bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel BAG5 variant impairs the ER stress response pathway, causing dilated cardiomyopathy and arrhythmia
Authors: Wongong Rutairat , Kijtawornrat Anusak , Srichomthong Chalurmpon , Tongkobpeth Siraprapa , Od-Ek Phichittra , Assawapitaksakul Adjima , Caengprasath Natarin , Khongphatthanayothin Apichai , Porntaveetus Thantrira , Shotelersuk Vorasuk 
Published: May 2024

AbstractPathogenic BAG5 variants recently linked to dilated cardiomyopathy (DCM) prompt further investigation into phenotypic, mutational, and pathomechanistic aspects. We explored the clinical and molecular characteristics of DCM associated with BAG5 variants, uncovering the consistently severe manifestations of the disease and its impact on the endoplasmic reticulum (ER) stress response. The analysis involved three siblings affected by DCM and arrhythmia, along with their four unaffected siblings, their unaffected father, and their mother who exhibited arrhythmia. The parents were consanguineous. Exome and Sanger sequencing identified a novel BAG5 variant, c.444_445delGA (p.Lys149AsnfsTer6), homozygous in affected siblings and heterozygous in parents and unaffected siblings. We generated heterozygous and homozygous Bag5 point mutant knock-in (KI) mice and evaluated cardiac pathophysiology under stress conditions, including tunicamycin (TN) administration. Bag5−/− mice displayed no abnormalities up to 12 months old and showed no anomalies during an exercise stress test. However, following TN injection, Bag5−/− mice exhibited significantly reduced left ventricular fractional shortening (LVFS) and ejection fraction (LVEF). Their cardiac tissues exhibited a notable increase in apoptotic cells, despite non-distinctive changes in CHOP and GRP78 levels. Interestingly, only Bag5 KI male mice demonstrated arrhythmia, which was more pronounced in Bag5−/− than in Bag5+/−males. Here, our study reveals a novel BAG5 mutation causing DCM by impairing the ER stress response, with observed sex-specific arrhythmia differences.
Automated thorax disease diagnosis using multi-branch residual attention network
Authors: Li Dongfang , Huo Hua , Jiao Shupei , Sun Xiaowei , Chen Shuya 
Published: May 2024

AbstractChest X-ray (CXR) is an extensively utilized radiological modality for supporting the diagnosis of chest diseases. However, existing research approaches suffer from limitations in effectively integrating multi-scale CXR image features and are also hindered by imbalanced datasets. Therefore, there is a pressing need for further advancement in computer-aided diagnosis (CAD) of thoracic diseases. To tackle these challenges, we propose a multi-branch residual attention network (MBRANet) for thoracic disease diagnosis. MBRANet comprises three components. Firstly, to address the issue of inadequate extraction of spatial and positional information by the convolutional layer, a novel residual structure incorporating a coordinate attention (CA) module is proposed to extract features at multiple scales. Next, based on the concept of a Feature Pyramid Network (FPN), we perform multi-scale feature fusion in the following manner. Thirdly, we propose a novel Multi-Branch Feature Classifier (MFC) approach, which leverages the class-specific residual attention (CSRA) module for classification instead of relying solely on the fully connected layer. In addition, the designed BCEWithLabelSmoothing loss function improves the generalization ability and mitigates the problem of class imbalance by introducing a smoothing factor. We evaluated MBRANet on the ChestX-Ray14, CheXpert, MIMIC-CXR, and IU X-Ray datasets and achieved average AUCs of 0.841, 0.895, 0.805, and 0.745, respectively. Our method outperformed state-of-the-art baselines on these benchmark datasets.
Effect of high temperature on mechanical properties of lithium slag concrete
Authors: Liang Jiongfeng , Zou Wanjie , Tian Yongliang , Wang Caisen , Li Wei 
Published: May 2024

AbstractAs the main gel material of concrete, cement is used in an astonishing amount every year in the construction industry. However, a large amount of CO2 is emitted into the atmosphere while producing cement. Therefore, it is the general trend to look for substitutes for cement and develop new green concrete. Lithium slag (LS) is the industrial waste discharged from lithium salt plants. Through testing, it is found that the chemical composition of LS has a high degree of coincidence with ordinary Portland cement (OPC) Therefore, LS can be incorporated into concrete as supplementary cementations material (SCM) to prepare lithium slag concrete (LSC). The pollution of the natural environment caused by a large number of piled-up and landfilled LS is immeasurable. Consuming and using LS in large quantities and with high efficiency not only eliminates the pollution of lithium slag to the natural environment, but also helps to reduce the amount of cement used in green concrete and truly reuse waste resources. In order to study the mechanical properties of post-heated LSC, the test were carried out for LSC specimens after high-temperature. The main influence factors were considered, including the temperatures of 20℃, 100 ℃, 300 ℃, 500 ℃ and 700 ℃, the contents of lithium slag in LSC of 0%, 10%, 20% and 30%, cooling method of LSC after exposure high temperature. The results showed that the mechanical properties of LS concrete specimens were slightly improved at 100 ℃, and when the temperature was 300 ℃ or higher, the damage to the specimens was huge and irreversible. An appropriate amount of LS (20% lithium slag content) could improve the strength of LSC. This paper also studied the relationship between lithium slag content and strengths of LS concrete. The research results show that adding an appropriate amount of LS to concrete improves the mechanical properties of concrete. When the LS replacement rate is 20%, the mass loss rate of LSC after different high temperature treatments was the minimum. The cubic compressive strength, axial compressive strength, and flexural strength of specimens with 20% LS substitution can be increased by 8.16%, 8.33%, and 13.46% after high temperature. The cubic compressive strength, axial compressive strength, and flexural strength of specimens with 20% LS substitution can be increased by 8.16%, 8.33%, and 13.46% after high temperature.
The study on spatial distribution of water ecological environment carrying capacity during extreme drought conditions
Authors: Zhou Yang , Gui Yingying , Zhou Qiang , Li Li , Chen Miaomiao , Liu Yuling 
Published: May 2024

AbstractDue to global warming and the disturbance of the interannual variability of precipitation, the frequency of extreme drought events has increased. The impact of global climate change on water resources is becoming increasingly apparent, then it is particularly necessary to explore the carrying capacity of water ecological environment under extreme drought conditions, which can guarantee the ecological water security in river basins. This study takes the Guanzhong area of the Wei River Basin as an example, calculating the water environment carrying capacity of 40 areas in the Weihe Guanzhong area in different levels of years under extreme drought conditions by comprehensive evaluation model of carrying capacity and using geographic information system GIS to display the spatial distribution of water environment carrying capacity in 40 regions. According to the results of the spatial distribution of water environmental bearing capacity, four different schemes are designed to improve the bearing capacity. The first plan reduces the industrial water consumption and irrigation quota by 5%, the second plan increases the industrial water and sewage treatment rate on this basis. the third plan further improves the development and utilization rate of surface and groundwater, and the fourth plan, on the basis of the first three plans, supplies 600 million cubic meters of industrial and agricultural water to Guanzhong region. Through comparative analysis, without taking any measures, under the extreme drought conditions, the water environment carrying capacity of the 40 areas in Guanzhong is all in an unbearable state. Overall, plan 4 has the most significant improvement in the water environment-carrying capacity, especially the Dong zhuang Reservoir of the Jing River which has played a very important role in enhancing the water ecological environment carrying capacity of the downstream water of the Wei River.
Identification and clinical validation of diverse cell-death patterns-associated prognostic features among low-grade gliomas
Authors: Yang Wenyong , Yu Hui , Lei Qingqiang , Pu Chunlan , Guo Yuanbiao , Lin Liangbin 
Published: May 2024

AbstractLow-grade glioma (LGG) is heterogeneous at biological and transcriptomic levels, and it is still controversial for the definition and typing of LGG. Therefore, there is an urgent need for specific and practical molecular signatures for accurate diagnosis, individualized therapy, and prognostic evaluation of LGG. Cell death is essential for maintaining homeostasis, developing and preventing hyperproliferative malignancies. Based on diverse programmed cell death (PCD) related genes and prognostic characteristics of LGG, this study constructed a model to explore the mechanism and treatment strategies for LGG cell metastasis and invasion. We screened 1161 genes associated with PCD and divided 512 LGG samples into C1 and C2 subtypes by consistent cluster analysis. We analyzed the two subtypes' differentially expressed genes (DEGs) and performed functional enrichment analysis. Using R packages such as ESTIMATE, CIBERSOTR, and MCPcounter, we assessed immune cell scores for both subtypes. Compared with C1, the C2 subtype has a poor prognosis and a higher immune score, and patients in the C2 subtype are more strongly associated with tumor progression. LASSO and COX regression analysis screened four characteristic genes (CLU, FHL3, GIMAP2, and HVCN1). Using data sets from different platforms to validate the four-gene feature, we found that the expression and prognostic correlation of the four-gene feature had a high degree of stability, showing stable predictive effects. Besides, we found downregulation of CLU, FHL3, and GIMAP2 significantly impairs the growth, migration, and invasive potential of LGG cells. Take together, the four-gene feature constructed based on PCD-related genes provides valuable information for further study of the pathogenesis and clinical treatment of LGG.
Farmer typology and drivers of agricultural mechanization use in Haiti
Authors: Paul Bénédique , Régis Jude 
Published: May 2024

AbstractAgricultural mechanization is recognized as an important technology to increase agricultural productivity, face labor shortages, and reduce post-harvest loss. However, variations among farms’ characteristics and agricultural production systems suggest adopting a targeted strategy in mechanization programs for farmers. This research aimed to answer the following questions in the particular case of Haiti: are there different types of smallholder farmers in terms of mechanization use and socio-economic characteristics? What types of mechanization are used by farmers, and what drives their use among different types of farmers? What are the different types of farms in terms of mechanization use? We used typology construction methodology (principal component analysis (PCA) and hierarchical cluster analysis (HCA)) for a sample of 637 farmers and have identified four different clusters of farmers according to the characteristics of the farms they managed: “Little rain-fed farms” (cluster 1), “Little lowlands farms” (cluster 2), “Medium-sized farms in irrigated plains” (cluster 3), and “Large fragmented mountain farms”. Farms in cluster 3 were those who used more agricultural mechanization, and the results of multinomial logistic regression (MNLR) model revealed that the significant drivers of this use were location, access to credit and low food security status. Mechanization use of farms in clusters 1 and 4 was distinctively driven by saving behavior and off-farm income, respectively. In the pooled sample, the drivers of mechanization were: regions or location, age of the farmers, irrigation, livestock, access to credit, off-farm income and food security status. This study contributes to the literature by testing new drivers of agricultural mechanization such as food security status, and off-farm income. The findings can be used to design appropriate mechanization strategies to increase productivity and face labor price/scarcity challenges. They suggest that mechanization policies should focus on agricultural equipment that are adapted to the specificities of the production systems of each farm type, and strengthen access to credit. Otherwise, mechanization will be predominantly used only in irrigated lowlands.
Deep-learning segmentation to select liver parenchyma for categorizing hepatic steatosis on multinational chest CT
Authors: Zhang Zhongyi , Li Guixia , Wang Ziqiang , Xia Feng , Zhao Ning , Nie Huibin , Ye Zezhong , Lin Joshua S. , Hui Yiyi , Liu Xiangchun 
Published: May 2024

AbstractUnenhanced CT scans exhibit high specificity in detecting moderate-to-severe hepatic steatosis. Even though many CTs are scanned from health screening and various diagnostic contexts, their potential for hepatic steatosis detection has largely remained unexplored. The accuracy of previous methodologies has been limited by the inclusion of non-parenchymal liver regions. To overcome this limitation, we present a novel deep-learning (DL) based method tailored for the automatic selection of parenchymal portions in CT images. This innovative method automatically delineates circular regions for effectively detecting hepatic steatosis. We use 1,014 multinational CT images to develop a DL model for segmenting liver and selecting the parenchymal regions. The results demonstrate outstanding performance in both tasks. By excluding non-parenchymal portions, our DL-based method surpasses previous limitations, achieving radiologist-level accuracy in liver attenuation measurements and hepatic steatosis detection. To ensure the reproducibility, we have openly shared 1014 annotated CT images and the DL system codes. Our novel research contributes to the refinement the automated detection methodologies of hepatic steatosis on CT images, enhancing the accuracy and efficiency of healthcare screening processes.
A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders
Authors: Zadka Assaf , Rabin Neta , Gazit Eran , Mirelman Anat , Nieuwboer Alice , Rochester Lynn , Del Din Silvia , Pelosin Elisa , Avanzino Laura , Bloem Bastiaan R. , Della Croce Ugo , Cereatti Andrea , Hausdorff Jeffrey M. 
Published: May 2024

AbstractStep length is an important diagnostic and prognostic measure of health and disease. Wearable devices can estimate step length continuously (e.g., in clinic or real-world settings), however, the accuracy of current estimation methods is not yet optimal. We developed machine-learning models to estimate step length based on data derived from a single lower-back inertial measurement unit worn by 472 young and older adults with different neurological conditions, including Parkinson’s disease and healthy controls. Studying more than 80,000 steps, the best model showed high accuracy for a single step (root mean square error, RMSE = 6.08 cm, ICC(2,1) = 0.89) and higher accuracy when averaged over ten consecutive steps (RMSE = 4.79 cm, ICC(2,1) = 0.93), successfully reaching the predefined goal of an RMSE below 5 cm (often considered the minimal-clinically-important-difference). Combining machine-learning with a single, wearable sensor generates accurate step length measures, even in patients with neurologic disease. Additional research may be needed to further reduce the errors in certain conditions.
Genome of the endangered eastern quoll (Dasyurus viverrinus) reveals signatures of historical decline and pelage color evolution
Authors: Hartley Gabrielle A. , Frankenberg Stephen R. , Robinson Natasha M. , MacDonald Anna J. , Hamede Rodrigo K. , Burridge Christopher P. , Jones Menna E. , Faulkner Tim , Shute Hayley , Rose Karrie , Brewster Rob , O’Neill Rachel J. , Renfree Marilyn B. , Pask Andrew J. , Feigin Charles Y. 
Published: May 2024

AbstractThe eastern quoll (Dasyurus viverrinus) is an endangered marsupial native to Australia. Since the extirpation of its mainland populations in the 20th century, wild eastern quolls have been restricted to two islands at the southern end of their historical range. Eastern quolls are the subject of captive breeding programs and attempts have been made to re-establish a population in mainland Australia. However, few resources currently exist to guide the genetic management of this species. Here, we generated a reference genome for the eastern quoll with gene annotations supported by multi-tissue transcriptomes. Our assembly is among the most complete marsupial genomes currently available. Using this assembly, we infer the species’ demographic history, identifying potential evidence of a long-term decline beginning in the late Pleistocene. Finally, we identify a deletion at the ASIP locus that likely underpins pelage color differences between the eastern quoll and the closely related Tasmanian devil (Sarcophilus harrisii).
Coupling thermotolerance and high production of recombinant protein by CYR1N1546K mutation via cAMP signaling cascades
Authors: Ren Haiyan , Lan Qing , Zhou Shihao , Lyu Yilin , Yu Yao , Zhou Jungang , Mo Wenjuan , Lu Hong 
Published: May 2024

AbstractIn recombinant protein-producing yeast strains, cells experience high production-related stresses similar to high temperatures. It is possible to increase recombinant protein production by enhancing thermotolerance, but few studies have focused on this topic. Here we aim to identify cellular regulators that can simultaneously activate thermotolerance and high yield of recombinant protein. Through screening at 46 °C, a heat-resistant Kluyveromyces marxianus (K. marxianus) strain FDHY23 is isolated. It also exhibits enhanced recombinant protein productivity at both 30 °C and high temperatures. The CYR1N1546K mutation is identified as responsible for FDHY23’s improved phenotype, characterized by weakened adenylate cyclase activity and reduced cAMP production. Introducing this mutation into the wild-type strain greatly enhances both thermotolerance and recombinant protein yields. RNA-seq analysis reveals that under high temperature and recombinant protein production conditions, CYR1 mutation-induced reduction in cAMP levels can stimulate cells to improve its energy supply system and optimize material synthesis, meanwhile enhance stress resistance, based on the altered cAMP signaling cascades. Our study provides CYR1 mutation as a novel target to overcome the bottleneck in achieving high production of recombinant proteins under high temperature conditions, and also offers a convenient approach for high-throughput screening of recombinant proteins with high yields.
SpatialPrompt: spatially aware scalable and accurate tool for spot deconvolution and domain identification in spatial transcriptomics
Authors: Swain Asish Kumar , Pandit Vrushali , Sharma Jyoti , Yadav Pankaj 
Published: May 2024

AbstractEfficiently mapping of cell types in situ remains a major challenge in spatial transcriptomics. Most spot deconvolution tools ignore spatial coordinate information and perform extremely slow on large datasets. Here, we introduce SpatialPrompt, a spatially aware and scalable tool for spot deconvolution and domain identification. SpatialPrompt integrates gene expression, spatial location, and single-cell RNA sequencing (scRNA-seq) dataset as reference to accurately infer cell-type proportions of spatial spots. SpatialPrompt uses non-negative ridge regression and graph neural network to efficiently capture local microenvironment information. Our extensive benchmarking analysis on Visium, Slide-seq, and MERFISH datasets demonstrated superior performance of SpatialPrompt over 15 existing tools. On mouse hippocampus dataset, SpatialPrompt achieves spot deconvolution and domain identification within 2 minutes for 50,000 spots. Overall, domain identification using SpatialPrompt was 44 to 150 times faster than existing methods. We build a database housing 40 plus curated scRNA-seq datasets for seamless integration with SpatialPrompt for spot deconvolution.
Eco-friendly and biocompatible gelatin plasmonic filters for UV-vis-NIR light
Authors: Becerril-Castro I. Brian , Negrín-Montecelo Yoel , Moreno Josep , Correa-Duarte Miguel A. , Giannini Vincenzo , Alvarez-Puebla Ramón A. 
Published: May 2024

AbstractThe quest for environmentally sustainable materials spans many fields and applications including optical materials. Here, we present the development of light filters using a gelatin-based nanocomposite. Owing to the plasmonic properties of metallic nanoparticles (NPs), strong light-matter interactions, these filters can be customized across the UV-Visible-NIR spectrum. The filters are designed for modular use, allowing for the addition or removal of desired spectral ranges. Moreover, the nanocomposites are composed of biodegradable and biocompatible materials which highlight the intersection of chemistry and ecological awareness for the exploration of new eco-friendly alternatives. These plasmonic gelatin-based filters block light due to the Localized Surface Plasmon Resonance (LSPR) of the NPs and can be tailored to meet various requirements, akin to a diner selecting options from a menu. This approach is inspired by culinary techniques, and we anticipate it will stimulate further exploration of biomaterials for applications in optics, materials science or electronics.
In situ observation and reduction of hot-cracks in laser additive manufacturing
Authors: Chen Yunhui , Zhang Duyao , O’Toole Patrick , Qiu Dong , Seibold Marc , Schricker Klaus. , Bergmann Jean-Pierre , Rack Alexander , Easton Mark 
Published: May 2024

AbstractCracking during Laser Additive Manufacturing is a problem for many higher-strength aluminium alloys, including AA6061. Here, we used a pulsed laser with ramp-down power modulation to improve the cracking resistance by about 50% compared to the use of a rectangular pulsed laser. Using synchrotron in situ X-ray imaging at 100,000 images s−1, ground truth data was obtained about changes in melt pool geometry, solidification rate, and thermal gradients were calculated. An analytical hot cracking model was developed to show that these changes lead to a decreased hot tear susceptibility. Therefore, laser pulse modulation can be an effective tool to reduce crack susceptibility of alloys. More fundamentally, the results demonstrate that modifying thermal conditions provides a pathway to crack elimination in LAM and the model established in our study sets the foundation for further complex laser manipulation in modifying the printability and resulting mechanical properties of hard-to-process alloys in Laser Additive Manufacturing.