bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical and Laboratory Risk Factors of Early Poor Outcome in Patients With Childhood‐Onset Lupus Nephritis—A Single‐Center Retrospective Study
Authors: Qijiao Wei , Fujia Huang , Bing Yang , Changyan Wang , Linqing Zhong , Yanqing Dong , Wei Wang , Hongmei Song 
Published: February 2025

ABSTRACTObjectiveChildhood‐onset lupus nephritis (LN) tends to be more severe than in adults. A significant correlation between remission at 3 months of induction therapy and remission after 3 years was found in adults. While few studies on the risk factors of poor early prognosis in children with LN were made. Thus, this study investigated the risk factors of early poor response to help doctors develop effective treatment strategies.MethodsA total of 99 LN children at Peking Union Medical College Hospital from January 2012 to January 2018 were evaluated and clinical data were retrospectively collected. In the study, a complete remission (CR) was defined as laboratory test results were completely normal, including blood routine, renal function, albumin, complement, and erythrocyte sedimentation rate, and the 24‐h urinary total protein (24 h UTP) was less than 150 mg. After 3 months of treatment, 15 children achieved CR, and they were in good prognosis group (n = 15). While 84 did not achieve CR, and they were in poor prognosis group (n = 84). We compared the differences of clinical and laboratory indicators between the two groups.ResultsAccording to inclusion and exclusion criteria, 99 of 116 children with LN were included in this study. And 15 LN children were in good prognosis group. While 84 patients were in poor prognosis group. The incidence of rash (32.1% vs. 6.7%, p = 0.036) and oral ulcer (81.0% vs. 53.3%, p = 0.027) in poor prognosis group is higher than that in the good prognosis group. The 24 h UTP (g) [2.46 (1.41, 4.86) vs. 0.56 (0.30, 0.66), p < 0.001] and the serum creatinine (umol/L) [53.0 (40.3, 65.0) vs. 39.0 (29.8, 51.5), p = 0.017] were higher in poor prognosis group. The albumin (g/L) (28.7 ± 8.1 vs. 34.5 ± 5.3, p = 0.003) is lower in poor prognosis group. Logistic regression analysis showed that rash (p = 0.036), oral ulcer (p = 0.027), high 24 h UTP (p < 0.001), high creatinine (p = 0.017), and low serum albumin (p = 0.003) were significantly associated with poor early prognosis in childhood‐onset LN.ConclusionThe occurrence of rash cannot be ignored, especially for children with oral ulcers, a comprehensive evaluation of each system should be carried out, so as not to cause inactive treatment and affect the prognosis. High 24 h UTP have a positive predictive value for the early poor outcome of childhood‐onset LN. Active control of proteinuria and achieving rapid renal remission is crucial for good prognosis.
Carbonic anhydrase‐9‐targeted near‐infrared photoimmunotherapy as a theranostic modality for clear cell renal cell carcinoma
Authors: Fukushima Hiroshi , Takao Seiichiro , Furusawa Aki , Suzuki Motofumi , Yang Youfeng , Ricketts Christopher J. , Kano Makoto , Okuyama Shuhei , Yamamoto Hiroshi , Kano Miyu , Ball Mark W. , Choyke Peter L. , Linehan W. Marston , Kobayashi Hisataka 
Published: February 2025

AbstractCarbonic anhydrase‐9 (CA9) is highly expressed in clear cell renal cell carcinoma (ccRCC) cells despite no expression in normal kidney tissues. Thus, CA9 has been proposed as a theranostic target for radioligand therapy (RLT). However, ccRCC tends to be radioresistant and may not effectively respond to RLT. Alternatively, CA9 can be targeted for near‐infrared photoimmunotherapy (NIR‐PIT) of ccRCC. Here, we sought to test NIR‐PIT using CA9 in a preclinical model of ccRCC to determine its potential as a therapeutic strategy. Tissue microarray analysis showed that membrane CA9 was expressed in the majority of ccRCC cases. In vitro, CA9‐targeted NIR‐PIT induced cell membrane damage and cell killing in all CA9‐expressing ccRCC cell lines specifically, UOK154, UOK220, and UOK122. In vivo, CA9‐targeted NIR‐PIT significantly inhibited tumor growth and prolonged survival in UOK154 and UOK220 subcutaneous xenograft models. Notably, 70%–80% of mice achieved complete remission after a single treatment of NIR‐PIT. Additionally, remaining tumors after the first NIR‐PIT persistently expressed CA9, suggesting that remaining tumors can be treated with repeated NIR‐PIT. Furthermore, CA9‐targeted NIR‐PIT induced significant cytoplasmic damages on ccRCC cells in UOK154 orthotopic xenograft models. In conclusion, CA9‐targeted NIR‐PIT, which allow for safe and repeated application on the same lesion, is a promising treatment for ccRCC, especially in the management of multiple primary ccRCC (e.g., von Hippel–Lindau syndrome) and oligometastatic ccRCC.
Geopolitical Risks and the Predictability of Green Investments: A GARCH‐Based Mixed Data Sampling Approach
Authors: Adekoya Oluwasegun B. , Badmus Jamiu O. , Al‐Faryan Mamdouh Abdulaziz Saleh 
Published: February 2025

ABSTRACTThe frequent occurrences of geopolitical tensions, wars and conflicts continue to place a great limitation on the development of green projects, thereby reducing the incentives for sustainable investments. While there have been several attempts to connect geopolitical risks with financial market performance, there are still several limitations that this study intends to address. Among others, we make a comparison between the predictive impacts of global and country‐specific geopolitical risks on the volatility of green investment assets, putting threats and actual acts into perspective. Using the GARCH‐MIDAS methodology, we find that global geopolitical risks increase the volatility of most of the green investment assets, with the highest impact attributed to geopolitical risk threats. The country‐specific analysis shows more heterogeneous impacts, although a positive relationship is found in most cases. In Europe, the geopolitical risks of the Netherlands and the United Kingdom exert the strongest impacts on the volatility of green investments, whereas in the non‐European countries, the geopolitical risks of Russia and the United States have the strongest influence. Comparing regional impacts, the geopolitical risks of the non‐European countries have a stronger impact than those of the European countries.
Exploring the Impact of a Naturalist Training Camp on Biodiversity Conservation Willingness and Mental Well‐Being
Authors: Meng Yichuan , Zhao Jiangbo , Chen Jin 
Published: February 2025

ABSTRACTEngaging the public in naturalist activities has been identified as a promising approach to enhancing conservation awareness and improving mental well‐being; however, empirical evidence supporting this relationship remains limited. This study aimed to explore the impact of a naturalist training camp on participants' conservation attitudes and mental well‐being. The 9‐day camp, organized by the Xishuangbanna Tropical Botanical Garden (XTBG), focused on increasing participants' knowledge, social connectedness, and naturalist identity through a combination of indoor lectures and outdoor fieldwork on plants, insects, reptiles, and birds. Each session was led by expert researchers and science communicators. A mixed‐methods approach was used to assess the camp's effects on 26 participants through questionnaires administered before, immediately after, and 6 months post‐camp, as well as phone interviews. Quantitative analysis revealed significant improvements in participants' knowledge of biodiversity, social connectedness, perceived naturalist identity, and mental well‐being, although changes in conservation attitudes were not statistically significant. Qualitative data further supported these findings, indicating that enhanced conservation willingness and mental well‐being were likely influenced by increased knowledge, social connectedness, and perceived naturalist identity. Interview responses highlighted the importance of the camp's unique environment, supportive atmosphere, and the professionalism of the instructors in contributing to its success. Overall, this study underscores the value of promoting public engagement in naturalist activities as a means of addressing both biodiversity loss and mental health challenges while also advocating for ecological civilization to enhance human and environmental well‐being.
Hushed brilliance: Maintaining African American language‐speaking adolescent writers' rhetorical power
Authors: Breland Chevaunne Dara 
Published: February 2025

AbstractThis article examines African American rhetorical feature use in the secondary literacy classroom. It explores the historical evolution and pedagogical implications of incorporating African American rhetorical features into classroom writing instruction. The article discusses the historical evolution of African American Language and its position in the American literacy classroom. It also proposes actions educators can take in order to preserve African American Language‐speaking students' rhetorical style, including acknowledgment of African American Language, researching the evolution of African American Language in literacy education, and steps to support professional racialized linguistic self‐reflection. It also reviews recent literature and provides examples of African American rhetorical features educators can leverage while implementing instructional strategies that affirm African American Language‐speaking students. Understanding African American rhetorical feature's role in literacy education is crucial for developing equitable instructional practices that respect and affirm students' diverse linguistic backgrounds. This article offers valuable insight for secondary and middle school educators, policymakers, and researchers interested in language, race, literacy, and education. This article concludes that integrating culturally specific strategies into literacy practices can enhance student learning, confidence, and promote cultural equity. It calls for further research and policy development to support culturally affirming written literacy practices in schools.
Characterization of the Red Dye From Arthrinium phaeospermum and Its Application in Wood Dyeing
Authors: Wu Mengqi , Song Taize , Pang Tingwei , Zhuang Pengyan , Niu Jiashun , Li Yalan , Sun Jianping 
Published: February 2025

ABSTRACTThe aim of this study was to investigate the production, stability and applicability of dyes produced by filamentous fungi isolated from wood. First, the effect of culture conditions on fungal growth and dye production was investigated. The dyes were experimentally studied for solubility and stability and chemically characterized by FT‐IR and UPLC‐Q‐EXACTIVE‐MS. Finally, the dye was used to evaluate its industrial applicability by staining a variety of woods. The results showed that the filamentous fungus Arthrinium phaeospermum was able to produce red water‐soluble pigments, which were thermally and ultraviolet stable and remained stable in pH 1−9. Chemical analysis showed that the red dye contained the chromogenic substances bostrycin and about 7.01% of griseofulvin. Dyeing experiments showed that the red dye was able to give the wood a red color and a natural grain. The results of various experiments indicate that A. phaeospermum has the potential to produce dyes for use in the wood dyeing and textile industries.
Cultivation Strategies to Improve Chlamydomonas reinhardtii Growth and Recombinant Mcherry Expression
Authors: Pessoa Jassiara da Silva , Silva Bruno Guzzo da , Júnior Ednilson Donisete de França , Filho Isac José da Silva , Molino João Vitor Dutra , de Carvalho João Carlos Monteiro , Ferreira‐Camargo Livia Seno 
Published: February 2025

ABSTRACTChlamydomonas reinhardtii is a promising model microalga for recombinant molecules production. Nonetheless, low yield is a challenge for its industrial use. This work investigated the influence of ammonium chloride (NH4Cl) concentration and temperature on the growth of transgenic C. reinhardtii expressing the fluorescent protein mCherry on a laboratory scale. A Central Composite Rotatable Design was used to establish the cultivation conditions. NH4Cl concentrations ranging from 400 to 647.49 mg/L and temperatures between 25°C and 32.1°C resulted in maximum values of cell concentration and mCherry fluorescence. Lower temperatures (15°C–17°C) were found to be more suitable for the accumulation of total soluble proteins. These results demonstrate that cultivation conditions can positively affect C. reinhardtii growth, with a range of conditions that can be used. Unlike genetic approaches, this study provides a solution to enhance both growth and recombinant protein expression in C. reinhardtii. These findings pave the way for scaling up the use of C. reinhardtii as a biofactory in industry and can be applied to other microalgal systems.
Are the Risk Factors for Developing Type 1 and Type 2 Cesarean Scar Pregnancy Different?
Authors: Tang Yunhui , Qian Cuifeng , Li Man , Zhao Min , Chen Qi 
Published: February 2025

ObjectivesCesarean scar pregnancy (CSP) is a life‐threatening complication of pregnancy. Early termination of pregnancy is recommended because of the potential risks of uterine rupture if the pregnancy continues. CSP is clinically divided into type 1 and type 2, based on the site of embryo implantation and grow direction of the gestational sac. The clinical risk and treatment options may vary between these subtypes. Identifying the differences and potential factors impacting the development of each type could contribute to improved clinical management.MethodsThis retrospective study included 143 women with type 1 CSP and 200 women with type 2 CSP women, diagnosed between January 2020 and July 2023. The primary objective was to analyze the differences in clinical characteristics between the 2 CSP subtypes.ResultsBody mass index, the number of previous CSPs, elective abortions, gravidity, and parity were not significantly different between the 2 subtypes. Similarly, the interval between the last cesarean section and the current CSP was not associated with developing the 2 subtypes. However, women with more than 3 prior cesarean sections had an increased risk of developing type 1 CSP. In contrast, vaginal bleeding before diagnosis was more frequently associated with type 2 CSP.ConclusionsOur study with a large sample size found that despite type 2 CSP involving deeper myometrial invasion, the 2 subtypes share many clinical characteristics. Moreover, the clinical risk factors for distinguishing between type 1 and type 2 CSP are limited. Future research to identify predictors for CSP classification is required.
Spastic Paraplegia Type 78 Associated With ATP13A2 Gene Variants in Compound Heterozygosity
Authors: Ramírez R. Bermejo , Gascó N. Villena , Palmero L. Ruiz , Bueno G. A. Ribes , Yamanaka E. Seiti , Andújar J. D. Arroyo 
Published: February 2025

ABSTRACTBackgroundSpastic Paraplegia Type 78 (SPG78) is a rare form of hereditary spastic paraplegia (HSP), mainly characterized by late‐onset lower‐limb spasticity, muscle weakness, and in some cases cerebellar dysfunction and cognitive impairment. Understanding its genetic background is essential to distinguish it from other autosomal recessive types of HSP.MethodsA pathogenic variant screening in a Spanish HSP patient was carried out by whole‐exome sequencing, followed by a software filtering process and validation of candidate variants by Sanger sequencing. The pathogenicity of the selected variants was evaluated by In Silico predictions and a segregation analysis including the proband and 16 family members.ResultsTwo variants in the ATP13A2 gene, predicted to have damaging effects by In Silico analyses, were considered potentially pathogenic: NM022089.4:c.649G>A (rs199961048), previously associated with SPG78 but with uncertain clinical significance, and NM_022089.4:c.2097delC, an unreported variant. The segregation analysis revealed that both variants were present in compound heterozygosity in the proband and two affected siblings, while unaffected relatives carried only one or none of the variants.ConclusionThese findings suggest that the two variants are pathogenic when occurring in compound heterozygosity and, therefore, should be included in the genetic spectrum of SPG78 diagnosis.
Beam's eye view to fluence maps 3D network for ultra fast VMAT radiotherapy planning
Authors: Arberet Simon , Ghesu Florin C. , Gao Riqiang , Kraus Martin , Sackett Jonathan , Kuusela Esa , Kamen Ali 
Published: February 2025

AbstractBackgroundVolumetric modulated arc therapy (VMAT) revolutionizes cancer treatment by precisely delivering radiation while sparing healthy tissues. Fluence maps generation, crucial in VMAT planning, traditionally involves complex and iterative, and thus time consuming processes. These fluence maps are subsequently leveraged for leaf‐sequence. The deep‐learning approach presented in this article aims to expedite this by directly predicting fluence maps from patient data.PurposeTo accelerate VMAT treatment planning by quickly predicting fluence maps from a 3D dose map. The predicted fluence maps can be quickly leaf sequenced because the network was trained to take into account the machine constraints.MethodsWe developed a 3D network which we trained in a supervised way using a combination of and losses, and radiation therapy (RT) plans generated by Eclipse and from the REQUITE dataset, taking the RT dose map as input and the fluence maps computed from the corresponding RT plans as target. Our network predicts jointly the 180 fluence maps corresponding to the 180 control points (CP) of single arc VMAT plans. In order to help the network, we preprocess the input dose by computing the projections of the 3D dose map to the beam's eye view (BEV) of the 180 CPs, in the same coordinate system as the fluence maps. We generated over 2000 VMAT plans using Eclipse to scale up the dataset size. Additionally, we evaluated various network architectures and analyzed the impact of increasing the dataset size.ResultsWe are measuring the performance in the 2D fluence maps domain using image metrics (PSNR and SSIM), as well as in the 3D dose domain using the dose‐volume histogram (DVH) on a test set. The network inference, which does not include the data loading and processing, is less than 20 ms. Using our proposed 3D network architecture as well as increasing the dataset size using Eclipse improved the fluence map reconstruction performance by approximately 8 dB in PSNR compared to a U‐Net architecture trained on the original REQUITE dataset. The resulting DVHs are very close to the one of the input target dose.ConclusionsWe developed a novel deep learning approach for ultrafast VMAT planning by predicting all the fluence maps of a VMAT arc in one single network inference. The small difference of the DVH validate this approach for ultrafast VMAT planning.
Automatic bone marrow segmentation for precise [177Lu]Lu‐PSMA‐617 dosimetry
Authors: Lu Zhonglin , Hu Jiaxi , Chen Gefei , Jiang Han , Shih Cheng‐Ting , Afshar‐Oromieh Ali , Rominger Axel , Shi Kuangyu , Mok Greta S. P. 
Published: February 2025

AbstractBackgroundBone marrow (BM) is the dominant dose‐limiting organ in [177Lu]Lu‐PSMA‐617 therapy for patients with metastasized castration resistant prostate cancer, where BM dosimetry is challenging due to segmentation.PurposeWe aim to develop an automatic image‐based segmentation method on peri‐therapeutic sequential [177Lu]Lu‐PSMA‐617 images for personalized BM dosimetry.MethodsQuantitative SPECT/CT imaging at 2, 20, 40 and 60 (n = 14)/200 (n = 16) h post [177Lu]Lu‐PSMA‐617 injection were analyzed for 10 patients with 30 treatment cycles. X‐means clustering was applied on the deep learning‐based segmented lumbar spines CT images to classify the BM region. A single threshold method, two empirical segmentation methods (one sphere and five spheres), and gold standard manual segmentation were also implemented. The Dice similarity coefficient between BM masks of the X‐means clustering and single threshold method was calculated as compared to the gold standard. BM mean absorbed dose (Dmean) was obtained for different segmentation methods. Absolute errors and Bland–Altman analysis were also evaluated for BM Dmean derived from evaluated segmentation methods compared with the gold standard. Wilcoxon signed‐rank test was performed for statistical evaluation. BM Dmean was correlated with the change of platelets and white blood cells (WBC) pre‐ and post‐treatment using Pearson correlation analysis.ResultsIn 30 cycles of 10 patients, the average Dice is 0.76 ± 0.18 for the X‐means clustering method, as compared to 0.61 ± 0.19 for the single threshold method. The gold standard yields mean BM Dmean of 0.46 ± 0.69 Gy. The X‐means clustering method exhibits significantly (p < 0.01) lower mean absolute BM Dmean (25.34 ± 64.48%) errors, followed by the single threshold (32.46 ± 69.49%), one sphere (50.53 ± 35.40%), and five spheres (72.73 ± 115.97%) methods. Bland–Altman analysis reveals that the X‐means clustering method has a smaller Dmean difference (0.0330 Gy) compared to the single threshold (0.0512 Gy), one sphere (−0.1903 Gy), and five spheres (0.2108 Gy) methods. Stronger correlations (r ≤ −0.65) are found between platelets/WBC changes and BM Dmean from both the gold standard and X‐means clustering methods than other methods.ConclusionsX‐means clustering is feasible to segment the BM based on the CT images of peri‐therapy SPECT/CT and shows advantages compared with the single threshold and empirical sphere segmentation methods.
A deep learning‐based peer review method for radiotherapy planning
Authors: Zhou Pujun , Gu Huikuan , Peng Qinghe , Kang Dehua , Zhu Jinhan , Chen Li 
Published: February 2025

AbstractBackgroundQuality control (QC) in radiotherapy planning is crucial for ensuring treatment efficacy and patient safety. Traditionally, QC relies on standard indicators and subjective assessments, which may lead to inconsistencies.PurposeThis study aims to develop a novel peer review method for personalized QC in radiotherapy planning, which is based on patient anatomical information, and utilizes deep learning dose prediction and a statistical model.MethodsA UNet model was trained on 139 nasopharyngeal carcinoma patients to predict 3D dose distribution, with plans divided into 95 for training, 20 for validation, and 24 for testing. For the clinical evaluation (24 items in total) of organs at risk (OAR), the QC interval (qualified, acceptable, or unqualified) for these items was set according to the model accuracy. Peer review was performed on another 29 clinical treatment plans, the items identified by the model as requiring optimization and improvement were optimized, and the effectiveness of the peer review method was tested.ResultsThe predicted mean voxel‐based dose difference was 0.29 ± 0.13 Gy. For most evaluation items, the model prediction results were comparable to the planned results. Peer review results suggested that 66% of the plans were acceptable or unqualified. After optimization, 100% of the acceptable plans and 47% of the unqualified plans became qualified, and 20% of the unqualified plans became acceptable.ConclusionsA deep learning dose prediction model based on patient information can be used to develop personalized QC in radiotherapy planning and can help improve the quality of radiotherapy plans.