bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical Effectiveness of Tislelizumab With Gemcitabine/Cisplatin Versus Gemcitabine/Cisplatin Alone as Adjuvant Therapy for High‐Risk Muscle‐Invasive Urothelial Carcinoma: A Real‐World Study
Authors: Wang Yanjun , Zhong Kaihua , Tan Xingliang , Zhou Qianghua , Jiang Lijuan , Yao Kai , Wu Zhiming 
Published: February 2025

ABSTRACTBackgroundMuscle‐invasive urothelial carcinoma (MIUC) is a highly aggressive cancer associated with poor prognosis. Despite advancements in treatment, the optimal therapeutic approach remains unclear. Immune checkpoint inhibitors, when added to chemotherapy, have shown promise in improving patient outcomes.AimsThis study aimed to evaluate the efficacy and safety of adjuvant tislelizumab combined with gemcitabine/cisplatin (Tisle+GC) compared to GC alone in patients with high‐risk MIUC.Materials & MethodsWe conducted a retrospective analysis of 117 patients with histologically confirmed pT3/4 and pN+ MIUC treated at our center between October 2016 and March 2023. Eligible patients received either Tisle+GC or GC alone, excluding those with prior neoadjuvant therapy. We compared disease‐free survival (DFS), overall survival (OS), and treatment‐related adverse events (AEs) between the two groups using Cox proportional hazards models and Kaplan–Meier estimates.ResultsThe Tisle+GC group showed significantly longer median DFS (19.08 vs. 9.06 months, HR = 0.114, p < 0.001) and OS (20.07 vs. 10.63 months, HR = 0.083, p = 0.026) compared to the GC group. Nerve tract invasion was identified as a significant predictor of poor outcomes (HR = 22.1, p = 0.003). Both groups experienced manageable grade 1–2 immune‐related AEs, with pruritus being the most common, followed by liver function abnormalities and thyroid disturbances. Nonhematologic toxicities in the Tisle+GC group included elevated aspartate aminotransferase and hyponatremia, while the GC group mainly reported vomiting. No treatment‐related fatalities occurred.DiscussionThe addition of tislelizumab to GC chemotherapy significantly improved both DFS and OS in high‐risk MIUC patients. The safety profile was manageable, with immune‐related AEs being predictable and not life‐threatening. The findings support the potential of Tisle+GC as an effective adjuvant therapy.ConclusionTisle+GC is a promising adjuvant treatment for high‐risk MIUC, offering improved survival outcomes with a manageable safety profile. Further prospective studies are needed to confirm these results and establish the long‐term benefits of this combination therapy.
Selective Recognition of Nucleoside Triphosphates in Water by Tetraphenylethene‐Based Tetraimidazolium Cyclophanes†
Authors: Wang Pingxia , Li Yingjie , Zhao Lingu , Yang Yanxia , Kang Xuhao , Yang Ting , Cao Fan , Cheng Lin , Cao Liping 
Published: February 2025

Comprehensive SummaryThe design and development of selective recognition and sensing systems for biologically important nucleoside triphosphates (NTPs) have attracted significant attention in recent years, owing to their critical roles in cellular processes. In this study, we report the synthesis of two tetraphenylethene‐based tetraimidazolium cyclophanes (1 and 2) through a one‐step SN2 reaction. These cyclophanes are capable of recognizing NTPs by forming stable 1 : 1 host‐guest complexes in aqueous solution. Of particular interest, cyclophane 1 demonstrates exceptional selectivity for guanosine triphosphate (GTP), distinguishing it from other nucleoside triphosphates such as ATP, CTP, and UTP. This selective recognition is accompanied by distinct and measurable fluorescence responses, which are significantly enhanced upon binding to GTP, enabling the potential for sensitive detection. This study highlights the potential of tetraphenylethene‐based tetraimidazolium cyclophanes as a highly selective and sensitive sensor for GTP, offering new insights into the design of molecular systems for the recognition of biologically relevant nucleotides.
Assessing the Success of a Mineral Trioxide Aggregate and a Pre‐Mixed Bioceramic in Mature Teeth With Irreversible Pulpitis With Full Pulpotomy: A Randomized Clinical Trial
Authors: Suresh Sarang , Kalhoro Feroze A. , Rani Priya , Memon Mahwish 
Published: February 2025

ABSTRACTObjectivesThe aim of this study is to compare the clinical and radiographic success of MTA versus EBRRM in pulpotomy of permanent teeth with irreversible pulpitis without apical periodontitis.Material and MethodsClinical and radiographic assessments were conducted at baseline, 6 days, 6 weeks, and 6 months. After administration of anesthesia and coronal pulp removal, pulp was capped with MTA or Endo Sequence Bioceramic Root Repair, followed by restoration with a glass ionomer and resin composite.ResultsThe overall success rate for pulpotomy was 71.9%, with MTA and the bioceramic showing success rates of 32.8% and 39.1%, respectively. There was no significant relationship with the type of cavity and failure of pulpotomy.ConclusionsMTA and EBBRRM are both practical choices for pulpotomy and there is no notable difference between them in the success rate and pain level. EBBRRM may be more effective in Class 1 cavities than in Class 2 cavities.
Integrated Wireless Transmitter for EV and AGV With High Interoperability
Authors: Liu Chao , Zheng Feijie , Zhuang Yizhan , Chen Xiaoying , Cheng Xiangpeng , Li Zhongqi , Zhang Yiming 
Published: February 2025

ABSTRACTWith the continuous expansion of wireless power transfer (WPT) in the field of electric vehicles (EVs) and automated guided vehicles (AGVs), there is a need for a wireless charger that can complete the charging of these two devices in a limited space. To fill the gap in this field, this paper proposes an integrated wireless transmitter (IWT) that is suitable for EV and AGV wireless charging under different frequencies, which can realize the radio energy transmission of two types of vehicles in one charging position. It can also tolerate different coupling structures in EV wireless charging, namely the unipolar (Q) and bipolar (DD) coils. The IWT is established by stacking the Q coil and the DD coil composed of two self‐decoupled poles, combined with circuit configuration topologies. An experimental prototype is established to verify the interoperability performance. The proposed WPT system can achieve interoperability with EV wireless charging of Q or DD receiving coils at 85 kHz and AGV wireless charging at 200 kHz.
Machine Learning and Spatio Temporal Analysis for Assessing Ecological Impacts of the Billion Tree Afforestation Project
Authors: Mehmood Kaleem , Anees Shoaib Ahmad , Muhammad Sultan , Shahzad Fahad , Liu Qijing , Khan Waseem Razzaq , Shrahili Mansour , Ansari Mohammad Javed , Dube Timothy 
Published: February 2025

ABSTRACTThis study evaluates the Billion Tree Afforestation Project (BTAP) in Pakistan's Khyber Pakhtunkhwa (KPK) province using remote sensing and machine learning. Applying Random Forest (RF) classification to Sentinel‐2 imagery, we observed an increase in tree cover from 25.02% in 2015 to 29.99% in 2023 and a decrease in barren land from 20.64% to 16.81%, with an accuracy above 85%. Hotspot and spatial clustering analyses revealed significant vegetation recovery, with high‐confidence hotspots rising from 36.76% to 42.56%. A predictive model for the Normalized Difference Vegetation Index (NDVI), supported by SHAP analysis, identified soil moisture and precipitation as primary drivers of vegetation growth, with the ANN model achieving an R2 of 0.8556 and an RMSE of 0.0607 on the testing dataset. These results demonstrate the effectiveness of integrating machine learning with remote sensing as a framework to support data‐driven afforestation efforts and inform sustainable environmental management practices.
Ecomorphological Convergence Following Niche Shifts in Montane Ground Beetles (Carabidae: Nebria)
Authors: Schat Jillian K. , Ehlert Elizabeth , Kavanaugh David H. , Dudko Roman Yu , Schoville Sean D. 
Published: February 2025

ABSTRACTA critical step toward uncovering generalizable patterns of phenotype‐niche relationships is understanding how functional traits have evolved as species occupy new habitats. Ecomorphological traits impact how organisms function in their environment and are predictive of habitat use and niche. Studying ecomorphological variation in the context of strong environmental filtering can provide opportunities to understand the role of convergent evolution in forming trait‐habitat use patterns. By integrating a molecular phylogeny, habitat use, and morphometrics, this study aimed to understand the role of ancestry and convergent evolution in ecomorphological trait evolution. This study examined these processes using an assemblage of 79 species in the ground beetle genus Nebria (Carabidae: Nebriini). Species in this genus are habitat specialists who occupy montane and alpine streambeds, talus, and snowfields in Holarctic mountain ranges (0–5000 m. above sea level). Morphological measurements, including pronotal ratio (widest point divided by the base), elytral length, elytral ratio (length divided by width), antennal scape length, and pronotal and elytral shape (Fourier decomposition), were used in this study, in conjunction with measurements of habitat use habitat where specimens were collected (1970‐2021). Morphological variation was examined in relation to habitat use and phylogenetic relatedness, and morphological trait evolution was tested for convergence. Ecomorphological traits are evolving slower than expected under a null model of Brownian motion evolution. Nebria species cluster in multivariate morphospace according to relatedness, but habitat use and relatedness together are the best predictors of morphological variation. There is evidence for convergence in riparian species based on morphologicy alone, and additional evidence for morphological convergence in riparian and alpine species when phylogenetic distance is considered. In species assemblages of Nebria, we found evidence of rapid diversification followed by a slow rate of ecomorphological evolution, with convergent evolution playing a significant role in shaping trait‐habitat use patterns and niche acquisition.
Artificial Attractants: Implications for Disease Management in Deer
Authors: Gritter Kelsey , Pybus Margo , Lewis Mark A. , Merrill Evelyn 
Published: February 2025

ABSTRACTChronic wasting disease (CWD) is a prion disease that infects cervid species by direct and environmental transmission and is invariably fatal. CWD spread can be promoted by the attraction of animals to “hotspots” such as hay bales and grain bags stored in fields and at farm sites. The density and location of hotspots may impact contact rates. We used an individual‐based movement model of mule deer (Odocoileus hemionus) to investigate the effects of density and configuration of hotspots (hereafter artificial attractants, AA) on contact rates at a constant density of 1 deer/km2 during winter. The model tracks when two deer from the same or different groups come into contact under 6 AA densities (0–1 AA/km2) and 6 AA configurations. We compared placing AA randomly versus clustered around farms, and removing them randomly versus biased by proximity to preferred habitat. Overall, the number of unique contacts per individual and the number of unique deer visiting an AA increased, and the number of AAs used by each deer decreased as AA density declined. Selectively removing field attractants near preferred habitat resulted in a larger increase in contacts per deer, with deer contacting more and different individuals, fewer deer using the remaining AA, and fewer visits per AA than random removal. There was a greater increase in contact rates when reducing AA density at farms by randomly removing all AA at a farm compared to randomly removing individual AA across farms. Deer responses to AA removal may not be as straightforward as originally believed. Deer contacts may increase, not decrease, with AA removal because deer are attracted to the remaining AA. Under moderate deer densities, AA removal may require a broad‐scale, “all or nothing” approach to prevent deer from concentrating at remaining AA, but concomitantly lowering deer density needs further assessment.
The Effectiveness of a Primary Care Diabetes Education and Self‐Management Program in Ireland: A 6‐Month Follow‐Up Study
Authors: Scannell Clodagh , O'Neill Tonya , Griffin Anne 
Published: February 2025

ABSTRACTAimsSelf‐management education is recognised as an essential element of comprehensive diabetes care. This study aims to assess the impact of the DESMOND (Diabetes Education and Self‐Management for Ongoing and Newly Diagnosed) structured diabetes self‐management education programme administered by a registered dietitian in a primary‐care setting on key clinical indicators (HbA1c, weight and BMI) in participants who returned for the locally developed 6‐month follow‐up session.MethodsA retrospective analysis was conducted of participants who attended the DESMOND 6‐h structured diabetes self‐management education programme and returned for the locally developed follow‐up programme during 2018 in the Midwest of Ireland. Paired sample t‐tests and McNemar chi‐square tests were used to assess any differences between baseline and 6 months post‐intervention.ResultsThere were 66 participants, mean age of 63 years. At follow‐up, HbA1c was reduced by 6.45 mmol/mol (standard deviation (SD): 15.02 mmol/mol, p = 0.006). The number of participants below the 53 mmol/mol cut‐off increased from 52% at baseline to 71% at follow‐up (p < 0.001). A mean weight reduction of 1.4 kg (SD: 4.4 kg, p = 0.21) was found at follow‐up. Those in the overweight BMI category decreased from 30.2% to 26.4%, a clinically significant result.ConclusionBetter glycaemic control and clinically significant improvements in BMI and weight were seen at 6 months among participants who attended the DESMOND program and returned for the locally developed follow‐up session. This supports the emerging evidence of the effectiveness of self‐management education for diabetes care. Further research is required to determine the optimal contact time and frequency of sessions required in order to sustain the observed improvement in clinical outcomes.
Dynamics of Worm Propagation Model in Complex Networks Considering Benign Worm and Link Prediction Approach
Authors: Asadi Elham , Hosseini Soodeh 
Published: February 2025

ABSTRACTIn this paper, the spread of worms as a type of malware is modeled with epidemic models. In the proposed model, we have considered the defense mechanism of the benign worm, link prediction, and quarantine of the infected nodes as methods to reduce the spread of the worm in complex networks. For the benign worm, the parameters of the ability to detect vulnerable nodes and the ability to immunization nodes have been considered, and we have investigated their role in reducing the spread of the worm in the network. The vulnerability list of the benign worm is considered as another characteristic of the benign worm and its role in the spread of the worm is analyzed. In the context of dynamic analysis of the model, we have obtained the initial equilibrium point and the basic reproduction ratio. Finally, the proposed model is evaluated on the Barabasi Albert artificial network and the standard data sets and compared with the SIR and SIRV models.
Toward Sustainable Perovskite Solar Cells: From Lead‐Free Materials to Environmental Concerns and Mitigation Strategies
Authors: Gao Shanshan , Bae Jeong‐Ju , Lee Da Seul , Yang Tae‐Youl , Shin Seong Sik 
Published: February 2025

ABSTRACTPerovskite solar cells (PSCs) have attracted considerable attention in the field of photovoltaics owing to their high power conversion efficiency (PCE), cost‐effective production methods, and versatile applications. However, the widespread use of lead (Pb)‐based materials in PSCs poses challenges related to their toxicity and environmental sustainability. This review explores recent advances in the development of Pb‐free perovskite materials, such as tin (Sn)‐based, germanium (Ge)‐based, and other B(IV) and B(III) cation alternatives, while assessing their electronic properties, stability, and performance‐enhancing strategies. Additionally, we discuss the use of green solvents and fabrication techniques to minimize their environmental impact. This review aims to guide future research toward safe, efficient, and environmentally sustainable PSC technologies, ensuring that the benefits of solar energy can be harnessed without compromising human health or the environment.
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Characterizing the Heat Transfer Performance of Contaminated Flame‐Resistant Fabrics
Authors: Tushar Shariful Islam , Mandal Sumit , Chowdhury Ishmam Zahin , Petrova Adriana , Boorady Lynn M. , Agnew Robert J. , Kubicki Michael , Park Haejun , Larson Preston 
Published: February 2025

ABSTRACTFor the safety of workers in the oil and gas field, flame‐resistant clothing is recommended to reduce the risks of skin burns and fatalities resulting from heat and fire hazards. However, flame‐resistant fabrics (FRFs) contaminated with flammable substances can compromise their flammability and heat transfer properties. Therefore, this study aims to evaluate the heat transfer performance (HTP) of the contaminated FRFs to improve workers' safety from burn injuries by understanding how contamination affects fabric thermal protection. The HTP in terms of second‐degree burn time was evaluated and characterized by exposing the fabrics to 84 kW/m2 mixed convective and radiant heat flux. The peak temperature and average heat release rate of the FRFs were also evaluated. Two levels of contamination, consisting of drilling mud and crude oil, were added to three FRFs: Meta‐aramid/cotton, meta‐aramid/para‐aramid, and para‐aramid/polybenzimidazole. The HTP of drilling mud‐contaminated fabrics increased, while the HTP of crude oil‐contaminated fabrics varied by fabric type and contamination level. This may be attributed to drilling mud's higher specific heat capacity and lower flammability than crude oil. Among the fabrics tested, meta‐aramid/cotton fabric showed the best HTP with higher second‐degree burn times of 9.63 s with drilling mud and 9.07 s with crude oil. The relationship among contamination level, fabric properties, and HTP was developed using a multiple linear regression statistical model. The fabric's properties, such as fabric weight and air permeability, significantly contributed to the HTP of the contaminated fabrics.
Transdiagnostic Connectome‐Based Prediction of Response Inhibition
Authors: Lv Qiuyu , Wang Xuanyi , Kang Ning , Wang Xiang , Lin Pan 
Published: February 2025

ABSTRACTResponse inhibition (RI) deficits are a core feature across diagnostic categories of mental disorders. However, it remains unclear whether the brain networks underlying different forms of RI deficits are disorder‐shared or disorder‐specific, and how they interact with aberrant brain connectivity across disorders. Connectome‐based predictive modeling (CPM) provides a novel approach for exploring the brain networks associated with RI abnormalities across diagnostic categories of mental disorders. Publicly available resting‐state functional magnetic resonance imaging data from individuals with schizophrenia (n = 47), bipolar disorder (n = 47), and attention‐deficit/hyperactivity disorder (n = 40), as well as healthy controls (n = 121), were utilized to construct whole‐brain network predictive models for different forms of RI (action cancellation and action restraint). The brain networks of different forms of RI were further compared with abnormal brain networks in the diagnostic groups. Action restraint and action cancellation exhibited both shared and distinct brain networks. There was a dissociation in the relationship between the brain networks underlying different forms of RI and the aberrant connectivity patterns observed across diagnostic categories. Our models successfully predicted action restraint performance across diagnostic categories, whereas the model failed to effectively predict action cancellation due to the influence of disease‐related aberrant connectivity on the brain networks underlying action cancellation. Nevertheless, the action cancellation model demonstrated generalizability to novel, healthy participants (n = 220) from an independent dataset. Our study clarifies the complex relationship between deficits in RI and the neuropathology of mental disorders and provides a foundation for more accurate cognitive assessment and targeted interventions. Our findings highlight the importance of refining RI constructs and emphasize the value of applying connectome methods to reveal cross‐diagnostic neural mechanisms.
Advancing Medical Research Through Artificial Intelligence: Progressive and Transformative Strategies: A Literature Review
Authors: Al‐Qudimat Ahmad R. , Fares Zainab E. , Elaarag Mai , Osman Maha , Al‐Zoubi Raed M. , Aboumarzouk Omar M. 
Published: February 2025

ABSTRACTBackground and AimsArtificial intelligence (AI) has become integral to medical research, impacting various aspects such as data analysis, writing assistance, and publishing. This paper explores the multifaceted influence of AI on the process of writing medical research papers, encompassing data analysis, ethical considerations, writing assistance, and publishing efficiency.MethodsThe review was conducted following the PRISMA guidelines; a comprehensive search was performed in Scopus, PubMed, EMBASE, and MEDLINE databases for research publications on artificial intelligence in medical research published up to October 2023.ResultsAI facilitates the writing process by generating drafts, offering grammar and style suggestions, and enhancing manuscript quality through advanced models like ChatGPT. Ethical concerns regarding content ownership and potential biases in AI‐generated content underscore the need for collaborative efforts among researchers, publishers, and AI creators to establish ethical standards. Moreover, AI significantly influences data analysis in healthcare, optimizing outcomes and patient care, particularly in fields such as obstetrics and gynecology and pharmaceutical research. The application of AI in publishing, ranging from peer review to manuscript quality control and journal matching, underscores its potential to streamline and enhance the entire research and publication process. Overall, while AI presents substantial benefits, ongoing research, and ethical guidelines are essential for its responsible integration into the evolving landscape of medical research and publishing.ConclusionThe integration of AI in medical research has revolutionized efficiency and innovation, impacting data analysis, writing assistance, publishing, and others. While AI tools offer significant benefits, ethical considerations such as biases and content ownership must be addressed. Ongoing research and collaborative efforts are crucial to ensure responsible and transparent AI implementation in the dynamic landscape of medical research and publishing.