bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electron beam lithography on nonplanar and irregular surfaces
Authors: Zhu Chenxu , Ekinci Huseyin , Pan Aixi , Cui Bo , Zhu Xiaoli 
Published: April 2024

AbstractE-beam lithography is a powerful tool for generating nanostructures and fabricating nanodevices with fine features approaching a few nanometers in size. However, alternative approaches to conventional spin coating and development processes are required to optimize the lithography procedure on irregular surfaces. In this review, we summarize the state of the art in nanofabrication on irregular substrates using e-beam lithography. To overcome these challenges, unconventional methods have been developed. For instance, polymeric and nonpolymeric materials can be sprayed or evaporated to form uniform layers of electron-sensitive materials on irregular substrates. Moreover, chemical bonds can be applied to help form polymer brushes or self-assembled monolayers on these surfaces. In addition, thermal oxides can serve as resists, as the etching rate in solution changes after e-beam exposure. Furthermore, e-beam lithography tools can be combined with cryostages, evaporation systems, and metal deposition chambers for sample development and lift-off while maintaining low temperatures. Metallic nanopyramids can be fabricated on an AFM tip by utilizing ice as a positive resistor. Additionally, Ti/Au caps can be patterned around a carbon nanotube. Moreover, 3D nanostructures can be formed on irregular surfaces by exposing layers of anisole on organic ice surfaces with a focused e-beam. These advances in e-beam lithography on irregular substrates, including uniform film coating, instrumentation improvement, and new pattern transferring method development, substantially extend its capabilities in the fabrication and application of nanoscale structures.
Formation of a zirconium oxide crystal nucleus in the initial nucleation stage in aluminosilicate glass investigated by X-ray multiscale analysis
Authors: Onodera Yohei , Takimoto Yasuyuki , Hijiya Hiroyuki , Li Qing , Tajiri Hiroo , Ina Toshiaki , Kohara Shinji 
Published: April 2024

Abstract
Understanding the nucleation mechanism in glass is crucial for the development of new glass-ceramic materials. Herein, we report the structure of a commercially important glass-ceramic ZrO2-doped lithium aluminosilicate system during its initial nucleation stage. We conducted an X-ray multiscale analysis, and this analysis was used to observe the structure from the atomic to the nanometer scale by using diffraction, small-angle scattering, absorption, and anomalous scattering techniques. The inherent phase separation between the Zr-rich and Zr-poor regions in the pristine glass was enhanced by thermal treatment without changing the spatial geometry at the nanoscale. Element-specific pair distribution function analysis using anomalous X-ray scattering data showed the formation of a liquid ZrO2-like local structural motif and edge sharing between the ZrO
x
polyhedra and (Si/Al)O4 tetrahedra during the initial nucleation stage. Furthermore, the local structure of the Zr4+ ions resembled a cubic or tetragonal ZrO2 crystalline phase and formed after 2 h of annealing the pristine glass. Therefore, the Zr-centric periodic structure formed in the early stage of nucleation was potentially the initial crystal nucleus for the Zr-doped lithium aluminosilicate glass-ceramic.
Electrochemically controlled blinking of fluorophores for quantitative STORM imaging
Authors: Yang Ying , Ma Yuanqing , Berengut Jonathan F. , Lee Lawrence K. , Tilley Richard D. , Gaus Katharina , Gooding J. Justin 
Published: April 2024

AbstractStochastic optical reconstruction microscopy (STORM) allows wide-field imaging with single-molecule resolution by calculating the coordinates of individual fluorophores from the separation of fluorophore emission in both time and space. Such separation is achieved by photoswitching the fluorophores between a long-lived OFF state and an emissive ON state. Although STORM can image single molecules, molecular counting remains challenging due to undercounting errors from photobleached or overlapping dyes and overcounting artefacts from the repetitive random blinking of dyes. Here we show that fluorophores can be electrochemically switched for STORM imaging (EC-STORM), with excellent control over the switching kinetics, duty cycle and recovery yield. Using EC-STORM, we demonstrate molecular counting by using electrochemical potential to control the photophysics of dyes. The random blinking of dyes is suppressed by a negative potential but the switching-ON event can be activated by a short positive-potential pulse, such that the frequency of ON events scales linearly with the number of underlying dyes. We also demonstrate EC-STORM of tubulin in fixed cells with a spatial resolution as low as ~28 nm and counting of single Alexa 647 fluorophores on various DNA nanoruler structures. This control over fluorophore switching will enable EC-STORM to be broadly applicable in super-resolution imaging and molecular counting.
Deep-learning model for evaluating histopathology of acute renal tubular injury
Authors: Nguyen Thi Thuy Uyen , Nguyen Anh-Tien , Kim Hyeongwan , Jung Yu Jin , Park Woong , Kim Kyoung Min , Park Ilwoo , Kim Won 
Published: April 2024

AbstractTubular injury is the most common cause of acute kidney injury. Histopathological diagnosis may help distinguish between the different types of acute kidney injury and aid in treatment. To date, a limited number of study has used deep-learning models to assist in the histopathological diagnosis of acute kidney injury. This study aimed to perform histopathological segmentation to identify the four structures of acute renal tubular injury using deep-learning models. A segmentation model was used to classify tubule-specific injuries following cisplatin treatment. A total of 45 whole-slide images with 400 generated patches were used in the segmentation model, and 27,478 annotations were created for four classes: glomerulus, healthy tubules, necrotic tubules, and tubules with casts. A segmentation model was developed using the DeepLabV3 architecture with a MobileNetv3-Large backbone to accurately identify the four histopathological structures associated with acute renal tubular injury in PAS-stained mouse samples. In the segmentation model for four structures, the highest Intersection over Union and the Dice coefficient were obtained for the segmentation of the “glomerulus” class, followed by “necrotic tubules,” “healthy tubules,” and “tubules with cast” classes. The overall performance of the segmentation algorithm for all classes in the test set included an Intersection over Union of 0.7968 and a Dice coefficient of 0.8772. The Dice scores for the glomerulus, healthy tubules, necrotic tubules, and tubules with cast are 91.78 ± 11.09, 87.37 ± 4.02, 88.08 ± 6.83, and 83.64 ± 20.39%, respectively. The utilization of deep learning in a predictive model has demonstrated promising performance in accurately identifying the degree of injured renal tubules. These results may provide new opportunities for the application of the proposed methods to evaluate renal pathology more effectively.
Robust identification of interactions between heat-stress responsive genes in the chicken brain using Bayesian networks and augmented expression data
Authors: Videla Rodriguez E. A. , Mitchell John B. O. , Smith V. Anne 
Published: April 2024

AbstractBayesian networks represent a useful tool to explore interactions within biological systems. The aims of this study were to identify a reduced number of genes associated with a stress condition in chickens (Gallus gallus) and to unravel their interactions by implementing a Bayesian network approach. Initially, one publicly available dataset (3 control vs. 3 heat-stressed chickens) was used to identify the stress signal, represented by 25 differentially expressed genes (DEGs). The dataset was augmented by looking for the 25 DEGs in other four publicly available databases. Bayesian network algorithms were used to discover the informative relationships between the DEGs. Only ten out of the 25 DEGs displayed interactions. Four of them were Heat Shock Proteins that could be playing a key role, especially under stress conditions, where maintaining the correct functioning of the cell machinery might be crucial. One of the DEGs is an open reading frame whose function is yet unknown, highlighting the power of Bayesian networks in knowledge discovery. Identifying an initial stress signal, augmenting it by combining other databases, and finally learning the structure of Bayesian networks allowed us to find genes closely related to stress, with the possibility of further exploring the system in future studies.
Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis
Authors: Miguel Olivier X. , Kaczmarek Emily , Lee Inok , Ducharme Robin , Dingwall-Harvey Alysha L. J. , Rennicks White Ruth , Bonin Brigitte , Aviv Richard I. , Hawken Steven , Armour Christine M. , Dick Kevin , Walker Mark C. 
Published: April 2024

AbstractDeep learning algorithms have demonstrated remarkable potential in clinical diagnostics, particularly in the field of medical imaging. In this study, we investigated the application of deep learning models in early detection of fetal kidney anomalies. To provide an enhanced interpretation of those models’ predictions, we proposed an adapted two-class representation and developed a multi-class model interpretation approach for problems with more than two labels and variable hierarchical grouping of labels. Additionally, we employed the explainable AI (XAI) visualization tools Grad-CAM and HiResCAM, to gain insights into model predictions and identify reasons for misclassifications. The study dataset consisted of 969 ultrasound images from unique patients; 646 control images and 323 cases of kidney anomalies, including 259 cases of unilateral urinary tract dilation and 64 cases of unilateral multicystic dysplastic kidney. The best performing model achieved a cross-validated area under the ROC curve of 91.28% ± 0.52%, with an overall accuracy of 84.03% ± 0.76%, sensitivity of 77.39% ± 1.99%, and specificity of 87.35% ± 1.28%. Our findings emphasize the potential of deep learning models in predicting kidney anomalies from limited prenatal ultrasound imagery. The proposed adaptations in model representation and interpretation represent a novel solution to multi-class prediction problems.
The impact of digital transformation on resource mismatch of Chinese listed companies
Authors: Wu Kedong , Liu Songzhu , Zhu Mengchun , Qu Yahui 
Published: April 2024

AbstractBased on a microeconomic entity perspective, this paper empirically examines the effect of enterprise digitalization on resource mismatch. We found that, firstly, an increasing in enterprise digitalization reduces resource mismatch. Moreover, the results remain robust after considering endogeneity and changing the variable measurements. Secondly, enterprise digitalization can significantly reduce resource mismatch of private and large-scale enterprises and significantly contribute to reducing enterprise resource mismatch in low marketability regions and eastern regions. Thirdly, enterprise digital transformation can reduce resource mismatch by decreasing operating costs and financing constraints; Executive incentives can help reduce resource mismatch in the digital process of enterprises. Fourthly, the increase in enterprise digitalization contributes to an enhance in corporate social responsibility, and enterprise resource mismatch plays a mediating role in the relationship of enterprise digitalization development improving corporate social responsibility. Finally, in response to the findings of the study, the paper suggests countermeasures for regional and corporate countermeasures regarding digital development.
Knowledge, attitude, and practice towards enhanced recovery after surgery among colorectal cancer patients
Authors: Xu Peng , Li Da , Li Jian , Zhang Cheng 
Published: April 2024

AbstractTo explore the knowledge, attitude, and practice (KAP) towards enhanced recovery after surgery (ERAS) among colorectal cancer (CRC) patients. This cross-sectional study included CRC patients who underwent selective operation at the author’s Hospital, between April 2021 and April 2023. Their demographic characteristics and KAP towards ERAS were collected using a self-designed questionnaire. A total of 652 valid questionnaires were collected, with knowledge, attitude, and practice scores of 37.29 ± 11.35 (possible range: 11–55), 39.51 ± 6.40 (possible range: 11–55), and 6.53 ± 2.21 (possible range: 0–8), respectively. A positive correlation was found between knowledge and attitude (r = 0.291, P < 0.001), knowledge and practice (r = 0.292, P < 0.001), and attitude and practice (r = 0.363, P < 0.001). Structural equation model (SEM) analysis showed that knowledge had a significant direct effect on attitude (β = 0.164, P < 0.001) and attitude had direct effect on practice (β = 0.099, P < 0.001), indicating an indirect effect of knowledge on practice. Attitude also had a direct effect on practice (β = 0.038, P < 0.001). CRC patients showed moderate knowledge and attitude, and proactive practice towards ERAS. Further improvement of knowledge may improve their attitude and practice, leading to better outcomes and quality of care among CRC patients.
Comparison of enjoyment and energy expenditure of exergame with and without blood flow restriction in men and women
Authors: Mousavi Zeynabalsadat , Karimi Zohreh , Wong Alexei , Cheraghloo Neda , Bagheri Hessan , Bagheri Reza 
Published: April 2024

AbstractThis study compared the effects of blood flow restriction (BFR) on intensity and perceived enjoyment during an exergame. Fourteen healthy young participants engaged in a boxing exergame for 20 min, with or without BFR, across two sessions. Perceived enjoyment levels were assessed using the Physical Activity Enjoyment Scale. Heart rate was monitored, and energy expenditure (EE) during exercise was calculated. A mixed model analysis of variance with repeated measures was used to evaluate differences in EE and enjoyment between exergame conditions (with and without BFR) as well as the interaction effects of these protocols with gender. Although not statistically significant, perceived enjoyment decreased with BFR inclusion for both genders. No significant differences were observed between men and women for both protocols. Regarding EE, there was no significant difference between the two groups (with and without BFR). However, a significant main effect of gender was found, with men exhibiting higher EE values in both protocols compared to women. In conclusion, exergames incorporating BFR impact perceptual responses, particularly perceived enjoyment. Furthermore, significant gender differences in EE were found, with men displaying higher values.
Narazaciclib, a novel multi-kinase inhibitor with potent activity against CSF1R, FLT3 and CDK6, shows strong anti-AML activity in defined preclinical models
Authors: Yang Tao , Ke Hang , Liu Jinping , An Xiaoyu , Xue Jia , Ning Jinying , Hao Feng , Xiong Lingxin , Chen Cen , Wang Yueying , Zheng Jia , Gao Bing , Bao Zhengzheng , Gong Kefeng , Zhang Lei , Zhang Faming , Guo Sheng , Li Qi-Xiang 
Published: April 2024

AbstractCSF1R is a receptor tyrosine kinase responsible for the growth/survival/polarization of macrophages and overexpressed in some AML patients. We hypothesized that a novel multi-kinase inhibitor (TKi), narazaciclib (HX301/ON123300), with high potency against CSF1R (IC50 ~ 0.285 nM), would have anti-AML effects. We tested this by confirming HX301’s high potency against CSF1R (IC50 ~ 0.285 nM), as well as other kinases, e.g. FLT3 (IC50 of ~ 19.77 nM) and CDK6 (0.53 nM). An in vitro proliferation assay showed that narazaciclib has a high growth inhibitory effect in cell cultures where CSF1R or mutant FLT3-ITD variants that may be proliferation drivers, including primary macrophages (IC50 of 72.5 nM) and a subset of AML lines (IC50 < 1.5 μM). In vivo pharmacology modeling of narazaciclib using five AML xenografts resulted in: inhibition of MV4-11 (FLT3-ITD) subcutaneous tumor growth and complete suppression of AM7577-PDX (FLT3-ITD/CSF1Rmed) systemic growth, likely due to the suppression of FLT3-ITD activity; complete suppression of AM8096-PDX (CSF1Rhi/wild-type FLT3) growth, likely due to the inhibition of CSF1R (“a putative driver”); and nonresponse of both AM5512-PDX and AM7407-PDX (wild-type FLT3/CSF1Rlo). Significant leukemia load reductions in bone marrow, where disease originated, were also achieved in both responders (AM7577/AM8096), implicating that HX301 might be a potentially more effective therapy than those only affecting peripheral leukemic cells. Altogether, narazaciclib can potentially be a candidate treatment for a subset of AML with CSF1Rhi and/or mutant FLT3-ITD variants, particularly second generation FLT3 inhibitor resistant variants.
Differences in diacylglycerol acyltransferases expression patterns and regulation cause distinct hepatic triglyceride deposition in fish
Authors: Xiang Xiaojun , Ji Renlei , Han Shangzhe , Xu Xiang , Zhu Si , Li Yongnan , Du Jianlong , Mai Kangsen , Ai Qinghui 
Published: April 2024

AbstractTriglyceride (TAG) deposition in the liver is associated with metabolic disorders. In lower vertebrate, the propensity to accumulate hepatic TAG varies widely among fish species. Diacylglycerol acyltransferases (DGAT1 and DGAT2) are major enzymes for TAG synthesis. Here we show that large yellow croaker (Larimichthys crocea) has significantly higher hepatic TAG level than that in rainbow trout (Oncorhynchus mykiss) fed with same diet. Hepatic expression of DGATs genes in croaker is markedly higher compared with trout under physiological condition. Meanwhile, DGAT1 and DGAT2 in both croaker and trout are required for TAG synthesis and lipid droplet formation in vitro. Furthermore, oleic acid treatment increases DGAT1 expression in croaker hepatocytes rather than in trout and has no significant difference in DGAT2 expression in two fish species. Finally, effects of various transcription factors on croaker and trout DGAT1 promoter are studied. We find that DGAT1 is a target gene of the transcription factor CREBH in croaker rather than in trout. Overall, hepatic expression and transcriptional regulation of DGATs display significant species differences between croaker and trout with distinct hepatic triglyceride deposition, which bring new perspectives on the use of fish models for studying hepatic TAG deposition.
Single-cell transcriptomics unveil profiles and interplay of immune subsets in rare autoimmune childhood Sjögren’s disease
Authors: Kim Myung-Chul , De Umasankar , Borcherding Nicholas , Wang Lei , Paek Joon , Bhattacharyya Indraneel , Yu Qing , Kolb Ryan , Drashansky Theodore , Thatayatikom Akaluck , Zhang Weizhou , Cha Seunghee 
Published: April 2024

AbstractChildhood Sjögren’s disease represents critically unmet medical needs due to a complete lack of immunological and molecular characterizations. This study presents key immune cell subsets and their interactions in the periphery in childhood Sjögren’s disease. Here we show that single-cell RNA sequencing identifies the subsets of IFN gene-enriched monocytes, CD4+ T effector memory, and XCL1+ NK cells as potential key players in childhood Sjögren’s disease, and especially in those with recurrent parotitis, which is the chief symptom prompting clinical visits from young children. A unique cluster of monocytes with type I and II IFN-related genes is identified in childhood Sjögren’s disease, compared to the age-matched control. In vitro regulatory T cell functional assay demonstrates intact functionality in childhood Sjögren’s disease in contrast to reduced suppression in adult Sjögren’s disease. Mapping this transcriptomic landscape and interplay of immune cell subsets will expedite the understanding of childhood Sjögren’s disease pathogenesis and set the foundation for precision medicine.
Mainstreaming systematic climate action in energy infrastructure to support the sustainable development goals
Authors: Wernersson Louise , Román Simon , Fuso Nerini Francesco , Mutyaba Robert , Stratton-Short Samantha , Adshead Daniel 
Published: April 2024

AbstractThe energy sector is the largest emitter of greenhouse gas emissions, accounting for 37% of the world’s combined emissions, and plays a key role in achieving the Sustainable Development Goals. However, there is no systematic means for planners and practitioners to integrate climate considerations throughout the lifecycle of energy infrastructure projects. Using a thematic document analysis, we provide a comprehensive list of activities related to climate mitigation and adaptation which can be systematically mainstreamed into the energy sector project lifecycle to support a range of sustainable development outcomes. Two renewable energy projects were used to integrate the results into a practical context and demonstrate the range of potential SDG target synergies. The case studies demonstrate the varied means by which climate action can be integrated through mainstreaming in project lifecycle stages, holistically achieving wider SDG impacts. This work provides a practical means to maximise progress within the framework of climate-compatible development.
Words Matter: Reframing Communication Sciences and Disorders Programs' Thinking About Adolescents
Authors: Nellenbach Kristin , Knight Carrie , Jennings Bailey 
Published: April 2024

Purpose:
The purpose of this investigation was to evaluate language development and disorders course titles across communication sciences and disorders (CSD) graduate programs in an effort to determine whether adolescents were specifically being recognized via inclusive language or dedicated courses. The findings can be used to propel important discussions about the need for inclusive course titles, inform initial directions for improvements in preprofessional education, and guide broader changes in the discipline, especially for the adolescent population.

Method:
A review of accredited CSD graduate programs across the United States was conducted using the American Speech-Language-Hearing Association EdFind database. A total of 298 master's-level CSD programs were used for this study. CSD course titles located in each of the university's graduate catalogs were documented, categorized, and reviewed by the research team.

Results:
Of the 298 CSD graduate programs reviewed, one in eight specifically included the word “adolescent(s)” or “adolescence” in the titles of their language development and disorders courses. Remarkably, only four adolescent-focused courses, two of which were listed as electives, were offered across all reviewed programs. A post hoc analysis of the language used in course titling revealed that 42 titles used inclusive terminology.

Conclusions:
Adolescents are developmentally distinct from children, yet a majority of CSD graduate programs used ambiguous or exclusive words in the titles of their language development and disorders courses. The unintentional failure to recognize this important difference in course titles may be contributing to the ongoing neglect of adolescents within the field. Reframing collective thinking is required for change. Reasons and suggestions for including adolescents in course titles and separate offerings are provided to assist CSD graduate programs in leading the way toward improving equity for adolescents.