bluuebunny/crossref_metadata_2025 huggingface dataset:
Advanced Soft Computing Techniques for Monthly Streamflow Prediction in Seasonal Rivers
Authors: Achite Mohammed , Katipoğlu Okan Mert , Kartal Veysi , Sarıgöl Metin , Jehanzaib Muhammad , Gül Enes
Published: January 2025

The rising incidence of droughts in specific global regions in recent years, primarily attributed to global warming, has markedly increased the demand for reliable and accurate streamflow estimation. Streamflow estimation is essential for the effective management and utilization of water resources, as well as for the design of hydraulic infrastructure. Furthermore, research on streamflow estimation has gained heightened importance because water is essential not only for the survival of all living organisms but also for determining the quality of life on Earth. In this study, advanced soft computing techniques, including long short-term memory (LSTM), convolutional neural network–recurrent neural network (CNN-RNN), and group method of data handling (GMDH) algorithms, were employed to forecast monthly streamflow time series at two different stations in the Wadi Mina basin. The performance of each technique was evaluated using statistical criteria such as mean square error (MSE), mean bias error (MBE), mean absolute error (MAE), and the correlation coefficient (R). The results of this study demonstrated that the GMDH algorithm produced the most accurate forecasts at the Sidi AEK Djillali station, with metrics of MSE: 0.132, MAE: 0.185, MBE: −0.008, and R: 0.636. Similarly, the CNN-RNN algorithm achieved the best performance at the Kef Mehboula station, with metrics of MSE: 0.298, MAE: 0.335, MBE: −0.018, and R: 0.597.
Research on Typhoon Prediction by Integrating Numerical Simulation and Deep Learning Methods
Authors: Lv Tianyi , Yu Huaming , Lin Liangshi , Tao Yijun , Qi Xin
Published: January 2025

Typhoons rank among the most destructive natural disasters, significantly affecting human activities and daily life. Atmospheric numerical model wind fields, which are widely utilized, often underestimate typhoon intensity. This study proposes a model for predicting typhoon maximum wind speeds using the Long Short-Term Memory (LSTM) neural network. The model predicts maximum wind speeds based on existing atmospheric numerical forecasts, constructs a parametric wind field model from these predictions, and integrates it with the numerical model wind fields to generate an LSTM-optimized wind field. The results show that the LSTM model accurately predicts typhoon maximum wind speeds, with the predicted extreme values closely aligning with actual observations and capturing the trends of maximum wind speed variations. Compared with the ERA5 typhoon maximum wind speed, the C of the LSTM model for predicting the typhoon maximum wind speed is improved from 0.801 to 0.859, and the RMSE and MAE are reduced by 58% and 64%, respectively. In the simulation of Typhoon DELTA (2020), the LSTM-optimized wind field exhibits substantially higher wind speed intensities in the central region of the typhoon compared to the ERA5 wind field, providing a more accurate representation of the intensity and structure of the typhoon.
Assessing the COVID-19 Lockdown Impact on Global Air Quality: A Transportation Perspective
Authors: Zheng Meina , Liu Feng , Wang Meichang
Published: January 2025

To address the COVID-19 pandemic, governments worldwide implemented mandatory restrictions. As an unintended consequence of these responses, significant air pollution reductions have been recorded across the world. We provide cross-national evidence on the causal impact of pandemic-induced lockdowns on air quality. Using daily air pollution data between 1 January and 31 December 2020, covering 596 major cities in 77 countries, we analyzed the data with a generalized difference-in-differences approach. The results show that lockdown restrictions reduced global concentrations of NO2 by 21~35%, PM10 by 14~26%, PM2.5 by 9~18%, CO by 6~16%, and SO2 by 5~16%, while the O3 concentrations increased by 15~29% under eight specific lockdown measures. Furthermore, a simultaneous equations model suggests that reductions in public and private mobility, measured by changes in public transportation and car ridership, partly explain the observed decreases in air pollution. These findings have significant implications for ongoing global efforts to mitigate air pollution and underscore the pivotal role of public transit in achieving this goal.
An Optimized NGS Workflow Defines Genetically Based Prognostic Categories for Patients with Uveal Melanoma
Authors: Massimino Michele , Tirrò Elena , Stella Stefania , Tomarchio Cristina , Di Bella Sebastiano , Vitale Silvia Rita , Conti Chiara , Puglisi Marialuisa , Di Crescenzo Rosa Maria , Varricchio Silvia , Merolla Francesco , Broggi Giuseppe , Martorana Federica , Turdo Alice , Gaggianesi Miriam , Manzella Livia , Russo Andrea , Stassi Giorgio , Caltabiano Rosario , Staibano Stefania , Vigneri Paolo
Published: January 2025

Background: Despite advances in uveal melanoma (UM) diagnosis and treatment, about 50% of patients develop distant metastases, thereby displaying poor overall survival. Molecular profiling has identified several genetic alterations that can stratify patients with UM into different risk categories. However, these genetic alterations are currently dispersed over multiple studies and several methodologies, emphasizing the need for a defined workflow that will allow standardized and reproducible molecular analyses. Methods: Following the findings published by “The Cancer Genome Atlas–UM” (TCGA-UM) study, we developed an NGS-based gene panel (called the UMpanel) that classifies mutation sets in four categories: initiating alterations (CYSLTR2, GNA11, GNAQ and PLCB4), prognostic alterations (BAP1, EIF1AX, SF3B1 and SRSF2), emergent biomarkers (CDKN2A, CENPE, FOXO1, HIF1A, RPL5 and TP53) and chromosomal abnormalities (imbalances in chromosomes 1, 3 and 8). Results: Employing commercial gene panels, reference mutated DNAs and Sanger sequencing, we performed a comparative analysis and found that our methodological approach successfully predicted survival with great specificity and sensitivity compared to the TCGA-UM cohort that was used as a validation group. Conclusions: Our results demonstrate that a reproducible NGS-based workflow translates into a reliable tool for the clinical stratification of patients with UM.
Cell Type Specific Suppression of Hyper-Recombination by Human RAD18 Is Linked to Proliferating Cell Nuclear Antigen K164 Ubiquitination
Authors: Rogers Colette B. , Leung Wendy , Baxley Ryan M. , Kram Rachel E. , Wang Liangjun , Buytendorp Joseph P. , Le Khoi , Largaespada David A. , Hendrickson Eric A. , Bielinsky Anja-Katrin
Published: January 2025

RAD18 is a conserved eukaryotic E3 ubiquitin ligase that promotes genome stability through multiple pathways. One of these is gap-filling DNA synthesis at active replication forks and in post-replicative DNA. RAD18 also regulates homologous recombination (HR) repair of DNA breaks; however, the current literature describing the contribution of RAD18 to HR in mammalian systems has not reached a consensus. To investigate this, we examined three independent RAD18-null human cell lines. Our analyses found that loss of RAD18 in HCT116, but neither hTERT RPE-1 nor DLD1 cell lines, resulted in elevated sister chromatid exchange, gene conversion, and gene targeting, i.e., HCT116 mutants were hyper-recombinogenic (hyper-rec). Interestingly, these phenotypes were linked to RAD18’s role in PCNA K164 ubiquitination, as HCT116 PCNAK164R/+ mutants were also hyper-rec, consistent with previous studies in rad18−/− and pcnaK164R avian DT40 cells. Importantly, the knockdown of UBC9 to prevent PCNA K164 SUMOylation did not affect hyper-recombination, strengthening the link between increased recombination and RAD18-catalyzed PCNA K164 ubiquitination, but not K164 SUMOylation. We propose that the hierarchy of post-replicative repair and HR, intrinsic to each cell type, dictates whether RAD18 is required for suppression of hyper-recombination and that this function is linked to PCNA K164 ubiquitination.
Toxicity Associated with Pembrolizumab Monotherapy in Patients with Gastrointestinal Cancers: A Systematic Review of Clinical Trials
Authors: Naleid Nikolas , Mahipal Amit , Chakrabarti Sakti
Published: January 2025

Background/Objectives: Pembrolizumab, an immune checkpoint inhibitor targeting programmed death 1 (PD-1), is a widely employed therapy for various gastrointestinal (GI) cancers. We conducted a systematic review of clinical trials investigating pembrolizumab monotherapy in GI cancer patients to assess the spectrum and incidence of immune-related adverse events (irAEs) associated with pembrolizumab. Methods: A comprehensive search of PubMed/MEDLINE was performed to identify clinical trials investigating pembrolizumab monotherapy in GI cancer patients. Primary endpoints included the incidence of grade 3 or higher irAEs and the rate of treatment discontinuation due to irAEs. Secondary endpoints encompassed the incidence of any-grade irAEs, as well as specific irAEs. Results: Data extraction and analysis were performed on 25 articles. The analysis included 3101 patients with a median age of 62 years (range 53–68), with 30.2% being female. Tumor types encompassed were colorectal (12%), esophagogastric (46%), hepatocellular carcinoma (24%), and other GI tumor types (18%). The rate of treatment discontinuation due to irAEs was 6.8%. The most prevalent grade 3 or higher irAEs were hepatitis (3.6%), pneumonitis (0.8%), and colitis (0.7%). Death attributed to irAEs was infrequent (0.9%). Conclusions: In patients with GI cancers treated with pembrolizumab monotherapy, severe toxicities are infrequent, and irAEs leading to treatment discontinuation or death are uncommon.
miRNAs and Hematological Markers in Non-Alcoholic Fatty Liver Disease—A New Diagnostic Path?
Authors: Michalak Agata , Guz Małgorzata , Kozicka Joanna , Cybulski Marek , Jeleniewicz Witold , Telejko Ilona , Szczygieł Karolina , Tywanek Ewa , Cichoż-Lach Halina
Published: January 2025

Background: Asymptomatic liver steatosis constitutes an emerging issue worldwide. Therefore, we decided to explore relationships between selected types of microRNAs (miRNAs), serological markers of liver fibrosis and hematological parameters in the course of non-alcoholic fatty liver disease (NAFLD). Methods: Two hundred and seven persons were included in the survey: 97 with NAFLD and 110 healthy controls. Serological concentrations of miR-126-3p, miR-197-3p, and miR-1-3p were measured in all participants. Direct indices of liver fibrosis [procollagen I carboxyterminal propeptide (PICP), procollagen III aminoterminal propeptide (PIIINP), platelet-derived growth factor AB (PDGF-AB), transforming growth factor-α (TGF-α) and laminin] together with indirect markers (AAR, APRI, FIB-4 and GPR) were also evaluated. The assessment of hematological parameters concerned: mean platelet volume (MPV), platelet distribution width (PDW), plateletcrit (PCT), red blood cell distribution width (RDW), MPV to platelet (PLT) ratio (MPR), RDW to PLT ratio (RPR), neutrophil to lymphocyte (LYM) ratio (NLR), PLT to LYM ratio (PLR) and RDW to LYM ratio (RLR). Additionally, the NAFLD fibrosis score and BARD score were applied. Results: The concentration of miR-126-3p and miR-1-3p was higher, and miR-197-3p was lower in the NAFLD group (p < 0.0001). miR-197-3p correlated notably with hematological indices: negatively with PDW (p < 0.05) and positively with PLR (p < 0.05). Conclusions: Significant correlations between miRNA molecules and hematological markers in the course of NAFLD indicate inflammation as a potential background and create new possibilities for a diagnostic approach.
Pharmacokinetics of Hydrogen During Hydrogen-Saturated Saline Infusion in Pigs
Authors: Shibuya Masaki , Fujinaka Masafumi , Yonezawa Mako , Nishimura Natsumi , Uchinoumi Hitoshi , Sunahara Hiroshi , Tani Kenji , Kobayashi Eiji , Sano Motoaki
Published: January 2025

Background: Hydrogen gas (H2) has been shown to be effective in the treatment of various clinical conditions, from acute illnesses to chronic illnesses. However, its clinical indications and the corresponding appropriate hydrogen delivery methods have yet to be determined. This is due to the fact that the pharmacokinetics and pharmacodynamics of hydrogen in each delivery method have not been experimentally proven. Here, we verified the pharmacokinetics of hydrogen after the infusion of hydrogen-saturated saline. Methods: Hydrogen-saturated saline was prepared and checked for sterility and component specifications. Hydrogen-saturated saline was administered intravenously (125 mL/h) through the left internal jugular vein of pigs, and the blood hydrogen concentration was measured over time. Results: It was confirmed that hydrogen can be safely mixed under pressure into intravenous solutions (pharmaceutical products) without the contamination of foreign substances by using a needle-less vial access cannula. No change in the PH or composition of the solution was observed due to hydrogen filling. The hydrogen concentrations of blood samples collected from the left internal jugular vein 3 cm to the heart from the tip of the infusion line were 6.4 (30 min), 4.7 (60 min), 4.9 (90 min), and 5.3 (120 min) ppb w/w, respectively. The hydrogen concentrations of blood samples collected from the right atrium were 0.7 (30 min), 0.5 (60 min), 0.7 (90 min), and 0.7 (120 min) ppb, respectively. The hydrogen concentration of blood samples collected from the right internal carotid artery were 0.1 (pre), 0.2 (30 min), 0.3 (60 min), 0.0 (90 min), and 0.0 (120 min) ppb w/w, respectively. Conclusions: We confirmed that hydrogen could be safely pressurized and filled into intravenous (pharmaceutical) solution without contamination by foreign objects using a needle-free vial access cannula. When saturated hydrogen saline was dripped intravenously, almost all of the hydrogen was expelled during its passage through the lungs and could not be supplied to the arterial side.
Evaluation of Individual Cardiovascular Risk in Pre-Dialysis CKD Patients by Using the Ratio of Calcium–Phosphorus Product to Estimated Glomerular Filtration Rate (Ca × P/eGFR)
Authors: Kostov Krasimir , Simeonova Tatyana , Ignatov Borislav , Eftimova Tsvetelina
Published: January 2025

Background: Chronic kidney disease (CKD) patients have an increased risk of cardiovascular disease (CVD), necessitating effective risk assessment methods. This study evaluates the calcium–phosphorus product (Ca × P) to estimated glomerular filtration rate (Ca × P/eGFR) ratio as a potential biomarker for predicting CV risk in pre-dialysis CKD patients. Methods: Eighty-four CKD patients in stages G1–G4, according to the KDIGO criteria, were classified into CVD (n = 43) and non-CVD (n = 41) groups. Biochemical parameters, including serum creatinine (SCr), blood urea nitrogen (BUN), calcium (Ca), inorganic phosphate (Pi), parathyroid hormone (PTH), alkaline phosphatase (ALP), Ca × P, eGFR, and the Ca × P/eGFR ratio, were measured and calculated. Statistical analyses were performed to identify predictors of CV risk and evaluate the diagnostic reliability of the Ca × P/eGFR ratio for predicting the risk. Results: Significant differences were observed in SCr, BUN, eGFR (p < 0.001), and the Ca × P/eGFR ratio (p = 0.007) between the groups. Regression analysis indicated the Ca × P/eGFR ratio as a significant CVD risk predictor (p = 0.012, OR = 1.206, 95% CI: 1.042–1.395). Receiver Operating Characteristic (ROC) curve analysis revealed an AUC of 0.751 (p < 0.001, 95% CI: 0.645–0.857), with a sensitivity and specificity of the method of 74.4% and 70.7%, respectively. Significant correlations were found between the Ca × P/eGFR ratio and SCr, BUN, UA, Ca, Pi, PTH, and ALP. Conclusions: The Ca × P/eGFR ratio may serve as a significant predictor of CVD risk in pre-dialysis CKD patients, suggesting that its integration into routine evaluations could enhance CV risk stratification and management.
A Biopsychosocial Overview of Speech Disorders: Neuroanatomical, Genetic, and Environmental Insights
Authors: Jaishankar Diya , Raghuram Tanvi , Raju Bhuvanesh Kumar , Swarna Divyanka , Parekh Shriya , Chirmule Narendra , Gujar Vikramsingh
Published: January 2025

Speech disorders encompass a complex interplay of neuroanatomical, genetic, and environmental factors affecting individuals’ communication ability. This review synthesizes current insights into the neuroanatomy, genetic underpinnings, and environmental influences contributing to speech disorders. Neuroanatomical structures, such as Broca’s area, Wernicke’s area, the arcuate fasciculus, and basal ganglia, along with their connectivity, play critical roles in speech production, comprehension, and motor coordination. Advances in the understanding of intricate brain networks involved in language offer insights into typical speech development and the pathophysiology of speech disorders. Genetic studies have identified key genes involved in neural migration and synaptic connectivity, further elucidating the role of genetic mutations in speech disorders, such as stuttering and speech sound disorders. Beyond the biological mechanisms, this review explores the profound impact of psychological factors, including anxiety, depression, and neurodevelopmental conditions, on individuals with speech disorders. Psychosocial comorbidities often exacerbate speech disorders, complicating diagnosis and treatment and underscoring the need for a holistic approach to managing these conditions. Future directions point toward leveraging genetic testing, digital technologies, and personalized therapies, alongside addressing the psychosocial dimensions, to improve outcomes for individuals with speech disorders. This comprehensive overview aims to inform future research and therapeutic advancements, particularly in treating fluency disorders like stuttering.
Natural Cyclic Peptides: Synthetic Strategies and Biomedical Applications
Authors: Buchanan Devan , Mori Shogo , Chadli Ahmed , Panda Siva S.
Published: January 2025

Natural cyclic peptides, a diverse class of bioactive compounds, have been isolated from various natural sources and are renowned for their extensive structural variability and broad spectrum of medicinal properties. Over 40 cyclic peptides or their derivatives are currently approved as medicines, underscoring their significant therapeutic potential. These compounds are employed in diverse roles, including antibiotics, antifungals, antiparasitics, immune modulators, and anti-inflammatory agents. Their unique ability to combine high specificity with desirable pharmacokinetic properties makes them valuable tools in addressing unmet medical needs, such as combating drug-resistant pathogens and targeting challenging biological pathways. Due to the typically low concentrations of cyclic peptides in nature, effective synthetic strategies are indispensable for their acquisition, characterization, and biological evaluation. Cyclization, a critical step in their synthesis, enhances metabolic stability, bioavailability, and receptor binding affinity. Advances in synthetic methodologies—such as solid-phase peptide synthesis (SPPS), chemoenzymatic approaches, and orthogonal protection strategies—have transformed cyclic peptide production, enabling greater structural complexity and precision. This review compiles recent progress in the total synthesis and biological evaluation of natural cyclic peptides from 2017 onward, categorized by cyclization strategies: head-to-tail; head-to-side-chain; tail-to-side-chain; and side-chain-to-side-chain strategies. Each account includes retrosynthetic analyses, synthetic advancements, and biological data to illustrate their therapeutic relevance and innovative methodologies. Looking ahead, the future of cyclic peptides in drug discovery is bright. Emerging trends, including integrating computational tools for rational design, novel cyclization techniques to improve pharmacokinetic profiles, and interdisciplinary collaboration among chemists, biologists, and computational scientists, promise to expand the scope of cyclic peptide-based therapeutics. These advancements can potentially address complex diseases and advance the broader field of biological drug development.
Palm Tocotrienol Activates the Wnt3a/β-Catenin Signaling Pathway, Protecting MC3T3-E1 Osteoblasts from Cellular Damage Caused by Dexamethasone and Promoting Bone Formation
Authors: Abdullah Sani Norfarahin , Kamaruddin Nur Aqilah , Soelaiman Ima Nirwana , Pang Kok-Lun , Chin Kok-Yong , Ramli Elvy Suhana Mohd
Published: January 2025

Background and aim: Prolonged glucocorticoid (GC) treatment increases oxidative stress, triggers apoptosis of osteoblasts, and contributes to osteoporosis. Tocotrienol, as an antioxidant, could protect the osteoblasts and preserve bone quality under glucocorticoid treatment. From this study, we aimed to determine the effects of tocotrienol on MC3T3-E1 murine pre-osteoblastic cells treated with GC. Methods: MC3T3-E1 cells were exposed to dexamethasone (150 µM), with or without palm tocotrienol (PTT; 0.25, 0.5, and 1 µg/mL). Cell viability was measured by the MTS assay. Alizarin Red staining was performed to detect calcium deposits. Cellular alkaline phosphatase activity was measured to evaluate osteogenic activity. The expression of osteoblastic differentiation markers was measured by an enzyme-linked immunoassay. Results: Enhanced matrix mineralization was observed in the cells treated with 0.5 µg/mL PTT, especially on day 18 (p < 0.05). The expression of Wnt3a, β-catenin, collagen 1α1, alkaline phosphatase, osteocalcin, low-density lipoprotein receptor-related protein 6, and runt-related transcription factor-2 were significantly increased in the PTT-treated groups compared to the vehicle control group, especially at 0.5 µg/mL of PTT (p < 0.05) and on day 6 of treatment. Conclusions: PTT maintains the osteogenic activity of the dexamethasone-treated osteoblasts by promoting their differentiation.
Potential of Zinc Oxide Nanostructures in Biosensor Application
Authors: Maafa Ibrahim M.
Published: January 2025

The burgeoning field of biosensors has seen significant advancements with the induction of zinc oxide (ZnO) nanostructures, because of their unique structural, electrical, and optical properties. ZnO nanostructures provide numerous benefits for biosensor applications. Their superior electron mobility enables effective electron transfer between the bioreceptor and transducer, enhancing sensitivity and reducing detection limits. Furthermore, ZnO’s biocompatibility and non-toxicity make it ideal for in vivo applications, reducing the chances of adverse biological responses. This review paper explores the prospects of ZnO nanostructures in the development of biosensors, focusing on their morphological and structural characteristics. Various synthesis techniques, that include sol-gel, sputtering, and chemical vapor deposition, were successfully employed to prepare different ZnO nanostructures, like nanorods, nanotubes, and nanowires. The various findings in this field underscore the efficacy of ZnO nanostructures in enhancing the specificity and sensitivity of biosensors, presenting a promising avenue for the advancement of point-of-care diagnostic devices.
Physical Properties, Chemical Structure, and Microstructure of Thermoplastic Polyurethane Recycled Material-Modified Asphalt
Authors: Yang Peng , Cong Peiliang , Hao Hongjie , Xiong Pengfei
Published: January 2025

Firstly, thermoplastic polyurethane recycled material (TPRM) particles were used to prepare modified asphalt. Then, the modified asphalt’s physical properties were investigated. The results show that the TPRM particles improved its high-temperature performance, low-temperature crack resistance, and shear behavior due to its increased cohesion and low-temperature fracture energy levels. Thermal susceptibility was affected by the degree of swelling and dissolution of the TPRM particles, the composition of the asphalt, and the interface effect between the asphalt molecules and both the regular and slender–irregular TPRM particles. The TPRM particles swelled and dissolved after absorbing the light components of asphalt. Changes in the shearing temperature and time made the TPRM particles swell and dissolve more than changes in the activation temperature and time. An increase in the shearing/activation temperature and time increased the hydrogen bond content in the modified asphalt due to the rearrangement of the polyurethane’s molecular structure and the hydrogen bonds formed by the asphaltene and polyurethane molecules. Slender–irregular TPRM and “sea–island” and hilly and gulley structures were found in the modified asphalt matrix.
Research on Flexural Performance of Basalt Fiber-Reinforced Steel–Expanded Polystyrene Foam Concrete Composite Wall Panels
Authors: Liu Fang , Zhao Long , Yuan Longxin , Wu Gang , Zheng Ran , Mu Yusong
Published: January 2025

This paper presents a novel design of prefabricated steel–EPS foam concrete composite wall panels, which can solve issues such as long curing times, decreased impermeability and durability, easy corrosion of steel reinforcement, and difficult construction under the cold climate conditions in Northeast China. A parametric analysis of the composite wallboard was carried out using the finite-element analysis software ABAQUS 6.12. In-depth exploration was conducted on the contributions of parameters such as the density of foam concrete, the strength of cold-formed thin-walled C-section steel, and the cross-sectional height of cold-formed thin-walled C-section steel compared to the overall flexural bearing capacity of the composite wallboard as well as the impacts of these parameters on the failure modes. The mechanical properties of the composite wallboard were verified through four-point bending tests. The bearing capacity of this composite wallboard can reach up to 100.58 kN at most, and its flexural bearing capacity can reach 30.44 kN·m. Meanwhile, its ductility coefficient of 2.9 is also within the optimal range. The research results confirm the superior mechanical properties of the designed composite wallboard, providing beneficial references for the research on similar composite material structures.
Assessing and Enhancing Green Quantity in the Open Spaces of High-Density Cities: A Comparative Study of the Macau Peninsula and Monaco
Authors: Li Jitai , Lin Fan , Chen Yile , Yang Shuai
Published: January 2025

Green open space in high-density cities has positive significance in terms of improving the quality of the living environment and solving problems such as “urban diseases”. Taking the high-density urban districts of the Macau Peninsula and Monaco as examples, this study divides the planning index of open space green quantity into two dimensions: the blue-green spaces occupancy rate (BGOR) within urban land areas and the blue-green spaces visibility rate (BGVR) of the main streetscape. Using satellite remote-sensing maps, GIS databases, and street-view images, this study evaluates the current green quantity in both regions and compares them to identify best practices. This study aims to assess and enhance the green quantity found in the open spaces of high-density cities, using the Macau Peninsula and Monaco as case studies. The primary research questions are as follows: (1) How can the green quantity in open spaces be effectively measured in high-density urban environments? (2) What planning strategies can be implemented to increase the green quantity and improve the urban living environment in such areas? Therefore, this study proposes planning strategies such as three-dimensional greening, converting grey spaces to green spaces, and implementing policies to encourage public participation in greening efforts. These strategies aim to enhance the green quantity in open spaces, thereby improving the urban living environment in high-density cities like Macau and providing a reference for similar urban areas in the world.
Exploration of Resident Satisfaction and Willingness in the Renovation of a Typical Old Neighborhood
Authors: Peng Wenjun , Huang Yanyan , Li Changquan , Wang Yilin
Published: January 2025

The reconstruction of old communities makes an outstanding contribution to, and holds practical significance for, livelihoods and ecological civilization in the urban renewal context. Clarifying the renovation intentions of residents is conducive to the effective implementation of reconstruction projects. This paper takes a typical old neighborhood in Wuhan as an example to survey residents’ living satisfaction and renovation intention. Multiple linear regression analysis, factor analysis, and correlation analysis were used to quantitatively screen, judge, and process sample data. The results show that residents’ living satisfaction and willingness to renovate were different under the dimensions of resident age and property rights, respectively. Most residents were dissatisfied with the living state of the neighborhood. Residents over 61 years old or those who held real estate certificates had a strong willingness to renovate and tended to accept a unified management manner after the renovation of the old neighborhood. Moreover, resident satisfaction with the internal road traffic, infrastructure, and building state significantly affected the residents’ overall satisfaction with the living environment in the old neighborhood, which should be given more attention to improve the residents’ willingness to support the renovation items. Furthermore, it was found that resident satisfaction with building conditions, infrastructure, internal road traffic, and public environment significantly impacted their agreement with the renovation in the old neighborhood. This investigation could provide a basis and guidance for the reconstruction and design of old communities.
Multi-Scale Building Load Forecasting Without Relying on Weather Forecast Data: A Temporal Convolutional Network, Long Short-Term Memory Network, and Self-Attention Mechanism Approach
Authors: Yang Lanqian , Guo Jinmin , Tian Huili , Liu Min , Huang Chang , Cai Yang
Published: January 2025

Accurate load forecasting is of vital importance for improving the energy utilization efficiency and economic profitability of intelligent buildings. However, load forecasting is restricted in the popularization and application of conventional load forecasting techniques due to the great difficulty in obtaining numerical weather prediction data at the hourly level and the requirement to conduct predictions on multiple time scales. Under the condition of lacking meteorological forecast data, this paper proposes to utilize a temporal convolutional network (TCN) to extract the coupled spatial features among multivariate loads. The reconstructed features are then input into the long short-term memory (LSTM) neural network to achieve the extraction of load time features. Subsequently, the self-attention mechanism is employed to strengthen the model’s ability to extract feature information. Finally, load forecasting is carried out through a fully connected network, and a multi-time scale prediction model for building multivariate loads based on TCN–LSTM–self-attention is constructed. Taking a hospital building as an example, this paper predicts the cooling, heating, and electrical loads of the hospital for the next 1 h, 1 day, and 1 week. The experimental results show that on multiple time scales, the TCN–LSTM–self-attention prediction model proposed in this paper is more accurate than the LSTM, CNN-LSTM, and TCN-LSTM models. Especially in the task of predicting cooling, heating, and electrical loads on a 1-week scale, the model proposed in this paper achieves improvements of 16.58%, 6.77%, and 3.87%, respectively, in the RMSE indicator compared with the TCN-LSTM model.
Treatment Patterns and Outcomes in Patients with Advanced Biliary Tract Cancers Treated with Gemcitabine-Based Chemotherapy: A Retrospective Study
Authors: Dayyani Farshid , Stirnadel-Farrant Heide A. , Hu Jenny , Lin Yian , Kebede Nehemiah , Valerio Stephen J. , Ahn Daniel H.
Published: January 2025

Background: Historically, the standard of care for advanced biliary tract cancers (aBTCs) was gemcitabine plus cisplatin (GemCis). Immunotherapy plus GemCis is now recommended as a first-line treatment for aBTCs. Whether patients can tolerate eight cycles of GemCis in clinical practice, as per the Advanced Biliary Cancer (ABC)-02 study, remains to be assessed. We performed a retrospective observational cohort study to assess real-world treatment patterns and overall survival (OS) in patients with de novo or recurrent aBTCs treated with first-line gemcitabine-based chemotherapy in the United States. Methods: This retrospective observational cohort study used Optum’s de-identified Market Clarity Data (Market Clarity). Adults diagnosed with de novo or recurrent aBTCs in the United States who began first-line gemcitabine-based chemotherapy from January 2016–March 2022 were identified and followed from index until death, the end of continuous enrolment, or the end of study period. Treatment patterns and OS were assessed. Results: Overall, 559 patients were included (de novo, n = 462; recurrent, n = 97). GemCis was the most common first-line therapy received (de novo: 73.8%; recurrent: 57.7%). Most patients received approximately five cycles of GemCis; median (95% CI) time to discontinuation was 4.6 (4.3–5.1) months. Most patients died over the follow-up period (de novo: 70.3%; recurrent: 62.9%). Median OS (95% CI) was 14.2 (12.1–16.1) months (de novo) and 18.5 (15.6–26.9) months (recurrent). Conclusions: GemCis was the most common first-line therapy received during the study period; most patients were unable to receive eight cycles of GemCis. Survival was limited over the follow-up period, highlighting the need for new treatments for aBTCs. Future studies are warranted to understand the real-world impact of first-line immunotherapy plus GemCis for patients with aBTCs.
Lung Cancers Associated with Cystic Airspaces
Authors: Valsecchi Clara , Petrella Francesco , Freguia Stefania , Frattini Milo , Argentieri Gianluca , Puligheddu Carla , Treglia Giorgio , Rizzo Stefania
Published: January 2025

Lung cancer, the second most common malignancy in both men and women, poses a significant health burden. Early diagnosis remains pivotal in reducing lung cancer mortality. Given the escalating number of computed tomography (CT) examinations in both outpatient and inpatient settings, radiologists play a crucial role in identifying early-stage pulmonary cancers, particularly non-nodular cancers. Screening programs have been instituted to achieve this goal, and they have raised attention within the scientific community to lung cancers associated with cystic airspaces. These cancers, although they have been known for at least a decade, remain understudied. Limited investigations with small sample sizes have estimated their prevalence and explored their radiological and pathological features. Lung cancers associated with cystic airspaces exhibit varying complexities within their cystic components and demonstrate suspicious changes over time. Adenocarcinoma is the predominant histological type, often with a peripheral location. Differential diagnosis on CT scans includes inflammatory processes or emphysema-related changes. Unfortunately, prospective studies specifically analyzing the prevalence of cystic airspace-associated lung cancers are lacking. However, it is estimated that they constitute approximately one-fourth of delayed radiological diagnoses. Increased awareness among radiologists could lead to more timely identification and potentially reduce lung cancer mortality in a cost-effective manner.
Comparison of Outcomes of Haploidentical Peripheral Blood Stem Cell Transplantation with Post-Transplant Cyclophosphamide in Older Versus Younger Patients
Authors: Adoncecchi Giacomo , Kumar Ambuj , Mogili Krishnakar , Faramand Rawan , Liu Hien , Khimani Farhad , Mishra Asmita , Nieder Michael , Nishihori Taiga , Hansen Doris , Jain Michael , Lazaryan Aleksandr , Perez Lia , Pidala Joseph , Locke Frederick , Anasetti Claudio , Bejanyan Nelli , Elmariah Hany
Published: January 2025

Background: Previous studies have shown that allogeneic peripheral blood stem cell transplantation (PBSCT) from an HLA haploidentical (haplo) donor followed by graft-versus-host disease (GVHD) prophylaxis with post-transplant cyclophosphamide (PTCy) results in lower relapse rates and improved DFS when compared to haplo bone marrow transplant (BMT) with PTCy. However, PBSCT leads to higher rates of GVHD. It is unknown whether the benefits of haplo PBSCT may be nullified in older patients (>60 years) by a higher susceptibility to GVHD and transplant related toxicity. Thus, we sought to determine if older patients receiving haplo PBSCT with PTCy experience significantly worse outcomes than younger patients. Methods: We evaluated 121 adult patients with hematologic malignancies treated at the Moffitt Cancer Center with allogeneic haplo PBSCT followed by PTCy and compared outcomes of patients ≥60 years (n = 55) versus patients <60 years (n = 66). Results: The cumulative incidence of non-relapse mortality (NRM) from the competing risk regression analysis was worse for the older patient group (SHR = 4.05, 95% CI: 1.43–11.47, p = 0.008). However, there was no significant difference between groups in graft-versus-host disease (GVHD), relapse, disease-free survival (DFS), or overall survival (OS). Instead, hematopoietic comorbidity index (HCT-CI) ≥ 3 was associated with worse DFS (HR = 1.87, 95% CI: 1.04–3.34, p = 0.035) and OS (HR = 1.98, 95% CI: 1.03–3.84, p-value = 0.042). Subgroup analysis of patients ≥60 years showed a trend toward improved 2-year OS with fludarabine/cyclophosphamide/total body irradiation (Flu/Cy/TBI) versus fludarabine/busulfan: 71% versus 53% (HR = 0.47, p = 0.121). In patients over 70 years (n = 14), NRM was 8% and OS was 76% at 1 year. Conclusion: Given similar OS and DFS between patients aged >60 years and those <60, haplo PBSCT with PTCy appears to be an appropriate transplant platform for older patients.
Cancer Therapy-Induced Cardiotoxicity: Results of the Analysis of the UK DEFINE Database
Authors: Chan Stefanie Ho Yi , Fitzpatrick Raymond W. , Layton Deborah , Webley Sherael , Salek Sam
Published: January 2025

Background: The accelerated development of novel cancer therapies necessitates a thorough understanding of the associated cardiotoxicity profiles, due to their significant implications for the long-term health and quality of life of cancer survivors. Objectives: The aim of this study was to determine the association between cardiotoxicity and non-small cell lung cancer (NSCLC) treatments using a hospital medicines usage database in England. Methods: An observational study based on a retrospective design using real-world data from the UK DEFINE database was performed. Monthly secondary data of 40 shortlisted drugs from April 2017 to July 2022 were extracted. Results: The cardiology drug that was associated with most oncology drugs was apixaban. Atezolizumab, bevacizumab, nintedanib, osimertinib, paclitaxel, pembrolizumab, gemcitabine and vincristine were all mostly associated with apixaban, which indicated association with atrial fibrillation. Afatinib, erlotinib and methotrexate were mostly associated with atenolol, hence suggesting the association with ischaemia or hypertension. Docetaxel and epirubicin were associated with verapamil, which indicated association with arrhythmia or hypertension. Conclusions: From the correlation and regression analyses, it can be concluded that hypertension was the most associated cardiovascular disease with the 20 shortlisted oncology drugs. The findings of this study have provided a better understanding of the association between each NSCLC–Cardio drug pair.
Deep Learning-Based Glioma Segmentation of 2D Intraoperative Ultrasound Images: A Multicenter Study Using the Brain Tumor Intraoperative Ultrasound Database (BraTioUS)
Authors: Cepeda Santiago , Esteban-Sinovas Olga , Singh Vikas , Shetty Prakash , Moiyadi Aliasgar , Dixon Luke , Weld Alistair , Anichini Giulio , Giannarou Stamatia , Camp Sophie , Zemmoura Ilyess , Giammalva Giuseppe Roberto , Del Bene Massimiliano , Barbotti Arianna , DiMeco Francesco , West Timothy Richard , Nahed Brian Vala , Romero Roberto , Arrese Ignacio , Hornero Roberto , Sarabia Rosario
Published: January 2025

Background: Intraoperative ultrasound (ioUS) provides real-time imaging during neurosurgical procedures, with advantages such as portability and cost-effectiveness. Accurate tumor segmentation has the potential to substantially enhance the interpretability of ioUS images; however, its implementation is limited by persistent challenges, including noise, artifacts, and anatomical variability. This study aims to develop a convolutional neural network (CNN) model for glioma segmentation in ioUS images via a multicenter dataset. Methods: We retrospectively collected data from the BraTioUS and ReMIND datasets, including histologically confirmed gliomas with high-quality B-mode images. For each patient, the tumor was manually segmented on the 2D slice with its largest diameter. A CNN was trained using the nnU-Net framework. The dataset was stratified by center and divided into training (70%) and testing (30%) subsets, with external validation performed on two independent cohorts: the RESECT-SEG database and the Imperial College NHS Trust London cohort. Performance was evaluated using metrics such as the Dice similarity coefficient (DSC), average symmetric surface distance (ASSD), and 95th percentile Hausdorff distance (HD95). Results: The training cohort consisted of 197 subjects, 56 of whom were in the hold-out testing set and 53 in the external validation cohort. In the hold-out testing set, the model achieved a median DSC of 0.90, ASSD of 8.51, and HD95 of 29.08. On external validation, the model achieved a DSC of 0.65, ASSD of 14.14, and HD95 of 44.02 on the RESECT-SEG database and a DSC of 0.93, ASSD of 8.58, and HD95 of 28.81 on the Imperial-NHS cohort. Conclusions: This study supports the feasibility of CNN-based glioma segmentation in ioUS across multiple centers. Future work should enhance segmentation detail and explore real-time clinical implementation, potentially expanding ioUS’s role in neurosurgical resection.
Computed Tomography-Image-Based Glioma Grading Using Radiomics and Machine Learning: A Proof-of-Principle Study
Authors: Bilgin Melike , Bilgin Sabriye Sennur , Akkurt Burak Han , Heindel Walter , Mannil Manoj , Musigmann Manfred
Published: January 2025

Background/Objectives: In recent years, numerous studies have been published on determining the WHO grade of central nervous system (CNS) tumors using machine learning algorithms. These studies are usually based on magnetic resonance imaging (MRI) and sometimes also on positron emission tomography (PET) images. To date, however, there are virtually no corresponding studies based on routinely generated computed tomography (CT) images. The aim of our proof-of-concept study is to investigate whether machine learning-based tumor diagnosis is also possible using CT images. Methods: We investigate the differentiability of histologically confirmed low-grade and high-grade gliomas. Three conventional machine learning algorithms and a neural net are tested. In addition, we analyze which of the common imaging methods (MRI or CT) appears to be best suited for the diagnostic question under investigation when machine learning algorithms are used. For this purpose, we compare our results based on CT images with numerous studies based on MRI scans. Results: Our best-performing model includes six features and is obtained using univariate analysis for feature preselection and a Naive Bayes approach for model construction. Using independent test data, this model yields a mean AUC of 0.903, a mean accuracy of 0.839, a mean sensitivity of 0.807 and a mean specificity of 0.864. Conclusions: Our results demonstrate that low-grade and high-grade gliomas can be differentiated with high accuracy using machine learning algorithms, not only based on the usual MRI scans, but also based on CT images. In the future, such CT-image-based models can help to further accelerate brain tumor diagnostics and to reduce the number of necessary biopsies.
Impact of Hyaluronic Acid on the Cutaneous T-Cell Lymphoma Microenvironment: A Novel Anti-Tumor Mechanism of Bexarotene
Authors: Ikawa Tetsuya , Yamazaki Emi , Amagai Ryo , Kambayashi Yumi , Sekine Mana , Takahashi Takuya , Asano Yoshihide , Fujimura Taku
Published: January 2025

Background: Cutaneous T-cell lymphoma (CTCL) is a type of non-Hodgkin’s lymphoma that primarily affects the skin, rich in hyaluronic acid (HA). HA is a component of the extracellular matrix in the dermis and likely affects the development of CTCL, but the mechanism is poorly understood. Here we show that low-molecular-weight HA (LMWHA) possibly exacerbates CTCL, and bexarotene, already used in CTCL treatment, decreases HA production. Methods: We conducted immunohistochemistry, qRT-PCR, immunoblotting, and HA quantification using both mouse and human specimens to evaluate the impact of HA on CTCL. Additionally, we assessed the effect of bexarotene, which is already used for CTCL treatment, on HA metabolism. Results: HA expression was higher in patients’ serum and skin sections than in healthy controls. HA extracted from the skin of mice inoculated with tumors showed an increase in LMWHA. LMWHA increased lymphoma cell proliferation in vitro and accelerated tumor formation in mice in vivo. LMWHA also created a favorable environment for tumor cells by affecting fibroblasts, vascular endothelial cells, and tumor-associated macrophages. Thus, increased levels of HA, mainly LMWHA, exacerbate CTCL progression by affecting tumor cells and their microenvironment. Bexarotene treatment reduced the amount of total HA in murine tumor-inoculated skin, as well as the supernatant of cultured normal human dermal fibroblasts (NHDFs) and HuT78 cells. Detailed in vitro analyses showed that bexarotene treatment decreased HA synthase (HAS)1 and HAS2 expression in NHDFs and HAS1 and HAS3, and CEMIP expression in HuT78 cells. Chromatin immunoprecipitation assays revealed that bexarotene reduced retinoid X receptor-α binding to the HAS1 and HAS2 promoters in NHDFs. Conclusions: Bexarotene potentially exerts its anti-tumor effect by reducing HA levels through decreased expression of HAS. These findings provide new insights into the process of CTCL development and additional insights regarding bexarotene treatment.
Immune-Based and Novel Therapies in Variant Histology Renal Cell Carcinomas
Authors: Miller Justin W. , Johnson Jeffrey S. , Guske Christopher , Mannam Gowtam , Hatoum Firas , Nassar Michelle , Potez Marine , Fazili Adnan , Spiess Philippe E. , Chahoud Jad
Published: January 2025

Renal cell carcinoma (RCC) is a heterogeneous disease that represents the most common type of kidney cancer. The classification of RCC is primarily based on distinct morphological and molecular characteristics, with two broad categories: clear cell RCC (ccRCC) and non-clear cell RCC (nccRCC). Clear cell RCC is the predominant subtype, representing about 70–80% of all RCC cases, while non-clear cell subtypes collectively make up the remaining 20–30%. Non-clear cell RCC encompasses many histopathological variants, each with unique biological and clinical characteristics. Additionally, any RCC subtype can undergo sarcomatoid dedifferentiation, which is associated with poor prognosis and rapid disease progression. Recent advances in molecular profiling have also led to the identification of molecularly defined variants, further highlighting the complexity of this disease. While immunotherapy has shown efficacy in some RCC variants and subpopulations, significant gaps remain in the treatment of rare subtypes. This review explores the outcomes of immunotherapy across RCC subtypes, including rare variants, and highlights opportunities for improving care through novel therapies, biomarker-driven approaches, and inclusive clinical trial designs.