bluuebunny/crossref_metadata_2025_split huggingface dataset:
SUnSeT: spectral unmixing of hyperspectral images for phenotyping soybean seed traits
Authors: Jeong Seok Won , Lyu Jae Il , Jeong HwangWeon , Baek Jeongho , Moon Jung-Kyung , Lee Chaewon , Choi Myoung-Goo , Kim Kyoung-Hwan , Park Youn-Il 
Published: June 2024

Abstract

Key message

Hyperspectral features enable accurate classification of soybean seeds using linear discriminant analysis and GWAS for novel seed trait genes.

Abstract
Evaluating crop seed traits such as size, shape, and color is crucial for assessing seed quality and improving agricultural productivity. The introduction of the SUnSet toolbox, which employs hyperspectral sensor-derived image analysis, addresses this necessity. In a validation test involving 420 seed accessions from the Korean Soybean Core Collections, the pixel purity index algorithm identified seed- specific hyperspectral endmembers to facilitate segmentation. Various metrics extracted from ventral and lateral side images facilitated the categorization of seeds into three size groups and four shape groups. Additionally, quantitative RGB triplets representing seven seed coat colors, averaged reflectance spectra, and pigment indices were acquired. Machine learning models, trained on a dataset comprising 420 accession seeds and 199 predictors encompassing seed size, shape, and reflectance spectra, achieved accuracy rates of 95.8% for linear discriminant analysis model. Furthermore, a genome-wide association study utilizing hyperspectral features uncovered associations between seed traits and genes governing seed pigmentation and shapes. This comprehensive approach underscores the effectiveness of SUnSet in advancing precision agriculture through meticulous seed trait analysis.
Investigations, management and outcome of neonates presenting with distal intestinal obstruction: challenging the need for contrast enemas
Authors: Wells Hannah , Bough Georgina , Stedman Francesca , Ekerin Abiola Rachel , Hall Nigel J. 
Published: June 2024

Abstract
Purpose
To characterise the investigations, management and ultimate diagnosis of neonates with distal intestinal obstruction.

Methods
Retrospective review of term (> 37 weeks) neonates with admission diagnosis of distal intestinal obstruction over 10 years (2012–2022). Patient pathways were identified and associations between presentations, response to treatments and outcome investigated.

Results
A total of 124 neonates were identified and all included. Initial management was colonic irrigation in 108, contrast enema in 4, and laparotomy in 12. Of those responding to irrigations none underwent contrast enema. Ultimately, 22 neonates proceeded to laparotomy. Overall, 106 had a suction rectal biopsy and 41 had genetic testing for cystic fibrosis. Final diagnosis was Hirschsprung disease (HD) in 67, meconium ileus with cystic fibrosis (CF) in 9, meconium plug syndrome in 19 (including 3 with CF), intestinal atresia in 10 and no formal diagnosis in 17. Median length of neonatal unit stay was 11 days (7–19).

Conclusions
Initial management of neonates with distal bowel obstruction should be colonic irrigation since this is therapeutic in the majority and significantly reduces the need for contrast enema. These infants should all have suction rectal biopsy to investigate for HD unless another diagnosis is evident. If a meconium plug is passed, testing for CF is recommended. Evaluation and therapy are multimodal and time consuming, placing burden on resources and families.
Genome-wide DNA methylation status is a predictor of the efficacy of anti-EGFR antibodies in the second-line treatment of metastatic colorectal cancer: Translational research of the EPIC trial
Authors: Ouchi Kota , Takahashi Shin , Sasaki Keiju , Yoshida Yuya , Taniguchi Sakura , Kasahara Yuki , Komine Keigo , Imai Hiroo , Saijo Ken , Shirota Hidekazu , Takahashi Masanobu , Ishioka Chikashi 
Published: June 2024

Abstract
Purpose
The genome-wide DNA methylation status (GWMS) predicts of therapeutic response to anti-epidermal growth factor receptor (EGFR) antibodies in treating metastatic colorectal cancer. We verified the significance of GWMS as a predictive factor for the efficacy of anti-EGFR antibodies in the second-line treatment of metastatic colorectal cancer.

Methods
Clinical data were obtained from a prospective trial database, and a genome-wide DNA methylation analysis was performed. GWMS was classified into high-methylated colorectal cancer (HMCC) and low-methylated colorectal cancer (LMCC). The patients were divided into subgroups according to the treatment arm (cetuximab plus irinotecan or irinotecan alone) and GWMS, and the clinical outcomes were compared between the subgroups.

Results
Of the 112 patients, 58 (51.8%) were in the cetuximab plus irinotecan arm, and 54 (48.2%) were in the irinotecan arm; 47 (42.0%) were in the HMCC, and 65 (58.0%) were in the LMCC group regarding GWMS. Compared with the LMCC group, the progression-free survival (PFS) was significantly shortened in the HMCC group in the cetuximab plus irinotecan arm (median 1.4 vs. 4.1 months, p = 0.001, hazard ratio = 2.56), whereas no significant differences were observed in the irinotecan arm. A multivariate analysis showed that GWMS was an independent predictor of PFS and overall survival (OS) in the cetuximab plus irinotecan arm (p = 0.002, p = 0.005, respectively), whereas GWMS did not contribute to either PFS or OS in the irinotecan arm.

Conclusions
GWMS was a predictive factor for the efficacy of anti-EGFR antibodies in the second-line treatment of metastatic colorectal cancer.
Genotypes and phenotypes of motor neuron disease: an update of the genetic landscape in Scotland
Authors: Leighton Danielle J. , Ansari Morad , Newton Judith , Cleary Elaine , Stephenson Laura , Beswick Emily , Carod Artal Javier , Davenport Richard , Duncan Callum , Gorrie George H. , Morrison Ian , Swingler Robert , Deary Ian J. , Porteous Mary , Chandran Siddharthan , Pal Suvankar ,   the Lothian Birth Cohorts Group, the CARE-MND Consortium, Bethell Andrew , Byrne Susan , Connor Myles , Craig Gillian , Dolezal Ondrej , Flett Moira , Gardiner Louise , Gill Jessica , Chau Isaac , Hatrick Janice , Johnson Micheala , Lassak Katja , Larraz Juan , Lennox Helen , MacDonald Pauline , Marshall Laura , McAleer Dympna , McEleney Alison , Millar Kitty , Murrie Louise , Perry David , Saravanan Gowri , Simpson David , Stewart Susan , Storey Dorothy , Stott Gill , Thompson David , Thornton Carol , Webber Carolyn , Wong Michael , Harris Sarah , Prendergast James , Russ Tom , Taylor Adele , Deary Ian 
Published: June 2024

Abstract
Background
Using the Clinical Audit Research and Evaluation of Motor Neuron Disease (CARE-MND) database and the Scottish Regenerative Neurology Tissue Bank, we aimed to outline the genetic epidemiology and phenotypes of an incident cohort of people with MND (pwMND) to gain a realistic impression of the genetic landscape and genotype–phenotype associations.

Methods
Phenotypic markers were identified from the CARE-MND platform. Sequence analysis of 48 genes was undertaken. Variants were classified using a structured evidence-based approach. Samples were also tested for C9orf72 hexanucleotide expansions using repeat-prime PCR methodology.

Results
339 pwMND donated a DNA sample: 44 (13.0%) fulfilled criteria for having a pathogenic variant/repeat expansion, 53.5% of those with a family history of MND and 9.3% of those without. The majority (30 (8.8%)) had a pathogenic C9orf72 repeat expansion, including two with intermediate expansions. Having a C9orf72 expansion was associated with a significantly lower Edinburgh Cognitive and Behavioural ALS Screen ALS-Specific score (p = 0.0005). The known pathogenic SOD1 variant p.(Ile114Thr), frequently observed in the Scottish population, was detected in 9 (2.7%) of total cases but in 17.9% of familial cases. Rare variants were detected in FUS and NEK1. One individual carried both a C9orf72 expansion and SOD1 variant.

Conclusions
Our results provide an accurate summary of MND demographics and genetic epidemiology. We recommend early genetic testing of people with cognitive impairment to ensure that C9orf72 carriers are given the best opportunity for informed treatment planning. Scotland is enriched for the SOD1 p.(Ile114Thr) variant and this has significant implications with regards to future genetically-targeted treatments.
Short–term outcomes of heavyweight versus mediumweight synthetic mesh in a retrospective cohort of clean–contaminated and contaminated retromuscular ventral hernia repairs
Authors: Ellis Ryan C. , Maskal Sara M. , Messer Nir , Miller Benjamin T. , Petro Clayton C. , Prabhu Ajita S. , Rosen Michael J. , Zheng Xinyan , Beffa Lucas R. A. 
Published: June 2024

Abstract
Background
Mediumweight (40–60 g/m2) polypropylene (MWPP) mesh has been shown to be safe and effective in CDC class II–III retromuscular ventral hernia repairs (RMVHR). However, MWPP has the potential to fracture, and it is possible that heavyweight (> 75 g/m2) polypropylene mesh has similar outcomes in this context. However, there is limited data on HWPP mesh performance in clean-contaminated and contaminated scenarios. We aimed to compare HWPP to MWPP mesh in CDC class II–III wounds during open RMVHR.

Methods
The Abdominal Core Health Quality Collaborative database was retrospectively queried for a cohort of patients who underwent open RMVHR with MWPP or HWPP mesh placed in CDC class II/III wounds from 2012 to 2023. Mesh types were compared using a 3:1 propensity score-matched analysis. Covariates for matching included CDC classification, BMI, diabetes, smoking within 1 year, hernia, and mesh width. Primary outcome of interest included wound complications. Secondary outcomes included reoperations and readmissions at 30 days.

Results
A total of 1496 patients received MWPP or HWPP (1378 vs. 118, respectively) in contaminated RMVHR. After propensity score matching, 351 patients remained in the mediumweight and 117 in the heavyweight mesh group. There were no significant differences in surgical site infection (SSI) rates (13.4% vs. 14.5%, p = 0.877), including deep SSIs (0.3% vs. 0%, p = 1), surgical site occurrence rates (17.9% vs. 22.2%, p = 0.377), surgical site occurrence requiring procedural intervention (16% vs. 17.9%, p = 0.719), mesh removal (0.3% vs. 0%, p = 1), reoperations (4.6% vs. 2.6%, p = 0.428), or readmissions (12.3% vs. 9.4%, p = 0.504) at 30 days.

Conclusion
HWPP mesh was not associated with increased wound morbidity, mesh excisions, reoperations, or readmissions in the early postoperative period compared with MWPP mesh in open RMVHR for CDC II/III cases. Longer follow-up will be necessary to determine if HWPP mesh may be a suitable alternative to MWPP mesh in contaminated scenarios.
Deep learning model utilizing clinical data alone outperforms image-based model for hernia recurrence following abdominal wall reconstruction with long-term follow up
Authors: Wilson Hadley H. , Ma Chiyu , Ku Dau , Scarola Gregory T. , Augenstein Vedra A. , Colavita Paul D. , Heniford B. Todd 
Published: June 2024

Abstract
Background
Deep learning models (DLMs) using preoperative computed tomography (CT) imaging have shown promise in predicting outcomes following abdominal wall reconstruction (AWR), including component separation, wound complications, and pulmonary failure. This study aimed to apply these methods in predicting hernia recurrence and to evaluate if incorporating additional clinical data would improve the DLM’s predictive ability.

Methods
Patients were identified from a prospectively maintained single-institution database. Those who underwent AWR with available preoperative CTs were included, and those with < 18 months of follow up were excluded. Patients were separated into a training (80%) set and a testing (20%) set. A DLM was trained on the images only, and another DLM was trained on demographics only: age, sex, BMI, diabetes, and history of tobacco use. A mixed-value DLM incorporated data from both. The DLMs were evaluated by the area under the curve (AUC) in predicting recurrence.

Results
The models evaluated data from 190 AWR patients with a 14.7% recurrence rate after an average follow up of more than 7 years (mean ± SD: 86 ± 39 months; median [Q1, Q3]: 85.4 [56.1, 113.1]). Patients had a mean age of 57.5 ± 12.3 years and were majority (65.8%) female with a BMI of 34.2 ± 7.9 kg/m2. There were 28.9% with diabetes and 16.8% with a history of tobacco use. The AUCs for the imaging DLM, clinical DLM, and combined DLM were 0.500, 0.667, and 0.604, respectively.

Conclusions
The clinical-only DLM outperformed both the image-only DLM and the mixed-value DLM in predicting recurrence. While all three models were poorly predictive of recurrence, the clinical-only DLM was the most predictive. These findings may indicate that imaging characteristics are not as useful for predicting recurrence as they have been for other AWR outcomes. Further research should focus on understanding the imaging characteristics that are identified by these DLMs and expanding the demographic information incorporated in the clinical-only DLM to further enhance the predictive ability of this model.
Caries and white spot lesion trajectories of orthodontic patients across an observation period of 20 years
Authors: Ganss Carolina , Schulz-Weidner Nelly , Klaus Katharina , von Bremen Julia , Ruf Sabine , Bock Niko C. 
Published: June 2024

Abstract
Objectives
Fixed orthodontic appliances may increase the risk for caries and white spot lesions. The aim of this retrospective study was to determine the long-term associations between both in orthodontic patients.

Materials and methods
103 patients aged 36.6 ± 6.5 years whose fixed appliance orthodontic treatment had finished at least 15 years ago were included. Current clinical data and photographs (T3), panoramic x-ray and photographs from before treatment (T0), after debonding (T1) and at 2-year follow-up (T2) were available. Parameters of interest were dentine caries, “Missing/Filled Teeth” (MFT), “White Spot Lesion” (WSL) index and “Periodontal Screening and Recording” index (PSR; T3 only).

Results
At T0, 30.4% had no caries experience decreasing to 25.6%, 22.4% and 6.8% at T1, T2 and T3 resp. The median MFT (95% CI) at T0, T1, T2 and T3 was 2 (1;3), 3 (2;4), 3 (2;4) and 7 (6;9) resp. increasing significantly at each time point (p < 0.001 each); 30.1% had WSL at debonding. Patients with caries experience at T0 had a 2.4-fold increased risk of WSL at debonding. Dentine caries, caries experience and WSL at T1 were significantly associated with incident caries at T2, but not at T3. PSR at T3 had a significant association with previous caries incidence and WSL.

Conclusions
Caries experience prior to orthodontic treatment may constitute a risk indicator for WSL, and caries experience and WSL at its end for caries incidence in the near term.

Clinical Relevance
Present caries and WSL may help identifying orthodontic patients with special need for prevention and counselling.
Strong Simple Policies for POMDPs
Authors: Winterer Leonore , Wimmer Ralf , Becker Bernd , Jansen Nils 
Published: June 2024

AbstractThe synthesis problem for partially observable Markov decision processes (POMDPs) is to compute a policy that provably adheres to one or more specifications. Yet, the general problem is undecidable, and policies require full (and thus potentially unbounded) traces of execution history. To provide good approximations of such policies, POMDP agents often employ randomization over action choices. We consider the problem of computing simpler policies for POMDPs, and provide several approaches to still ensure their expressiveness. Key aspects are (1) the combination of an arbitrary number of specifications the policies need to adhere to, (2) a restricted form of randomization, and (3) a light-weight preprocessing of the POMDP model to encode memory. We provide a novel encoding as a mixed-integer linear program as baseline to solve the underlying problems. Our experiments demonstrate that the policies we obtain are more robust, smaller, and easier to implement for an engineer than those obtained from state-of-the-art POMDP solvers.
Few-shot learning for COVID-19 chest X-ray classification with imbalanced data: an inter vs. intra domain study
Authors: Galán-Cuenca Alejandro , Gallego Antonio Javier , Saval-Calvo Marcelo , Pertusa Antonio 
Published: June 2024

AbstractMedical image datasets are essential for training models used in computer-aided diagnosis, treatment planning, and medical research. However, some challenges are associated with these datasets, including variability in data distribution, data scarcity, and transfer learning issues when using models pre-trained from generic images. This work studies the effect of these challenges at the intra- and inter-domain level in few-shot learning scenarios with severe data imbalance. For this, we propose a methodology based on Siamese neural networks in which a series of techniques are integrated to mitigate the effects of data scarcity and distribution imbalance. Specifically, different initialization and data augmentation methods are analyzed, and four adaptations to Siamese networks of solutions to deal with imbalanced data are introduced, including data balancing and weighted loss, both separately and combined, and with a different balance of pairing ratios. Moreover, we also assess the inference process considering four classifiers, namely Histogram, kNN, SVM, and Random Forest. Evaluation is performed on three chest X-ray datasets with annotated cases of both positive and negative COVID-19 diagnoses. The accuracy of each technique proposed for the Siamese architecture is analyzed separately. The results are compared to those obtained using equivalent methods on a state-of-the-art CNN, achieving an average F1 improvement of up to 3.6%, and up to 5.6% of F1 for intra-domain cases. We conclude that the introduced techniques offer promising improvements over the baseline in almost all cases and that the technique selection may vary depending on the amount of data available and the level of imbalance.
Q methodology and the sociotechnical perspective
Authors: Frank Muriel , Kohn Vanessa , Holten Roland 
Published: June 2024

AbstractWhen studying information systems (IS) phenomena, scholars increasingly aim to take a socio-technical approach. This means that instead of focusing exclusively on the technical side, they also study them from a human perspective. An underrecognized yet powerful tool for examining the opinions and attitudes of individuals is the Q methodology because it makes subjective viewpoints on IS phenomena objectively measurable. Despite its benefits and wide application in other disciplines, the use of Q methodology in top IS journals is still rare. Based on a systematic literature review, this article explores the potential and fit of Q methodology within the sociotechnical systems framework. This analysis leads to two main insights. First, Q methodology enables the integration of the social and the technical component as well as instrumental and humanistic outcomes. Second, this qualiquantilogical technique enriches the understanding of IS phenomena by objectifying the approach to exploring subjective viewpoints. Thus, our work highlights the potential of the method for conducting IS research. And it also provides clear guidelines on how to use the method to uncover new patterns inherent in the data being studied.
Revealing agricultural land ownership concentration with cadastral and company network data
Authors: Jänicke Clemens , Müller Daniel 
Published: June 2024

Abstract
In many high-income countries, agricultural land is highly concentrated in a few hands, but detailed knowledge of ownership structures is limited. We examined land ownership structures and agricultural land concentration for the entire state of Brandenburg, Germany (1.3 million ha), using cadastral and company network data. Our aim was to characterise all landowners, analyse the degree of ownership concentration, and examine the role of the largest landowners in more detail. We found a high fragmentation of ownership among 185,000 different owners. Most of the land was owned by individuals not active in agriculture and only a third of the land was owned by farmers and other agricultural actors. Absentee ownership covered a quarter of the land. Ownership concentration was low to moderate in most regions and reached high levels in only a few areas. The largest owners were public institutions, private investors and nature protection institutions. Areas where public institutions owned a lot of land showed high concentrations, but also some areas where private landowners owned a lot of land. In summary, our analysis provides rare information on the concentration of agricultural land ownership in a large region. Such analysis facilitates better justification and design of policies that regulate agricultural land markets.
Ground-motion models for earthquakes occurring in the United Kingdom
Authors: Douglas John , Aldama-Bustos Guillermo , Tallett-Williams Sarah , Daví Manuela , Tromans Iain J. 
Published: June 2024

AbstractThis article presents models to predict median horizontal elastic response spectral accelerations for 5% damping from earthquakes with moment magnitudes ranging from 3.5 to 7.25 occurring in the United Kingdom. This model was derived using the hybrid stochastic-empirical method based on an existing ground-motion model for California and a stochastic model for the UK that was developed specifically for this purpose. The model is presented in two consistent formats, both for two distance metrics, with different target end-users. Firstly, we provide a complete logic tree with 162 branches, and associated weights, capturing epistemic uncertainties in the depth to the top of rupture, geometric spreading, anelastic path attenuation, site attenuation and stress drop, which is more likely to be used for research. The weights for these branches were derived using Bayesian updating of a priori weights from expert judgment. Secondly, we provide a backbone model with three and five branches corresponding to different percentiles, with corresponding weights, capturing the overall epistemic uncertainty, which is tailored for engineering applications. The derived models are compared with ground-motion observations, both instrumental and macroseismic, from the UK and surrounding region (northern France, Belgium, the Netherlands, western Germany and western Scandinavia). These comparisons show that the model is well-centred (low overall bias and no obvious trends with magnitude or distance) and that the branches capture the body and range of the technically defensible interpretations. In addition, comparisons with ground-motion models that have been previously used within seismic hazard assessments for the UK show that ground-motion predictions from the proposed model match those from previous models quite closely for most magnitudes and distances. The models are available as computer subroutines for ease of use.