bluuebunny/crossref_metadata_2025_split huggingface dataset:
Harbinger transposon insertion in ethylene signaling gene leads to emergence of new sexual forms in cucurbits
Authors: Huang Hsin-Ya , Zhang Siqi , Choucha Fadi Abou , Verdenaud Marion , Tan Feng-Quan , Pichot Clement , Parsa Hadi Shirazi , Slavkovic Filip , Chen Qinghe , Troadec Christelle , Marcel Fabien , Dogimont Catherine , Quadrana Leandro , Boualem Adnane , Bendahmane Abdelhafid 
Published: June 2024

AbstractIn flowering plants, the predominant sexual morph is hermaphroditism, and the emergence of unisexuality is poorly understood. Using Cucumis melo (melon) as a model system, we explore the mechanisms driving sexual forms. We identify a spontaneous mutant exhibiting a transition from bisexual to unisexual male flower, and identify the causal mutation as a Harbinger transposon impairing the expression of Ethylene Insensitive 2 (CmEIN2) gene. Genetics and transcriptomic analysis reveal a dual role of CmEIN2 in both sex determination and fruit shape formation. Upon expression of CmACS11, EIN2 is recruited to repress the expression of the carpel inhibitor, CmWIP1. Subsequently, EIN2 is recruited to mediate stamina inhibition. Following the sex determination phase, EIN2 promotes fruit shape elongation. Genome-wide analysis reveals that Harbinger transposon mobilization is triggered by environmental cues, and integrates preferentially in active chromatin, particularly within promoter regions. Characterization of a large collection of melon germplasm points to active transpositions in the wild, compared to cultivated accessions. Our study underscores the association between chromatin dynamics and the temporal aspects of mobile genetic element insertions, providing valuable insights into plant adaptation and crop genome evolution.
Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression
Authors: Hao Ruo-Han , Zhang Tian-Pei , Jiang Feng , Liu Jun-Hui , Dong Shan-Shan , Li Meng , Guo Yan , Yang Tie-Lin 
Published: June 2024

AbstractThe human brain has been implicated in the pathogenesis of several complex diseases. Taking advantage of single-cell techniques, genome-wide association studies (GWAS) have taken it a step further and revealed brain cell-type-specific functions for disease loci. However, genetic causal associations inferred by Mendelian randomization (MR) studies usually include all instrumental variables from GWAS, which hampers the understanding of cell-specific causality. Here, we developed an analytical framework, Cell-Stratified MR (csMR), to investigate cell-stratified causality through colocalizing GWAS signals with single-cell eQTL from different brain cells. By applying to obesity-related traits, our results demonstrate the cell-type-specific effects of GWAS variants on gene expression, and indicate the benefits of csMR to identify cell-type-specific causal effect that is often hidden from bulk analyses. We also found csMR valuable to reveal distinct causal pathways between different obesity indicators. These findings suggest the value of our approach to prioritize target cells for extending genetic causation studies.
MSGene: a multistate model using genetic risk and the electronic health record applied to lifetime risk of coronary artery disease
Authors: Urbut Sarah M. , Yeung Ming Wai , Khurshid Shaan , Cho So Mi Jemma , Schuermans Art , German Jakob , Taraszka Kodi , Paruchuri Kaavya , Fahed Akl C. , Ellinor Patrick T. , Trinquart Ludovic , Parmigiani Giovanni , Gusev Alexander , Natarajan Pradeep 
Published: June 2024

AbstractCoronary artery disease (CAD) is the leading cause of death among adults worldwide. Accurate risk stratification can support optimal lifetime prevention. Current methods lack the ability to incorporate new information throughout the life course or to combine innate genetic risk factors with acquired lifetime risk. We designed a general multistate model (MSGene) to estimate age-specific transitions across 10 cardiometabolic states, dependent on clinical covariates and a CAD polygenic risk score. This model is designed to handle longitudinal data over the lifetime to address this unmet need and support clinical decision-making. We analyze longitudinal data from 480,638 UK Biobank participants and compared predicted lifetime risk with the 30-year Framingham risk score. MSGene improves discrimination (C-index 0.71 vs 0.66), age of high-risk detection (C-index 0.73 vs 0.52), and overall prediction (RMSE 1.1% vs 10.9%), in held-out data. We also use MSGene to refine estimates of lifetime absolute risk reduction from statin initiation. Our findings underscore our multistate model’s potential public health value for accurate lifetime CAD risk estimation using clinical factors and increasingly available genetics toward earlier more effective prevention.
Valine aminoacyl-tRNA synthetase promotes therapy resistance in melanoma
Authors: El-Hachem Najla , Leclercq Marine , Susaeta Ruiz Miguel , Vanleyssem Raphael , Shostak Kateryna , Körner Pierre-René , Capron Coralie , Martin-Morales Lorena , Roncarati Patrick , Lavergne Arnaud , Blomme Arnaud , Turchetto Silvia , Goffin Eric , Thandapani Palaniraja , Tarassov Ivan , Nguyen Laurent , Pirotte Bernard , Chariot Alain , Marine Jean-Christophe , Herfs Michael , Rapino Francesca , Agami Reuven , Close Pierre 
Published: June 2024

AbstractTransfer RNA dynamics contribute to cancer development through regulation of codon-specific messenger RNA translation. Specific aminoacyl-tRNA synthetases can either promote or suppress tumourigenesis. Here we show that valine aminoacyl-tRNA synthetase (VARS) is a key player in the codon-biased translation reprogramming induced by resistance to targeted (MAPK) therapy in melanoma. The proteome rewiring in patient-derived MAPK therapy-resistant melanoma is biased towards the usage of valine and coincides with the upregulation of valine cognate tRNAs and of VARS expression and activity. Strikingly, VARS knockdown re-sensitizes MAPK-therapy-resistant patient-derived melanoma in vitro and in vivo. Mechanistically, VARS regulates the messenger RNA translation of valine-enriched transcripts, among which hydroxyacyl-CoA dehydrogenase mRNA encodes for a key enzyme in fatty acid oxidation. Resistant melanoma cultures rely on fatty acid oxidation and hydroxyacyl-CoA dehydrogenase for their survival upon MAPK treatment. Together, our data demonstrate that VARS may represent an attractive therapeutic target for the treatment of therapy-resistant melanoma.
Reducing sectoral hard-to-abate emissions to limit reliance on carbon dioxide removal
Authors: Edelenbosch Oreane Y. , Hof Andries F. , van den Berg Maarten , de Boer Harmen Sytze , Chen Hsing-Hsuan , Daioglou Vassilis , Dekker Mark M. , Doelman Jonathan C. , den Elzen Michel G. J. , Harmsen Mathijs , Mikropoulos Stratos , van Sluisveld Mariësse A. E. , Stehfest Elke , Tagomori Isabela S. , van Zeist Willem-Jan , van Vuuren Detlef P. 
Published: June 2024

AbstractTo reach net-zero greenhouse gas targets, carbon dioxide removal (CDR) technologies are required to compensate for residual emissions in the hard-to-abate sectors. However, dependencies on CDR technologies involve environmental, technical and social risks, particularly related to increased land requirements for afforestation and bioenergy crops. Here, using scenarios consistent with the 1.5 °C target, we show that demand and technological interventions can substantially lower emission levels in four hard-to-abate sectors (industry, agriculture, buildings and transport) and reduce reliance on the use of bioenergy with carbon capture and storage. Specifically, demand measures and technology-oriented measures could limit peak annual bioenergy with carbon capture and storage use to 0.5–2.2 GtCO2e per year and 1.9–7.0 GtCO2e per year, respectively, compared with 10.3 GtCO2e per year in the default 1.5 °C scenario. Dietary change plays a critical role in the demand measures given its large share in residual agricultural emissions.
Probing the opto-electronic, phonon spectrum, and thermoelectric properties of lead-free fluoride perovskites A2GeSnF6 (A = K, Rb, Cs) for energy harvesting devices
Authors: Abdullah Danish , Gupta Dinesh C. 
Published: June 2024

AbstractThe present work employs density functional theory to explore the structural, optoelectronic, and thermoelectric attributes of the halide-based double perovskite A2GeSnF6 (A = K, Rb, and Cs) compounds. The stable phonon dispersion spectrum affirms dynamical stability, whereas the enthalpy of formation and tolerance factor evaluated collectively verify structural stability. Considering the Tran Blaha modified Becke Johnson potentials (mBJ), the predicted direct band gaps along the symmetry point are 3.19 eV for K2GeSnF6, 3.16 eV for Rb2GeSnF6 and 3.12 eV Cs2GeSnF6. According to an in-depth examination of the optoelectronic features, A2GeSnF6 (A = K, Rb, and Cs), double perovskites are assuring contenders for optoelectronic devices due to their suitable bandgap. The extremely high figure of merit values (0.94–0.97) obtained from the numerical calculation of power factor and thermal conductivity suggest the intriguing prospects of these compositions for thermoelectric devices. These studies offer a perceptive comprehension of the materials for their potential applications in the future.
Changes in protein fluxes in skeletal muscle during sequential stages of muscle regeneration after acute injury in male mice
Authors: Bizieff Alec , Cheng Maggie , Chang Kelvin , Mohammed Hussein , Ziari Naveed , Nyangau Edna , Fitch Mark , Hellerstein Marc K. 
Published: June 2024

AbstractChanges in protein turnover play an important role in dynamic physiological processes, including skeletal muscle regeneration, which occurs as an essential part of tissue repair after injury. The inability of muscle tissue to recapitulate this regenerative process can lead to the manifestation of clinical symptoms in various musculoskeletal diseases, including muscular dystrophies and pathological atrophy. Here, we employed a workflow that couples deuterated water (2H2O) administration with mass spectrometry (MS) to systematically measure in-vivo protein turnover rates across the muscle proteome in 8-week-old male C57BL6/J mice. We compared the turnover kinetics of over 100 proteins in response to cardiotoxin (CTX) induced muscle damage and regeneration at unique sequential stages along the regeneration timeline. This analysis is compared to gene expression data from mRNA-sequencing (mRNA-seq) from the same tissue. The data reveals quantitative protein flux signatures in response to necrotic damage, in addition to sequential differences in cell proliferation, energy metabolism, and contractile gene expression. Interestingly, the mRNA changes correlated poorly with changes in protein synthesis rates, consistent with post-transcriptional control mechanisms. In summary, the experiments described here reveal the signatures and timing of protein flux changes during skeletal muscle regeneration, as well as the inability of mRNA expression measurements to reveal changes in directly measured protein turnover rates. The results of this work described here provide a better understanding of the muscle regeneration process and could help to identify potential biomarkers or therapeutic targets.
Exact solutions for the Cahn–Hilliard equation in terms of Weierstrass-elliptic and Jacobi-elliptic functions
Authors: Hussain Akhtar , Ibrahim Tarek F. , Birkea F. M. Osman , Alotaibi Abeer M. , Al-Sinan Bushra R. , Mukalazi Herbert 
Published: June 2024

AbstractDespite the historical position of the F-expansion method as a method for acquiring exact solutions to nonlinear partial differential equations (PDEs), this study highlights its superiority over alternative auxiliary equation methods. The efficacy of this method is demonstrated through its application to solve the convective–diffusive Cahn–Hilliard (cdCH) equation, describing the dynamic of the separation phase for ternary iron alloys (Fe–Cr–Mo) and (Fe–X–Cu). Significantly, this research introduces an extensive collection of exact solutions by the auxiliary equation, comprising fifty-two distinct types. Six of these are associated with Weierstrass-elliptic function solutions, while the remaining solutions are expressed in Jacobi-elliptic functions. I think it is important to emphasize that, exercising caution regarding the statement of the term ’new,’ the solutions presented in this context are not entirely unprecedented. The paper examines numerous examples to substantiate this perspective. Furthermore, the study broadens its scope to include soliton-like and trigonometric-function solutions as special cases. This underscores that the antecedently obtained outcomes through the recently specific cases encompassed within the more comprehensive scope of the present findings.
Investigation and characterization of changes in potato peels by thermochemical acidic pre-treatment for extraction of various compounds
Authors: Mushtaq Qudsia , Ishtiaq Uzair , Joly Nicolas , Martin Patrick , Qazi JavedIqbal 
Published: June 2024

AbstractPotato peel waste (PPW) is an underutilized substrate which is produced in huge amounts by food processing industries. Using PPW a feedstock for production of useful compounds can overcome the problem of waste management as well as cost-effective. In present study, potential of PPW was investigated using chemical and thermochemical treatment processes. Three independent variables i.e., PPW concentration, dilute sulphuric acid concentration and liberation time were selected to optimize the production of fermentable sugars (TS and RS) and phenolic compounds (TP). These three process variables were selected in the range of 5–15 g w/v substrate, 0.8–1.2 v/v acid conc. and 4–6 h. Whole treatment process was optimized by using box-behnken design (BBD) of response surface methodology (RSM). Highest yield of total and reducing sugars and total phenolic compounds obtained after chemical treatment was 188.00, 144.42 and 43.68 mg/gds, respectively. The maximum yield of fermentable sugars attained by acid plus steam treatment were 720.00 and 660.62 mg/gds of TS and RS, respectively w.r.t 5% substrate conc. in 0.8% acid with residence time of 6 h. Results recorded that acid assisted autoclaved treatment could be an effective process for PPW deconstruction. Characterization of substrate before and after treatment was checked by SEM and FTIR. Spectras and micrographs confirmed the topographical variations in treated substrate. The present study was aimed to utilize biowaste and to determine cost-effective conditions for degradation of PWW into value added compounds.
Glucose-fed microbiota alters C. elegans intestinal epithelium and increases susceptibility to multiple bacterial pathogens
Authors: Kingsley Samuel F. , Seo Yonghak , Wood Alicia , Wani Khursheed A. , Gonzalez Xavier , Irazoqui Javier , Finkel Steven E. , Tissenbaum Heidi A. 
Published: June 2024

AbstractOverconsumption of dietary sugar can lead to many negative health effects including the development of Type 2 diabetes, metabolic syndrome, cardiovascular disease, and neurodegenerative disorders. Recently, the human intestinal microbiota, strongly associated with our overall health, has also been known to be affected by diet. However, mechanistic insight into the importance of the human intestinal microbiota and the effects of chronic sugar ingestion has not been possible largely due to the complexity of the human microbiome which contains hundreds of types of organisms. Here, we use an interspecies C. elegans/E. coli system, where E. coli are subjected to high sugar, then consumed by the bacterivore host C. elegans to become the microbiota. This glucose-fed microbiota results in a significant lifespan reduction accompanied by reduced healthspan (locomotion), reduced stress resistance, and changes in behavior and feeding. Lifespan reduction is also accompanied by two potential major contributors: increased intestinal bacterial density and increased concentration of reactive oxygen species. The glucose-fed microbiota accelerated the age-related development of intestinal cell permeability, intestinal distention, and dysregulation of immune effectors. Ultimately, the changes in the intestinal epithelium due to aging with the glucose-fed microbiota results in increased susceptibility to multiple bacterial pathogens. Taken together, our data reveal that chronic ingestion of sugar, such as a Western diet, has profound health effects on the host due to changes in the microbiota and may contribute to the current increased incidence of ailments including inflammatory bowel diseases as well as multiple age-related diseases.
Increased alcohol intake is associated with radiographic severity of knee and hand osteoarthritis in men
Authors: Xu Haimuzi , Kang Ji-Hyoun , Choi Sung-Eun , Park Dong-Jin , Kweon Sun-Seog , Lee Young-Hoon , Kim Hye-Yeon , Lee Jung-Kil , Shin Min-Ho , Lee Shin-Seok 
Published: June 2024

AbstractObservational studies have shown controversial associations between alcohol intake and radiographic osteoarthritis (OA). This study investigated whether this association was causal using a Mendelian randomization (MR) study in a population-based cohort in Korean. The study enrolled 2429 subjects (1058 men, 1371 women) from the Dong-gu Study. X-rays of the hand and knee joints were scored using a semi-quantitative grading system to calculate the total score of the hand and knee joints. ALDH2 rs671 genotyping was performed by high-resolution melting analysis. MR instrumental variable analysis and observational multivariable regression analysis were used to estimate the association between genetically predicted alcohol intake and the radiographic severity of OA. Subjects with the G/G genotype had a higher current alcohol intake than those with the G/A and A/A genotypes in both men and women (all P < 0.001). Men with the G/G genotype had higher total knee (P < 0.001) and hand scores (P = 0.042) compared to those with the G/A and A/A genotypes after adjusting for age and body mass index, but not in women. In the observational multivariable regression analysis, each alcohol drink per day in men was associated with increased knee (P = 0.001) and hand joint scores (P = 0.013) after adjustment, but not in women. In our MR analysis, utilizing ALDH2 rs671 genotypes as instrumental variables for alcohol consumption, has shown a significant link between each additional daily alcohol drink and increased radiographic joint severity in men.
A robust self-supervised approach for fine-grained crack detection in concrete structures
Authors: Sohaib Muhammad , Hasan Md Junayed , Shah Mohd Asif , Zheng Zhonglong 
Published: June 2024

AbstractThis work addresses a critical issue: the deterioration of concrete structures due to fine-grained cracks, which compromises their strength and longevity. To tackle this problem, experts have turned to computer vision (CV) based automated strategies, incorporating object detection and image segmentation techniques. Recent efforts have integrated complex techniques such as deep convolutional neural networks (DCNNs) and transformers for this task. However, these techniques encounter challenges in localizing fine-grained cracks. This paper presents a self-supervised 'you only look once' (SS-YOLO) approach that utilizes a YOLOv8 model. The novel methodology amalgamates different attention approaches and pseudo-labeling techniques, effectively addressing challenges in fine-grained crack detection and segmentation in concrete structures. It utilizes convolution block attention (CBAM) and Gaussian adaptive weight distribution multi-head self-attention (GAWD-MHSA) modules to accurately identify and segment fine-grained cracks in concrete buildings. Additionally, the assimilation of curriculum learning-based self-supervised pseudo-labeling (CL-SSPL) enhances the model's ability when applied to limited-size data. The efficacy and viability of the proposed approach are demonstrated through experimentation, results, and ablation analysis. Experimental results indicate a mean average precision (mAP) of at least 90.01%, an F1 score of 87%, and an intersection over union threshold greater than 85%. It is evident from the results that the proposed method yielded at least 2.62% and 4.40% improvement in mAP and F1 values, respectively, when tested on three diverse datasets. Moreover, the inference time taken per image is 2 ms less than that of the compared methods.
Gastroesophageal reflux disease and non-alcoholic fatty liver disease: a two-sample Mendelian randomization combined with meta-analysis
Authors: Leng Xuan , Liao Wan-Zhe , Zheng Fen-Ping 
Published: June 2024

AbstractAccumulating evidence from observational studies have suggested an association between gastroesophageal reflux disease (GERD) and non-alcoholic fatty liver disease (NAFLD). However, due to that such studies are prone to biases, we imported Mendelian randomization (MR) to explore whether the causal association between two diseases exsit. Hence, we aimed to analysis the potential association with MR. The single nucleotide polymorphisms (SNPs) of GERD were retrieved from the genome-wide association study dataset as the exposure. The SNPs of NAFLD were taken from the FinnGen dataset as the outcome. The relationship was analyzed with the assistance of inverse variance weighted, MR-Egger, and weighted median. We also uitilized the MR-Egger intercept, Cochran’s Q test, leave-one-out analysis, MR-PRESSO, and Steiger directionality test to evaluate the robustness of the causal association. The meta-analysis were also implemented to give an overall evaluation. Finally, our analysis showed a causal relationship between GERD and NAFLD with aid of MR and meta-analysis (OR 1.71 95% CI 1.40–2.09; P < 0.0001).
xECGArch: a trustworthy deep learning architecture for interpretable ECG analysis considering short-term and long-term features
Authors: Goettling Marc , Hammer Alexander , Malberg Hagen , Schmidt Martin 
Published: June 2024

AbstractDeep learning-based methods have demonstrated high classification performance in the detection of cardiovascular diseases from electrocardiograms (ECGs). However, their blackbox character and the associated lack of interpretability limit their clinical applicability. To overcome existing limitations, we present a novel deep learning architecture for interpretable ECG analysis (xECGArch). For the first time, short- and long-term features are analyzed by two independent convolutional neural networks (CNNs) and combined into an ensemble, which is extended by methods of explainable artificial intelligence (xAI) to whiten the blackbox. To demonstrate the trustworthiness of xECGArch, perturbation analysis was used to compare 13 different xAI methods. We parameterized xECGArch for atrial fibrillation (AF) detection using four public ECG databases ($$n = 9854$$

n
=
9854

ECGs) and achieved an F1 score of 95.43% in AF versus non-AF classification on an unseen ECG test dataset. A systematic comparison of xAI methods showed that deep Taylor decomposition provided the most trustworthy explanations ($$+24\%$$

+
24
%

compared to the second-best approach). xECGArch can account for short- and long-term features corresponding to clinical features of morphology and rhythm, respectively. Further research will focus on the relationship between xECGArch features and clinical features, which may help in medical applications for diagnosis and therapy.