in these countries and explore the potential of variable renewable energy (VRE) and its role in power sector decarbonization. We investigate whether hydro and non-hydro renewables can enable a net-zero transition by 2050 and how VRE might affect the hydropower cascade shared by the three countries. The Open-Source Energy Modelling System (OSeMOSYS) was used to develop a model representation of the countries’ power sectors. Findings show that the renewable potential of the countries is a significant 94.4 GW. This potential is 68% higher than previous assessments have shown. Under an Emission Limit scenario assuming net zero by 2050, 17% of this VRE potential is utilized to support the decarbonization of the power sectors. Additional findings show a limited impact of VRE technologies on total power generation output from the hydropower cascade. However, increased solar deployment shifts the operation of the cascade to increased short-term balancing, moving from baseload to more responsive power generation patterns. Prolonged use of thermal power plants is observed under scenarios assuming high wholesale electricity prices, leading to increased emissions. Results from scenarios with low cost of electricity trade suggest power sector developments that lead to decreased energy security.
Fate of surface gaps in magnetic topological insulators
Authors: Rostami Habib , Moghaddam Ali G
Published: October 2024

In magnetic topological insulators, the surface states can exhibit a gap due to the breaking of time-reversal symmetry. Various experiments, while suggesting the existence of the surface gap, have raised questions about its underlying mechanism in the presence of different magnetic orderings. Here, we demonstrate that magnon-mediated electron-electron interactions, whose effects are not limited to the surfaces perpendicular to the magnetic ordering, can significantly influence surface states and their effective gaps. On the surfaces perpendicular to the spin quantization axis, many-body interactions can enhance the band gap to a degree that surpasses the non-interacting scenario. Then, on surfaces parallel to the magnetic ordering, we find that strong magnon-induced fermionic interactions can lead to features resembling a massless-like gap. These remarkable results largely stem from the fact that magnon-mediated interactions exhibit considerable long-range behavior compared to direct Coulomb interactions among electrons, thereby dominating the many-body properties at the surface of magnetic topological insulators.
Reimagining anti-inflammatory drugs delivery: the integration of ordered mesoporous silica and MOF materials for enhanced therapeutic outcomes
Authors: Galarda Aleksandra , Panek Rafal , Goscianska Joanna
Published: October 2024

Migraine, one of the neurological conditions, affects approximately 15% of the global population. It is characterized by intense headaches accompanied by nausea, vomiting, and heightened sensitivity to light. The first line of drugs for treating migraine are non-steroidal anti-inflammatory drugs. Unfortunately, these medications suffer from poor solubility in water, uncontrolled release, and numerous adverse side effects. In order to maximize their therapeutic effect by preventing premature release and degradation, novel drug delivery systems based on composites are being dynamically developed. Herein, the biocompatible ketoprofen (K), naproxen sodium (NS), and diclofenac sodium (DS) vehicles integrating ordered mesoporous silica (SBA-16) with Fe-based metal–organic frameworks (MIL-101(Fe)) were synthesized via the solvothermal method. The composites were characterized by different percentages of MIL-101(Fe) (25 and 50 wt.%), which had a significant impact on their porosity, structure, and number of functional groups. The SBA-16@MIL-101(Fe)-25 and SBA-16@MIL-101(Fe)-50 samples exhibited BET surface areas of 768 and 324 m2 g−1, respectively. Their sorption capacities towards selected anti-inflammatory drugs were in the range of 141–318 mg g−1 for K, 481–490 mg g−1 for NS, and 246–589 mg g−1 for DS, notably exceeding the values obtained for pure mesoporous silica (5–9 mg g−1). Morphological defects and specific functional groups, derived from SBA-16 and MIL-101(Fe), contributed to generating new adsorption sites in composites, enhancing host-guest interactions. The drug release profiles were determined by the carrier porosity, surface charge, and the presence of functional groups. The diffusion of K and DS from the composites into the phosphate buffer (pH 7.7), mimicking rectal fluid, occurred in a more controlled manner compared to pristine silica. The SBA-16@MIL-101(Fe)-50 carrier released 82% of K and 90% of DS over 24 h.
Integrating canonical correlation analysis with machine learning for power quality disturbance classification
Authors: Singh Gurpreet , Pal Yash , Kumar Dahiya Anil
Published: October 2024

Recently, the rapid growth of Renewable Energy Resources (RER) in power generation has resulted in the frequent occurrence of Power Quality Disturbances (PQDs) within the power system. The timely and accurate detection of these PQDs is critical for maintaining good power quality while integrating RER into hybrid power systems to make them more robust and stable. In this paper, a multi-view dimensionality reduction approach based on Canonical Correlation Analysis (CCA) is proposed to differentiate different types of PQDs. Here, a dataset of 29 types of PQDs which include nine single types and twenty multiple types of PQDs have been generated using their mathematical model in MATLAB for experimentation. CCA being multi-view dimensionality reduction technique maximizes the correlation between two different views of the data. Here two cases of datasets have been considered for further exploration, Case 1: PQDs without noise and with 20 dB noise, Case 2: PQDs with 20 dB and 30 dB noise. Furthermore, to test the efficacy of CCA in both cases, the extracted features have been tested using four different classifiers i.e. K-Nearest Neighbour (KNN), Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF). The performance of each of the classifiers has been tested on five different performance metrics such as precision, recall, F1 score, hamming loss and accuracy and the results shows that the proposed technique of multi-view dimensionality reduction is capable of classifying the PQDs with two different views at a time.
AGCNAF: predicting disease-gene associations using GCN and multi-head attention to fuse the similarity features
Authors: Ma Jinlong , Qin Tian , Zhai Meijing , Cai Liangliang
Published: October 2024

Association prediction between diseases and genes is a critical step in revealing the molecular mechanisms of diseases and developing drug treatment strategies. With the explosive growth of data in the biomedical field, how to effectively utilize these data for accurate prediction has become a hotspot and challenge in current research. To overcome the limitations of current prediction methods in dealing with complex biological network structures and feature extraction, this study proposes AGCNAF, a method that combines an unsupervised Graph Convolutional Network (GCN) and a multi-head attention mechanism. The metagraph-guided random walk strategy enables AGCNAF to capture local and high-order topological structures in the graph, while GCN is responsible for realizing deep feature extraction of these structures. By incorporating similarity features through the multi-attention mechanism, AGCNAF achieves effective integration of global and local features, which significantly improves the prediction performance. By utilizing the machine learning binary classification model for prediction, the experimental results through five-fold cross-validation show that AGCNAF demonstrates significant advantages in prediction performance compared to existing methods, with its AUC and AUPR reaching 0.9686 and 0.9709, respectively, and the AUC up to 0.9812 under specific conditions. To verify the practical application value of AGCNAF, this study also conduct case studies on Alzheimer’s disease, lung cancer, and breast cancer. The results further confirm the excellent performance of AGCNAF in identifying potential disease-gene associations, which opens up new possibilities for future disease-gene research.
Comparative linkage mapping to investigate synteny and recombination in social Vespidae
Authors: Zarate Daniela , Canova Alyssa , Wilson Rankin Erin E , Loope Kevin , Purcell Jessica
Published: October 2024

Genetic linkage maps are valuable resources for investigating chromosomal structure, quantifying karyotype, estimating recombination rates, and improving preexisting genome assemblies. Comparative linkage mapping, in turn, broadens our understanding of the phylogenetic history of these genomic features. Through an assessment of synteny (the conservation of gene order on homologous chromosomes in different species) and variation in recombination rate, we can begin to understand how genomic features change during the evolution of distinct species. Here, we construct high-density genetic linkage maps for 3 Vespidae wasp species from the Vespula genus: Vespula consobrina, Vespula pensylvanica, and Vespula vidua to investigate shared genomic architecture between these 3 yellowjacket wasp species. We show that these species exhibit high levels of collinearity, often in chromosome-length blocks of synteny, with some evidence for small interchromosomal rearrangements. We also identify 2 “inversions” in all 3 species that are likely artifacts from the genome assembly process. In addition, we map genome-wide recombination rates and reveal the recombination landscape to be highly variable on intrachromosomal, interchromosomal, and interspecific scales. Genome-wide recombination rates are high for all three Vespula species, (V. pensylvanica: 22.7 cM/Mb, V. consobrina: 24.3 cM/Mb, and V. vidua: 24.7 cM/Mb), which is consistent with findings of high recombination rates for other eusocial species. Our high-quality linkage maps will be resources for ongoing evolutionary genetics studies interested in the genome evolution of social wasps.
Effects of exercise referral schemes enhanced with behavioural self-management strategies on functional capacity and self-reported disability in community-dwelling older adults. Secondary results from the SITLESS multi-country, three-armed randomized controlled trial
Authors: Olsen Pia Ø , Tully Mark A , del Pozo Cruz Borja , Giné-Garriga Maria , Coll-Planas Laura , Roqué Marta , Rothenbacher Dietrich , Dallmeier Dhayana , Sansano-Nadal Oriol , Blackburn Nicole E , Wilson Jason J , Skjødt Mathias , Caserotti Paolo ,   SITLESS Group, Coll-Planas Laura , Giné-Garriga Maria , Domingo Àlex , Roqué Marta , Salvà Antoni , Guerra Míriam , Martín-Borràs Carme , Jerez-Roig Javier , Sansano-Nadal Oriol , Santiago Marta , Ferry Kelly , Caserotti Paolo , Skjødt Mathias , Tully Mark A , Kee Frank , Wilson Jason J , Blackburn Nicole E , McMullan Ilona , Denkinger Michael , Rothenbacher Dietrich , Wirth Katharina , Dallmeier Dhayana , McIntosh Emma , Deidda Manuela , Lefebvre Guillaume , González Denise
Published: October 2024

Background

Exercise referral schemes (ERS) are an effective strategy for increasing physical activity (PA) in older adults. Behavioural self-management strategies (SMS) may augment the maintenance of PA and associated benefits in this population, resulting in preservation of the functional capacity and prevention of disability over the long-term.

Aim

The primary aim was to investigate the long-term (22-months) effects of ERS enhanced with SMS on functional capacity assessed by the Short Physical Performance Battery (SPPB) compared to ERS (primary comparison) and a control condition (CTRL).

Secondarily, between-group effects after 4 and 16 months on the SPPB and self-reported disability outcomes were investigated.

Methods

1360 physically inactive community-dwelling older adults ≥65 years from four European countries were randomized into (i) 16 weeks ERS enhanced with SMS (ERS-SMS), (ii) ERS alone and (iii) CTRL. In addition to SPPB, self-reported function and disability were assessed by the short-form late life function and disability index and with a six-item activity of daily living questionnaire.

Results

No long-term effects were found for the SPPB-score in ERS-SMS vs ERS (0.21 point, 95% CI [−0.04, 0.46]). Significant group × time effects were observed for the SPPB-score after 4 months in favour of ERS-SMS over CTRL (0.51 point, 95% CI [0.29, 0.73]) and ERS (0.46 point, 95% CI [0.24, 0.68]).

Conclusion

The study did demonstrate differences, in favour of ERS + SMS, but on SPPB these were small, and not sustained over time. The additional effect of SMS was inconsistent and uncertain.
Real-world mobility recovery after hip fracture: secondary analyses of digital mobility outcomes from four randomized controlled trials
Authors: Engdal Monika , Taraldsen Kristin , Jansen Carl-Philipp , Peter Raphael Simon , Vereijken Beatrix , Becker Clemens , Helbostad Jorunn Laegdheim , Klenk Jochen
Published: October 2024

Background

The main focus of rehabilitation following hip fracture is to regain mobility.

Objectives

To estimate the progression of real-world mobility the first year after hip fracture using digital mobility outcomes.

Design

An exploratory, prospective cohort study with pooled data from four previously conducted clinical trials.

Setting and Subjects

We combined data from the Trondheim Hip Fracture Trial and Eva-Hip Trial in Trondheim, Norway, and the PROFinD 1 and PROFinD 2 trials in Stuttgart and Heidelberg, Germany, resulting in a sample of 717 hip fracture patients aged ≥65 years.

Methods

Each of the trials assessed mobility using body-fixed sensors (activPAL) at three time points, collectively providing observations across the entire first year post-surgery. The following 24-h DMOs were calculated: total walking duration (minutes), maximum number of steps within a walking bout, and number of sit-to-stand-to-walk transfers. Continuous 1-year progression of the median, the 25th percentile, and the 75th percentile were estimated using quantile regression models with splines.

Results

The dataset contained 5909 observation days. The median daily total walking duration increased until 36 weeks post-surgery reaching 40 min; daily maximum number of steps within a walking bout increased during the first eight weeks and then stabilized at less than 100 steps; daily sit-to-stand-to-walk transfers reached a plateau after 6 weeks with less than 40 transfers.

Conclusions

The three DMOs progressed differently and attained plateau levels at varying times during the first year after hip fracture, indicating that these Digital Mobility Outcomes provide complementary information about different aspects of mobility recovery.
Assessing 1-year sodium-glucose co-transporter-2 inhibitor tolerance in older adults
Authors: Schafer Stephanie M , Zeithamel Marcia C , Waterbury Nancee V , Lund Brian C
Published: October 2024

Background

Evidence concerning tolerability of sodium-glucose co-transporter-2 (SGLT2) inhibitors in older adults is limited due to under-representation in clinical trials. Our study aimed to determine the extent to which SGLT2 inhibitor intolerance increases with age and explore additional factors associated with intolerance.

Methods

This retrospective observational study included patients in the Veterans Health Administration who initiated an SGLT2 inhibitor between 1 January 2013 and 31 December 2021. One-year discontinuation served as a proxy for intolerance. Relative risk (RR) for 1-year discontinuation was contrasted across age groups using log-binomial regression to adjust for confounding.

Results

Of 232 495 patients who initiated an SGLT2 inhibitor, 60 582 (26.1%) discontinued within one year. A difference was observed across age groups, <65, 65–74, 75–84 and ≥85 years, where 25.8%, 25.3%, 28.5% and 34.9% of patients discontinued, respectively (P < .001). After adjustment for confounding factors, patients 75–84 and ≥85 years were at 8% (RR = 1.08; 95% CI: 1.05, 1.10) and 21% increased risk (RR = 1.21; 95% CI: 1.15, 1.26) for discontinuation, respectively, relative to patients <65 years. Additional risk factors were identified: female (RR = 1.41; 95% CI: 1.37, 1.45), estimated glomerular filtration rate stage 4 (RR = 1.49; 95% CI: 1.39, 1.60), underweight (RR = 1.15; 95% CI: 1.03, 1.29), urinary tract infection history (RR = 1.25; 95% CI: 1.21, 1.30) and yeast infection history (RR = 1.39; 95% CI: 1.27, 1.51).

Conclusion

No clinically meaningful differences in SGLT2 inhibitor intolerance were observed in patients up to 84 years. Our findings support having closer follow-up when initiating in patients 85 years and older.
Macro- and micro-geographical genetic variation in early-fitness traits in populations of maritime pine (Pinus pinaster)
Authors: Solé-Medina Aida , Hurel Agathe , Avanzi Camilla , González-Martinez Santiago C , Vendramin Giovanni G , Bagnoli Francesca , Piotti Andrea , Marchi Maurizio , Spanu Ilaria , Robledo-Arnuncio Juan José , Ramírez-Valiente José Alberto
Published: October 2024

Background and Aims

Assessing adaptive genetic variation and its spatial distribution is crucial to conserve forest genetic resources and manage species’ adaptive potential. Macro-environmental gradients commonly exert divergent selective pressures that enhance adaptive genetic divergence among populations. Steep micro-environmental variation might also result in adaptive divergence at finer spatial scales, even under high gene flow, but it is unclear how often this is the case. Here, we assess genetic variation in early-fitness traits among distant and nearby maritime pine (Pinus pinaster) populations, to investigate climatic factors associated with trait divergence, and to examine trait integration during seedling establishment.

Methods

Open pollinated seeds were collected from seven population pairs across the European species distribution, with paired populations spatially close (between <1 and 21 km) but environmentally divergent. Seeds were sown in semi-natural conditions at three environmentally contrasting sites, where we monitored seedling emergence, growth and survival.

Key Results

At large spatial scales, we found significant genetic divergence among populations in all studied traits, with certain traits exhibiting an association with temperature and precipitation gradients. Significant trait divergence was also detected between pairs of nearby populations. In addition, we found consistent trait correlations across experimental sites; notably, heavier seeds and earlier seedling emergence were both associated with higher seedling survival and fitness over two years in all experimental conditions.

Conclusions

We identified mean annual temperature and precipitation seasonality as potential drivers of P. pinaster population divergence in the studied early-life traits. Populations genetically diverge also at local spatial scales, potentially suggesting that divergent natural selection can override gene flow along local-scale ecological gradients. These results suggest the species exhibits substantial adaptive potential that has allowed it to survive and evolve under contrasting environmental conditions.
Japanese Performance Profile on the WAIS-IV and Purported Cultural Influences
Authors: Fujii Daryl E , Kaseda Erin T , Sakamoto-Pomeroy Maiko
Published: October 2024

Objective

The present exploratory study aimed to examine the potential impact of culture on cognitive skills and intelligence by comparing the Japanese Wechsler Adult Intelligence Scale-IV (WAIS-IV) (JW) subtests, IQs, and index scores to those of the U.S. WAIS-IV (USW).

Method

JW raw scores corresponding to a scaled score of 10 for each subtest were scored with USW norms. Subtest, index, and IQ scores were then calculated for each age range. The impact of education on scores was evaluated through ratio of educational attainment for each cohort of the Japanese and US samples. Japanese and US data were compared using one-sample t-tests. Correlations between subtest, index, and IQ scores and education were calculated.

Results

The USW sample performed higher than the JW sample on verbal comprehension subtests, while the JW sample demonstrated stronger performances in processing speed and perceptual reasoning subtests. However, all scores with the exception of Block Design, Matrix Reasoning, and Figure Weights were significantly associated with differential educational attainment between the two countries. Educational differences were linearly associated with age with the higher educational attainment for younger Japanese age groups and higher attainment for the older US cohorts.

Conclusions

The present study demonstrates cognitive differences between Japan and the USA. Performance on the WAIS-IV subtest and composite measures are highly correlated with education. Cultural factors impacting the cognitive profile of the Japanese sample such as differences in worldview, customs, educational systems, and writing system, were proposed. Clinical neuropsychologists should take these aspects into account when administering and interpreting test results.
Neurocognitive Intraindividual Variability in Veterans with Mild Traumatic Brain Injury History and Posttraumatic Stress Disorder
Authors: Rau Holly K , Sheppard David P , Karr Justin E , Hendrickson Rebecca C , Schindler Abigail , Peskind Elaine R , Pagulayan Kathleen F
Published: October 2024

Objective

Veterans with a history of blast-related mild traumatic brain injury (mTBI) and posttraumatic stress disorder (PTSD) may be at risk for greater cognitive concerns and worse functional outcomes compared to those with either condition in isolation. However, traditional neuropsychological assessment approaches have yielded equivocal results in these populations. The present study examined an alternative method for detecting subtle cognitive inefficiencies: neurocognitive intraindividual variability (IIV), a measure of within-person performance consistency.

Method

Participants were 79 male Veterans with a history of blast-related mTBI and current PTSD (mTBI/PTSD group; n = 54) or neither diagnosis (controls; n = 25). Mean T-scores and IIV scores were calculated from neuropsychological measures of attention and speed of information processing (A/SoP) as well as executive functioning (EF).

Results

Global IIV was significantly higher in the mTBI/PTSD group compared to controls (p = .047, Cohen’s d = 0.49). At the domain level, larger effect sizes were observed for EF IIV (Cohen’s d = 0.46) compared to A/SoP IIV (d = 0.32), although neither were statistically significant. Within the mTBI/PTSD group, higher Global IIV was associated with worse self-reported executive dysfunction, psychological quality of life, and cognitive post-concussive symptoms; at the domain level, these clinical outcomes were generally associated with greater A/SoP IIV (but not EF IIV).

Conclusion

Findings extend previous investigations of neurocognitive IIV in individuals with a history of mTBI across PTSD status. Among Veterans with a history of mTBI and comorbid PTSD, neurocognitive variability may be a better indicator of self-reported cognitive inefficiencies and Veteran experience of daily cognitive functioning than mean neuropsychological performances.
Public information use—are invasive demersal fish species more effective than natives?
Authors: Augustyniak Mateusz , Kobak Jarosław , Jermacz Łukasz , Adamiak Agnieszka , Kakareko Tomasz
Published: October 2024

Organisms determine environmental quality using their senses and personal experience (personal information) but can also use byproducts of other individuals’ activities (i.e. public information). The ability to use public information originating from both con- and heterospecifics gives an advantage over individuals relying only on personal information or conspecific cues. The role of public information in invasion ecology is of high concern, as any differences in this aspect between alien and native species may determine the success of the former. Here, we studied 2 pairs of sympatric invasive and native demersal fish species (racer goby Babka gymnotrachelus/European bullhead Cottus gobio; monkey goby Neogobius fluviatilis/gudgeon Gobio gobio) facing 2 types of public cues (associated with antipredatory and foraging behavior). We used them as a model to check if the invaders could use public information from more sources than the natives. Both invaders and the native gudgeon used cues from con- and heterospecifics, exhibiting antipredatory behavior, while the native bullhead failed to recognize such cues from heterospecifics. The monkey goby and both native species were attracted to foraging cues from donors less likely to exert competitive pressure on the observer (i.e. native species rather than potentially more aggressive invaders). On the other hand, the racer goby appeared unable to correctly recognize heterospecific foraging cues. Our results showed that public cues can enable invaders to read threat from a wide range of individuals and to find optimal food patches, which may contribute to their invasion success.
MicroNet-MIMRF: a microbial network inference approach based on mutual information and Markov random fields
Authors: Feng Chenqionglu , Jia Huiqun , Wang Hui , Wang Jiaojiao , Lin Mengxuan , Hu Xiaoyan , Yu Chenjing , Song Hongbin , Wang Ligui
Published: October 2024

Motivation

The human microbiome, comprises complex associations and communication networks among microbial communities, which are crucial for maintaining health. The construction of microbial networks is vital for elucidating these associations. However, existing microbial networks inference methods cannot solve the issues of zero-inflation and non-linear associations. Therefore, necessitating novel methods to improve the accuracy of microbial networks inference.

Results

In this study, we introduce the Microbial Network based on Mutual Information and Markov Random Fields (MicroNet-MIMRF) as a novel approach for inferring microbial networks. Abundance data of microbes are modeled through the zero-inflated Poisson distribution, and the discrete matrix is estimated for further calculation. Markov random fields based on mutual information are used to construct accurate microbial networks. MicroNet-MIMRF excels at estimating pairwise associations between microbes, effectively addressing zero-inflation and non-linear associations in microbial abundance data. It outperforms commonly used techniques in simulation experiments, achieving area under the curve values exceeding 0.75 for all parameters. A case study on inflammatory bowel disease data further demonstrates the method’s ability to identify insightful associations. Conclusively, MicroNet-MIMRF is a powerful tool for microbial network inference that handles the biases caused by zero-inflation and overestimation of associations.

Availability and implementation

The MicroNet-MIMRF is provided at https://github.com/Fionabiostats/MicroNet-MIMRF.
GEEES: inferring cell-specific gene–enhancer interactions from multi-modal single-cell data
Authors: Chen Shuyang , Keleş Sündüz
Published: October 2024

Motivation

Gene–enhancer interactions are central to transcriptional regulation. Current multi-modal single-cell datasets that profile transcriptome and chromatin accessibility simultaneously in a single cell are yielding opportunities to infer gene–enhancer associations in a cell type specific manner. Computational efforts for such multi-modal single-cell datasets thus far focused on methods for identification and refinement of cell types and trajectory construction. While initial attempts for inferring gene–enhancer interactions have emerged, these have not been evaluated against benchmark datasets that materialized from bulk genomic experiments. Furthermore, existing approaches are limited to inferring gene–enhancer associations at the level of grouped cells as opposed to individual cells, thereby ignoring regulatory heterogeneity among the cells.

Results

We present a new approach, GEEES for “Gene EnhancEr IntEractions from Multi-modal Single Cell Data,” for inferring gene–enhancer associations at the single-cell level using multi-modal single-cell transcriptome and chromatin accessibility data. We evaluated GEEES alongside several multivariate regression-based alternatives we devised and state-of-the-art methods using a large number of benchmark datasets, providing a comprehensive assessment of current approaches. This analysis revealed significant discrepancies between gold-standard interactions and gene–enhancer associations derived from multi-modal single-cell data. Notably, incorporating gene–enhancer distance into the analysis markedly improved performance across all methods, positioning GEEES as a leading approach in this domain. While the overall improvement in performance metrics by GEEES is modest, it provides enhanced cell representation learning which can be leveraged for more effective downstream analysis. Furthermore, our review of existing experimentally driven benchmark datasets uncovers their limited concordance, underscoring the necessity for new high-throughput experiments to validate gene–enhancer interactions inferred from single-cell data.

Availability and implementation

https://github.com/keleslab/GEEES.
Bayesian inference for group-level cortical surface image-on-scalar regression with Gaussian process priors
Authors: Whiteman Andrew S , Johnson Timothy D , Kang Jian
Published: October 2024

In regression-based analyses of group-level neuroimage data, researchers typically fit a series of marginal general linear models to image outcomes at each spatially referenced pixel. Spatial regularization of effects of interest is usually induced indirectly by applying spatial smoothing to the data during preprocessing. While this procedure often works well, the resulting inference can be poorly calibrated. Spatial modeling of effects of interest leads to more powerful analyses; however, the number of locations in a typical neuroimage can preclude standard computing methods in this setting. Here, we contribute a Bayesian spatial regression model for group-level neuroimaging analyses. We induce regularization of spatially varying regression coefficient functions through Gaussian process priors. When combined with a simple non-stationary model for the error process, our prior hierarchy can lead to more data-adaptive smoothing than standard methods. We achieve computational tractability through a Vecchia-type approximation of our prior that retains full spatial rank and can be constructed for a wide class of spatial correlation functions. We outline several ways to work with our model in practice and compare performance against standard vertex-wise analyses and several alternatives. Finally, we illustrate our methods in an analysis of cortical surface functional magnetic resonance imaging task contrast data from a large cohort of children enrolled in the adolescent brain cognitive development study.
Derivation of outcome-dependent dietary patterns for low-income women obtained from survey data using a supervised weighted overfitted latent class analysis
Authors: Wu Stephanie M , Williams Matthew R , Savitsky Terrance D , Stephenson Briana J K
Published: October 2024

Poor diet quality is a key modifiable risk factor for hypertension and disproportionately impacts low-income women. Analyzing diet-driven hypertensive outcomes in this demographic is challenging due to the complexity of dietary data and selection bias when the data come from surveys, a main data source for understanding diet-disease relationships in understudied populations. Supervised Bayesian model-based clustering methods summarize dietary data into latent patterns that holistically capture relationships among foods and a known health outcome but do not sufficiently account for complex survey design. This leads to biased estimation and inference and lack of generalizability of the patterns. To address this, we propose a supervised weighted overfitted latent class analysis (SWOLCA) based on a Bayesian pseudo-likelihood approach that integrates sampling weights into an exposure-outcome model for discrete data. Our model adjusts for stratification, clustering, and informative sampling, and handles modifying effects via interaction terms within a Markov chain Monte Carlo Gibbs sampling algorithm. Simulation studies confirm that the SWOLCA model exhibits good performance in terms of bias, precision, and coverage. Using data from the National Health and Nutrition Examination Survey (2015–2018), we demonstrate the utility of our model by characterizing dietary patterns associated with hypertensive outcomes among low-income women in the United States.
A new robust approach for the polytomous logistic regression model based on Rényi’s pseudodistances
Authors: Castilla Elena
Published: October 2024

This paper presents a robust alternative to the maximum likelihood estimator (MLE) for the polytomous logistic regression model, known as the family of minimum Rènyi Pseudodistance (RP) estimators. The proposed minimum RP estimators are parametrized by a tuning parameter $\alpha \ge 0$, and include the MLE as a special case when $\alpha =0$. These estimators, along with a family of RP-based Wald-type tests, are shown to exhibit superior performance in the presence of misclassification errors. The paper includes an extensive simulation study and a real data example to illustrate the robustness of these proposed statistics.
Melanoma arising from pre-existing naevus in carriers of a germline CDKN2A pathogenic variant
Authors: Rauwerdink Daan J W , Hoogland Yann , Schrader Anne  M R , Potjer Thomas P , Kapiteijn Ellen , van der Hage Jos A , van Doorn Remco
Published: October 2024

In this study we used total-body photography (TBP) to determine whether melanoma emerges from a pre-existing naevi or normal-appearing skin in individuals with the pathogenic CDKN2A variant. In total, 60 melanoma cases occurred in 44 CDKN2A germline carriers. In addition, we observed that 78% of the 60 included melanoma cases developed from pre-existing naevi, significantly higher than the 30% reported for sporadic melanoma. This high incidence may be due to the numerous atypical naevi and early bi-allelic loss of CDKN2A. Our findings underscore the importance of routine TBP in these patients for early detection of melanoma. More than previously appreciated, the surgical removal of melanocytic naevi in these patients at high risk may prevent melanoma development.
Biologics in congenital ichthyosis: are they effective?
Authors: Mazereeuw-Hautier Juliette , Granier Tournier Céline , Hernandez-Martin Angela , Milesi Sarah , Texier Hélène , Severino-Freire Maëlla , Bellon Nathalia , Bodemer Christine , Gruber Robert , Mahé Emmanuel , Morice Picard Fanny , Hannula-Jouppi Katariina , Murase Jenny E , Barbarot Sébastien , Cohen-Barak Eran , Torres-Pradilla Maurico , Bruckner Anna , Levy Moise , Koh Mark J A , Masson Regnault Marie , Rossel Vanya , Chiaverini Christine , Arkin Lisa M , Ott Hagen , Has Cristina , Süβmuth Kira , Gostynski Antoni , Shourick Jason , Paller Amy S
Published: October 2024

Background

Congenital ichthyoses comprise a heterogeneous group of genetic diseases that require lifelong treatment and have a major impact on patients’ quality of life. Conventional treatments reduce scaling and skin discomfort; however, they usually have little or no effect on erythema and pruritus. The identification of cytokine alterations in congenital ichthyoses has raised the possibility of repurposing currently available biologics. Several case reports have reported success with different biologics.

Objectives

To report the real-life effects of biologics on congenital ichthyoses.

Methods

This was a retrospective observational international multicentric study of patients with congenital ichthyoses treated with at least one biologic for a minimum of 3 months. The effect of the biologics was evaluated using an Investigator Global Assessment for change (IGA-C) scale. A comprehensive literature search was performed in parallel.

Results

Ninety-eight patients were included [mean (SD) age of 19.7 years, 50 female patients]. Patients with Netherton syndrome (NS) or congenital ichthyosiform erythroderma (CIE) represented the majority of patients (30% and 21%, respectively). Most patients (85%) had a severe or very severe form of congenital ichthyoses. The most frequently used biologics were inhibitors targeting interleukin (IL)-17, IL-12/IL-23 or the IL-4 receptor (IL-4R). The mean (SD) duration of treatment was 22.1 (20.1) months. There were 45 responders (46%), including 18 (18%) who were good responders; all had a subset of erythrodermic congenital ichthyoses and received one of the three main biologics. In patients with NS and CIE, IL-12/IL-23 and IL-4R inhibitors tended to be most effective. The literature review revealed a shorter mean (SD) duration of biologic treatment [11.5 (8.5) months] and higher percentage of responders (86%), suggesting reporter bias.

Conclusions

This series identified subsets of congenital ichthyoses that may respond to biologics and will help with the design of future clinical trials of biologics for congenital ichthyoses.
Post-mortem CT service structures in non-suspicious death investigations
Authors: Davendralingam Natasha , Brookes Amy-Lee , Shah Mohammad Ali , Shelmerdine Susan C
Published: October 2024

Post-mortem CT (PMCT) is increasingly used in adult post-mortem investigations as a non-invasive alternative to traditional autopsies. Using PMCT supports death investigations in the face of severe pathologist workforce shortages and the less invasive nature maintains respect for cultural sensitivities. This article reviews the diverse service structures of PMCT, highlighting the importance of customizing these structures to meet the specific needs of various coronial jurisdictions. These jurisdictions often face challenges such as limited access to imaging facilities and logistical issues with geographically dispersed mortuaries. We outline options for leading and operating PMCT services, including models led by pathologists, radiologist, or a hybrid of the two; use of static, relocatable, or mobile CT scanning units; as well as making the most of existing resources such as NHS or private scanning facility scanners already in place. We also explore different PMCT reporting structures through in-house NHS radiologists, combined in-house and teleradiology, or fully outsourced teleradiology services. Each of these offerings provides different levels of efficiency, cost-effectiveness, data security and challenges to set-up. Where applicable, we present and describe real-world examples as case studies for readers interested in replicating existing models.
Parathyroid gland identification and angiography classification using simple machine learning methods
Authors: McEntee Philip D , Greevy Joseph E , Triponez Frédéric , Demarchi Marco S , Cahill Ronan A
Published: October 2024

Background

Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance between surgeons, we developed an automatic computational quantification method using computer vision that portrays expert interpretation of visualized parathyroid gland near-infrared indocyanine green angiographic fluorescence signals.

Methods

Near-infrared indocyanine green-parathyroid gland angiography video recordings (Fluobeam® LX, Fluoptics, Grenoble—part of Getinge—Göteborg) from patients undergoing endocrine cervical surgery in a high-volume unit were used for model development. Computation (MATLAB, Mathworks, Ireland) included segmentation-identification of the parathyroid gland (by autofluorescence), image stabilization (by linear translation) and adjusted time-fluorescence intensity profile generation. Relative upslope and maximum intensity ratios then trained a simple logistic regression model based on expert interpretation and outcome (including hypoparathyroidism), with subsequent unseen testing for validation.

Results

The model was trained on 37 patient videos (45 glands, 29 judged well perfused by parathyroid gland angiography experts), achieving feature data separation with 100% accuracy, and tested on 22 unseen videos (27 glands, 15 judged well perfused), including four in real time. Segmentation-guided parathyroid gland detection correctly identified all parathyroid glands during unseen testing along with three additional non-parathyroid gland regions (90% positive predictive value). Subsequent time-fluorescence intensity profile extraction with vitality prediction was shown feasible in all cases within 5 min, with a 96.3% model accuracy (sensitivity and specificity were 93.3 and 100% respectively) when compared with expert judgement.

Conclusion

Automatic parathyroid gland perfusion quantification using simple machine learning computational methods discriminates parathyroid gland perfusion in concordance with expert surgeon interpretation, providing a means for near-infrared indocyanine green-parathyroid gland signal evaluation.
AAV-based TCAP delivery rescues mitochondria dislocation in limb-girdle muscular dystrophy R7
Authors: Lv Xiaoqing , Liu Shuangwu , Li Xi , Lv He , Shao Kai , Luo Sushan , Zhao Dandan , Yan Chuanzhu , Lin Pengfei
Published: October 2024

Limb-girdle muscular dystrophy R7 is a rare genetic disease caused by homozygous or compound heterozygous variants in the titin-cap (TCAP) gene that results in the absence of the protein telethonin. The primary pathological features of limb-girdle muscular dystrophy R7 are fibre size variation, nuclear centralization and abnormal mitochondrial distribution. The mechanisms underlying this disease are unclear and there is currently no specific treatment for limb-girdle muscular dystrophy R7.

This study established a Tcap-deficient mouse model to explore the disease mechanism of mitochondria dislocation and potential therapeutic strategies. We used methods such as proteomics, immunofluorescence, histopathological staining and western blotting to explore the mechanism of mitochondrial dislocation. Moreover, in the quest for a prospective therapeutic intervention for this disorder, the adeno-associated virus (AAV) serotype 2/9 was employed to deliver the Tcap gene into the muscles of these mice, facilitating preclinical experimentation. After 2 months and 7 months, the muscular phenotype was evaluated and selected mice were humanely euthanized for subsequent molecular and histological analysis.

The phenotype of Tcap−/− mice mimicked that observed in individuals diagnosed with limb-girdle muscular dystrophy R7. This study elucidated the mechanism of mitochondrial dislocation in limb-girdle muscular dystrophy R7. Through our in vitro experiments, we discovered that telethonin aids in preserving the integrity of desmin by preventing truncation at the N-terminus. Additionally, telethonin combined with desmin and co-localized at the Z-disc. Research has shown that the Tcap gene plays a crucial role in controlling the desmin cytoskeleton organization. The absence of telethonin leads to a collapsed desmin cytoskeleton. This causes disorganization of the mitochondrial network, leading to mitochondrial dysfunction. In addition, the study investigated the efficacy of AAV-mediated Tcap replacement in Tcap−/− mice. By intramuscular delivery of AAV, we observed dramatic improvements in muscle phenotype, muscle pathology, CK levels, muscle MRI, mitochondrial network organization and mitochondrial function.

The results of this study demonstrated that telethonin deficiency led to desmin cytoskeleton collapse that caused mitochondrial dislocation. AAV-mediated replacement therapy could be a promising safe and efficient treatment option for limb-girdle muscular dystrophy R7. The study highlights the potential of AAV-mediated replacement therapy for specific types of limb-girdle muscular dystrophy.