bluuebunny/crossref_metadata_2025_split huggingface dataset:
AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors
Authors: Fernández-Díaz Raúl , Cossio-Pérez Rodrigo , Agoni Clement , Lam Hoang Thanh , Lopez Vanessa , Shields Denis C 
Published: September 2024

Abstract

Motivation
Automated machine learning (AutoML) solutions can bridge the gap between new computational advances and their real-world applications by enabling experimental scientists to build their own custom models. We examine different steps in the development life-cycle of peptide bioactivity binary predictors and identify key steps where automation cannot only result in a more accessible method, but also more robust and interpretable evaluation leading to more trustworthy models.

Results
We present a new automated method for drawing negative peptides that achieves better balance between specificity and generalization than current alternatives. We study the effect of homology-based partitioning for generating the training and testing data subsets and demonstrate that model performance is overestimated when no such homology correction is used, which indicates that prior studies may have overestimated their performance when applied to new peptide sequences. We also conduct a systematic analysis of different protein language models as peptide representation methods and find that they can serve as better descriptors than a naive alternative, but that there is no significant difference across models with different sizes or algorithms. Finally, we demonstrate that an ensemble of optimized traditional machine learning algorithms can compete with more complex neural network models, while being more computationally efficient. We integrate these findings into AutoPeptideML, an easy-to-use AutoML tool to allow researchers without a computational background to build new predictive models for peptide bioactivity in a matter of minutes.

Availability and implementation
Source code, documentation, and data are available at https://github.com/IBM/AutoPeptideML and a dedicated web-server at http://peptide.ucd.ie/AutoPeptideML. A static version of the software to ensure the reproduction of the results is available at https://zenodo.org/records/13363975.
Dynamic category-sensitive hypergraph inferring and homo-heterogeneous neighbor feature learning for drug-related microbe prediction
Authors: Xuan Ping , Xu Zelong , Cui Hui , Gu Jing , Liu Cheng , Zhang Tiangang , Wu Peiliang 
Published: September 2024

Abstract

Motivation
The microbes in human body play a crucial role in influencing the functions of drugs, as they can regulate the activities and toxicities of drugs. Most recent methods for predicting drug–microbe associations are based on graph learning. However, the relationships among multiple drugs and microbes are complex, diverse, and heterogeneous. Existing methods often fail to fully model the relationships. In addition, the attributes of drug–microbe pairs exhibit long-distance spatial correlations, which previous methods have not integrated effectively.

Results
We propose a new prediction method named DHDMP which is designed to encode the relationships among multiple drugs and microbes and integrate the attributes of various neighbor nodes along with the pairwise long-distance correlations. First, we construct a hypergraph with dynamic topology, where each hyperedge represents a specific relationship among multiple drug nodes and microbe nodes. Considering the heterogeneity of node attributes across different categories, we developed a node category-sensitive hypergraph convolution network to encode these diverse relationships. Second, we construct homogeneous graphs for drugs and microbes respectively, as well as drug–microbe heterogeneous graph, facilitating the integration of features from both homogeneous and heterogeneous neighbors of each target node. Third, we introduce a graph convolutional network with cross-graph feature propagation ability to transfer node features from homogeneous to heterogeneous graphs for enhanced neighbor feature representation learning. The propagation strategy aids in the deep fusion of features from both types of neighbors. Finally, we design spatial cross-attention to encode the attributes of drug–microbe pairs, revealing long-distance correlations among multiple pairwise attribute patches. The comprehensive comparison experiments showed our method outperformed state-of-the-art methods for drug–microbe association prediction. The ablation studies demonstrated the effectiveness of node category-sensitive hypergraph convolution network, graph convolutional network with cross-graph feature propagation, and spatial cross-attention. Case studies on three drugs further showed DHDMP’s potential application in discovering the reliable candidate microbes for the interested drugs.

Availability and implementation
Source codes and supplementary materials are available at https://github.com/pingxuan-hlju/DHDMP.
Structure-inclusive similarity based directed GNN: a method that can control information flow to predict drug–target binding affinity
Authors: Huang Jipeng , Sun Chang , Li Minglei , Tang Rong , Xie Bin , Wang Shuqin , Wei Jin-Mao 
Published: September 2024

Abstract

Motivation
Exploring the association between drugs and targets is essential for drug discovery and repurposing. Comparing with the traditional methods that regard the exploration as a binary classification task, predicting the drug–target binding affinity can provide more specific information. Many studies work based on the assumption that similar drugs may interact with the same target. These methods constructed a symmetric graph according to the undirected drug similarity or target similarity. Although these similarities can measure the difference between two molecules, it is unable to analyze the inclusion relationship of their substructure. For example, if drug A contains all the substructures of drug B, then in the message-passing mechanism of the graph neural network, drug A should acquire all the properties of drug B, while drug B should only obtain some of the properties of A.

Results
To this end, we proposed a structure-inclusive similarity (SIS) which measures the similarity of two drugs by considering the inclusion relationship of their substructures. Based on SIS, we constructed a drug graph and a target graph, respectively, and predicted the binding affinities between drugs and targets by a graph convolutional network-based model. Experimental results show that considering the inclusion relationship of the substructure of two molecules can effectively improve the accuracy of the prediction model. The performance of our SIS-based prediction method outperforms several state-of-the-art methods for drug–target binding affinity prediction. The case studies demonstrate that our model is a practical tool to predict the binding affinity between drugs and targets.

Availability and implementation
Source codes and data are available at https://github.com/HuangStomach/SISDTA.
Are cows pickier than goats? Linnaeus’s innovative large-scale feeding experiment
Authors: Carlsson Bengt Å , Björkman Camilla , Rydin Håkan 
Published: September 2024

Abstract
In 1749, Linnaeus published Pan Svecicus, a thesis that was defended by his student Nils Hesselgren. The thesis describes food preference trials in cows, goats, sheep, horses, and pigs, and includes 2325 tests with 643 plant species. The data had surprisingly little bearing on the text in the thesis, and even though the experiments quickly became internationally known, the data were merely repeated, rather than discussed. We have digitized the data and linked the species names to modern nomenclature and present the first analysis and discussion of the results. Pigs were most selective (eating 32% of the 204 plant species that were tested on all animals), followed by horses (59%), cows (66%), sheep (82%), and goats (85%). The ruminants (especially goats and sheep) had high overlap in food choice, and the pigs deviated most (despite the fact that pigs are more closely related to the ruminants than are horses). Among plant orders, Fabales and Poales were generally preferred, while Lamiales and Ranunculales were avoided, especially by cows and horses. Cows and horses were also more keen to avoid toxic plant species. All animals showed a preference for species that are today considered nutritious. We now make the data available, for further analyses in ecology, history of science, and other disciplines.
Apolipoprotein B-48 and late graft failure in kidney transplant recipients
Authors: Szili-Torok Tamas , de Borst Martin H , Soteriou Alexandra , Post Laura , Bakker Stephan J L , Tietge Uwe J F 
Published: September 2024

ABSTRACT

Introduction
Transplant vasculopathy resembles atherosclerotic plaque formation and is a major contributor to late graft failure in kidney transplant recipients (KTR). Remnant lipoproteins and associated triglycerides are causal risk factors for atherosclerotic plaques and have been implicated in late kidney graft failure. However, whether remnants derived from liver (containing apolipoprotein [apo] B100) or intestine (containing apoB48) are clinically more important is unclear. The current study investigated the association between baseline fasting apoB48 levels and late kidney graft failure.

Methods
481 KTR with a functioning graft for at least 1 year were included in this retrospective, observational longitudinal single center cohort study. The primary endpoint was death-censored late graft failure, defined as need for initiation of dialysis or re-transplantation. ApoB48 was measured by enzyme-linked immunosorbent assay.

Results
During a median follow-up of 9.5 years, 61 KTR developed graft failure (12.7%). At baseline, KTR with higher apoB48 levels had lower eGFR (P &lt; .001), lower high-density lipoprotein (HDL) cholesterol (P &lt; .001), increased triglycerides (P &lt; .001) and used cyclosporine more frequently (P = .003). Cox regression showed that higher baseline apoB48 was associated with higher risk of late graft failure [hazard ratio (95% confidence interval), 1.59 (1.22, 2.07), P &lt; .001], independent of stepwise adjustment for potential confounders, including age and sex, immunosuppression type and proteinuria, triglycerides, and waist circumference (fully adjusted HR, 1.78 (1.29, 2.47), P &lt; .001].

Conclusion
ApoB48 is strongly associated with late graft failure, independent of potential confounders. Since apoB48-containing lipoproteins originate from the intestine, this study provides a rationale for considering pharmacological interventions targeting lipid absorption to improve graft outcome.
Cardiac anatomic digital twins: findings from a single national centre
Authors: Lippert Matthias , Dumont Karl-Andreas , Birkeland Sigurd , Nainamalai Varatharajan , Solvin Håvard , Suther Kathrine Rydén , Bendz Bjørn , Elle Ole Jakob , Brun Henrik 
Published: September 2024

Abstract

Aims
New three-dimensional cardiac visualization technologies are increasingly employed for anatomic digital twins in pre-operative planning. However, the role and influence of extended reality (virtual, augmented, or mixed) within heart team settings remain unclear. We aimed to assess the impact of mixed reality visualization of the intracardiac anatomy on surgical decision-making in patients with complex heart defects.

Methods and results
Between September 2020 and December 2022, we recruited 50 patients and generated anatomic digital twins and visualized them in mixed reality. These anatomic digital twins were presented to the heart team after initial decisions were made using standard visualization methods. Changes in the surgical strategy were recorded. Additionally, heart team members rated their mixed reality experience through a questionnaire, and post-operative outcomes were registered. Anatomic digital twins changed the initially decided upon surgical strategies for 68% of cases. While artificial intelligence facilitated the rapid creation of digital anatomic twins, manual corrections were always necessary.

Conclusion
In conclusion, mixed reality anatomic digital twins added information to standard visualization methods and significantly influenced surgical planning, with evidence that these strategies can be implemented safely without additional risk.
A new perspective on tumor progression
Authors: Thomas Frédéric , DeGregori James , Marusyk Andriy , Dujon Antoine M , Ujvari Beata , Capp Jean-Pascal , Gatenby Robert , Nedelcu Aurora M 
Published: September 2024

ABSTRACT
Tumorigenesis is commonly attributed to Darwinian processes involving natural selection among cells and groups of cells. However, progressing tumors are those that also achieve an appropriate group phenotypic composition (GPC). Yet, the selective processes acting on tumor GPCs are distinct from that associated with classical Darwinian evolution (i.e. natural selection based on differential reproductive success) as tumors are not genuine evolutionary individuals and do not exhibit heritable variation in fitness. This complex evolutionary scenario is analogous to the recently proposed concept of ‘selection for function’ invoked for the evolution of both living and non-living systems. Therefore, we argue that it is inaccurate to assert that Darwinian processes alone account for all the aspects characterizing tumorigenesis and cancer progression; rather, by producing the genetic and phenotypic diversity required for creating novel GPCs, these processes fuel the evolutionary success of tumors that is dependent on selection for function at the tumor level.
Adaptive small-scale fisheries in the eastern Cantabrian coast through reliance on essential species
Authors: Bachiller Eneko , Mugerza Estanis , Murillas-Maza Arantza , Mateo Maria , Korta Maria , Zarauz Lucia 
Published: September 2024

Abstract
In recent decades, small-scale fisheries (SSF) activity along the Basque coast (eastern Cantabrian) has declined, which has led remaining vessels to undergo notable shifts in their targeted species and therefore the fishing gears used, aimed at enhancing efficiency. Within that context, this study combines logbooks and sales notes spanning from 1995 to 2022 to assess inter-annual and seasonal variations in fishing activity and the main target species across different fishing gears, namely ‘fleet segments’. Results reveal that the spring Atlantic mackerel (Scomber scombrus) and summer albacore (Thunnus alalunga) seasons, with an intensified harvesting under favourable conditions during the past decade, affected the activity of all other segments throughout the year. In the face of climate change affecting harvested species, a scenario where mackerel and/or albacore seasons are disturbed would lead the SSF to predominantly depend on European hake, mainly caught by declining longlines and set nets, as well as on complementary species. Assessing essential species targeted by each SSF segment relies on is crucial for stakeholders as it helps manage interactions between fleets targeting the same species (e.g. SSF vs. industrial and recreational fisheries), and understand gear shifts by vessels targeting specific species in certain seasons.
HiMAL: Multimodal

Hi

erarchical

M

ulti-task

A

uxiliary

L

earning framework for predicting Alzheimer’s disease progression
Authors: Kumar Sayantan , Yu Sean C , Michelson Andrew , Kannampallil Thomas , Payne Philip R O 
Published: September 2024

Abstract

Objective
We aimed to develop and validate a novel multimodal framework Hierarchical Multi-task Auxiliary Learning (HiMAL) framework, for predicting cognitive composite functions as auxiliary tasks that estimate the longitudinal risk of transition from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD).

Materials and Methods
HiMAL utilized multimodal longitudinal visit data including imaging features, cognitive assessment scores, and clinical variables from MCI patients in the Alzheimer’s Disease Neuroimaging Initiative dataset, to predict at each visit if an MCI patient will progress to AD within the next 6 months. Performance of HiMAL was compared with state-of-the-art single-task and multitask baselines using area under the receiver operator curve (AUROC) and precision recall curve (AUPRC) metrics. An ablation study was performed to assess the impact of each input modality on model performance. Additionally, longitudinal explanations regarding risk of disease progression were provided to interpret the predicted cognitive decline.

Results
Out of 634 MCI patients (mean [IQR] age: 72.8 [67-78], 60% male), 209 (32%) progressed to AD. HiMAL showed better prediction performance compared to all state-of-the-art longitudinal single-modality singe-task baselines (AUROC = 0.923 [0.915-0.937]; AUPRC = 0.623 [0.605-0.644]; all P &lt; .05). Ablation analysis highlighted that imaging and cognition scores with maximum contribution towards prediction of disease progression.

Discussion
Clinically informative model explanations anticipate cognitive decline 6 months in advance, aiding clinicians in future disease progression assessment. HiMAL relies on routinely collected electronic health records (EHR) variables for proximal (6 months) prediction of AD onset, indicating its translational potential for point-of-care monitoring and managing of high-risk patients.
Management of Acute Hand Burns: A Survey of American Burn Association-Verified Burn Centers
Authors: Liu Hilary Y , Alessandri-Bonetti Mario , Shockey Siddhi , Corcos Alain C , Ziembicki Jenny A , Stofman Guy M , Egro Francesco M 
Published: September 2024

Abstract
Hand burns have a significant impact on the long-term function of burn patients. Recently, new protocols and technologies, such as dermal substitutes, have been introduced for the treatment of hand burns. This cross-sectional study investigates the preferred current management of acute hand burns and the role of dermal substitutes in treatment. A 10-question survey related to acute hand burns management was sent to 64 directors of American Burn Association (ABA)-verified burn centers. A total of 51.6% (n = 33) directors of ABA-verified burn centers responded to the survey. For the treatment of superficial partial-thickness hand burns, 90.9% preferred a nonoperative approach. Conversely, most respondents chose a single-stage excision and skin graft for deep partial-thickness hand burns (75.8%) and full-thickness hand burns (51.5%). However, for full-thickness hand burns, some surgeons prefer a 2-stage reconstruction involving excision and placement of a skin substitute (27.3%) or allograft (9.1%), followed by a skin graft. Only 6.1% would utilize a 3-stage reconstruction involving excision and allograft, excision and skin substitute, followed by skin grafting. Among surgeons who used skin substitutes (n = 26), Integra (42.3%) and Novosorb-Biodegradable Temporizing Matrix (23.1%) were preferred. The top reasons for choosing 1 specific dermal substitute were surgeon’s preference (n = 20; 76.9%) and cost (n = 9; 34.6%). While a conservative nonoperative approach is preferred for superficial partial-thickness hand burns, excision and skin grafting as a 1-stage procedure remains the most common strategy for deep partial-thickness and full-thickness hand burns.
Developing Music Therapy in Maternity Care in Ireland: A Qualitative Study
Authors: Cheung Pui Sze , McCaffrey Triona , Tighe Sylvia Murphy , Lowther Timothy , Mohamad Mas Mahady 
Published: September 2024

Abstract
Music therapy can be a form of preventive or early intervention. It strengthens and utilizes women’s own resources to build resilience, aids relaxation, reduces symptoms of anxiety and depression, promotes parent–infant attachment, and adapts to physical and psychological challenges during the perinatal period. The inclusion of music therapy in Irish maternity services has the potential to improve the quality of healthcare delivery provided to parents and infants. Recent studies demonstrate that the prospect of music therapy is welcomed by parents and perinatal healthcare professionals in Ireland, but such services are yet to be formally embedded in maternity care. Building on a cross-sectional survey, this qualitative study employed 6 semi-structured interviews with women and perinatal healthcare professionals in Ireland to understand their perspectives on developing music therapy in Irish maternity care services. Four themes were identified from the thematic analysis of these interviews: (1) music has multiple functions during the perinatal period; (2) music programs contribute to holistic perspectives and approachability in perinatal care; (3) music therapy provides specialist support; and (4) further development of music therapy services is challenging. The findings offer important insights and practical considerations on the key components of the music therapy programs and strategies in developing music therapy in Irish maternity settings. This information can directly inform music therapy researchers and practitioners in designing music therapy programs and developing relevant services in collaboration with maternity care professionals and policymakers.
Retained bullets: to remove or not to remove? Lessons from two clinical scenarios with intracardiac bullet embolization
Authors: Hinton Jared B , Landwehr Hunter J , Loudon Andrew M , Moorman Matthew L 
Published: September 2024

Abstract
Firearm-related injuries in the USA are increasing, with over 105,000 cases annually. Gunshot wounds (GSWs), especially those involving retained bullets, present complex challenges due to bullet trajectories and embolization risks. This study reviews two cases of bullet emboli, focusing on bullet localization strategies and timing of removal. Imaging techniques such as chest X-ray, CT scan, intraoperative fluoroscopy, and transesophageal echocardiogram were employed for localization. In Case 1, a stable patient with a left-back GSW had a bullet embolism from the inferior vena cava to the right ventricle, necessitating prompt removal. In Case 2, an unstable patient with thoracoabdominal GSWs experienced a delayed embolism to the aortic root, requiring multiple surgeries. Effective management of retained bullets involves diverse imaging and timely surgical intervention, especially for stable patients, emphasizing individualized and proactive strategies to enhance outcomes in bullet embolization cases.