bluuebunny/crossref_metadata_2025_split huggingface dataset:
Industry Payments and Sentiments Toward Robotic Surgery Among US Physicians
Authors: Loh Wei San , Ibrahim Andrew M. , Sheskey Sarah , Stone Colleen M. , Sheetz Kyle H. 
Published: February 2025

ImportanceGiven the rapid adoption of robotic surgery and its association with substantial industry payments, objective documentation of physicians’ perceptions toward robotic surgery is important.ObjectiveTo assess US-based physicians’ sentiments toward robotic surgery and whether industry payments are associated with their perceptions.Design, Setting, and ParticipantsThis cohort study analyzed publicly available posts made from March 19, 2009, to April 1, 2024, by 268 US-based physicians who followed the Society of American Gastrointestinal and Endoscopic Surgeons on X (formerly Twitter). Trainees and individuals without validated clinical practices were excluded. Physicians’ specialties were confirmed using the National Provider Identifier Registry.ExposurePayments from Intuitive Surgical Inc, a biotechnology company that manufactures robotic products for use in surgery, were identified via the Open Payments website. Among the physicians, 177 (66.0%) received payments and 91 (34.0%) did not.Main Outcomes and MeasuresPolarity and subjectivity scores of social media posts shared by physicians. Polarity was scored from −1 to 1, with higher scores reflecting more positive sentiment, lower scores reflecting more negative sentiment, and 0 indicating neutrality. Subjectivity was scored from 0 to 1, with higher scores reflecting more subjective opinions and lower scores reflecting objective facts.ResultsThis study comprised 268 physicians (154 men [57.5%], 68 women [25.4%], and 46 physicians [17.2%] with sex not reported; 113 general surgeons [42.2%] and 155 physicians in surgical subspecialties [57.8%]). The overall sentiment scores ranged from −0.25 to 0.5 (mean [SD] score, 0.1 [0.2]; 95% CI, 0.09-0.13) and subjectivity scores ranged from 0 to 0.9 (mean [SD] score, 0.4 [0.2]; 95% CI, 0.38-0.41), suggesting that posts were relatively objective with occasional personal insights. No significant difference was seen in mean polarity scores between the 177 physicians who received payments and the 91 physicians who did not (mean [SD] score, 0.12 [0.2]; 95% CI, 0.09-0.14 vs 0.1 [0.2]; 95% CI, 0.07-0.14). Physicians posting before and after receiving industry payments showed consistent positive sentiments (median polarity, 0.1 [IQR, 0.03-0.21]) and decreased subjectivity after receiving payment. Physicians in the top 25% of payment distribution had more positive sentiments and increased subjectivity after receiving payments, whereas those in the bottom 75% showed little change.Conclusions and RelevanceIn this cohort study of US-based physicians, publicly available social media data were used to quantify perceptions of robotic surgery. These findings demonstrate the potential of such data to inform health care practices, guide balanced information dissemination, and uphold the integrity of health information shared by physicians.
The implementation of knowledge‐based planning with partial OAR contours for prostate radiotherapy
Authors: Osipitan Ositomiwa O. , Wiant David , Liu Han 
Published: February 2025

AbstractPurposeIntra‐ and inter‐observer contour uncertainty is a continuous challenge in treatment planning for radiotherapy. Our proposed solution to address this challenge is the use of partial contours for treatment planning, focusing on uninvolved or non‐overlapping portions of the organs‐at‐risk (OARs) with the planning target volume (PTV).MethodsThe partial contours systematically eliminate overlapping regions. The partial contours were evaluated against fully contoured OARs. We incorporated advanced tools like knowledge‐based planning (KBP) to create treatment plans and artificial intelligence (AI) to create auto‐segmented contours. We developed two models, Rapid Plan (RP) and Rapid Plan partial uninvolved (RP_Part_Un), using 70 previous clinically approved volumetric arc therapy (VMAT) plans each prescribed with 70 Gy/28 fractions. From these models, we created three plans, RP, RP_Part_Un, and MIM AI_Part_Un. In this retrospective study, 60 prostate patients were analyzed using the three plans. For determining OAR sparing, Dmax and Dmean along the percent volume receiving a dose over a range (V10 Gy V70 Gy) between each plan were compared. Geometric evaluations, dice similarity coefficient (DSC), and overlay index (OI) between the OAR contours from partial‐contoured manual structure sets and partial‐contoured AI structure sets were analyzed.ResultsWhen comparing the DSC and OI for full contours to the partial contours, in both groups, all comparisons were significantly increased for both organs. This indicated the partial contours had a higher degree of concordance. In patients with SpaceOAR, RP_Part_Un plans exhibited significantly reduced bladder Dmax and Dmean compared to RP plans, while rectum Dmax and Dmean showed no significant differences. For patients without SpaceOAR, RP_Part_Un significantly lowered rectum Dmean. MIM AI_Part_Un plans demonstrated lower rectum Dmax in both patient groups.ConclusionsPartial contours, defined at a specified distance from the PTV, yielded dosimetry comparable to fully contoured plans, highlighting their potential efficacy in treatment planning.
Designing Biomimetic Leaves for Solar Spectrum Similarity and Even Multifunction
Authors: Yang Peiyao , Zhang Tong , Wang Yuchao , Ou Houzheng , Zheng Haitao , Zhang Jing , Wang Meng , Deng Danni , Chen Yingbi , Liu Xiangcui , Liu Zhiming , Xiong Xiang , Lei Yongpeng 
Published: February 2025

AbstractSimulating the characteristics and achieving specific functions of biological systems are stirring but challenging. Developing biomimetic leaves (BLs) with functions such as photosynthesis, transpiration, and solar spectrum similarity receives great attention. With increasingly developed hyperspectral imaging techniques, though BLs for solar spectrum similarity have made significant strides, they are still grappling with low similarity and single function. In this review, first, the tissue and optical path of natural leaves are analyzed. Then, the spectral characteristics of the up‐to‐date pigments for single functional and multifunctional BLs are summarized. The importance of multifunctional BLs is highlighted. Notably, organic–inorganic hybrid pigments with vibrant colors and multifunction, show boundless promise. At last, insights into perspectives and challenges on BLs for solar spectrum similarity are provided. This review contributes profound insights into the biomimetic materials toward natural plants.
Synergistic Macroscopic–Microscopic Regulation: Dual Constraints of the Island Effect and Coffee‐Ring Effect in Printing Efficient Flexible Perovskite Photovoltaics
Authors: Chu Zhaoyang , Fan Baojin , Shi Weijie , Xing Zhi , Gong Chenxiang , Li Jin , Li Linfeng , Meng Xiangchuan , Niazi Muhammad Bilal Khan , Hu Xiaotian , Chen Yiwang 
Published: February 2025

AbstractThe performance of flexible perovskite solar modules (FPSMs) remains inferior to their rigid counterparts, primarily due to poor crystallinity and homogeneity resulting from disordered perovskite colloid transfer during the printing process. Here, the study introduces an Elastic Porous Meniscus (EPM) printing strategy to mitigate the island effect and coffee‐ring effect. By increasing the peak shear rate, the study effectively disperses perovskite islands. The issue of heterogeneous deposition is addressed by controlling shear force and surface tension. Additionally, the Laplace force is regulated to weaken Marangoni flow, enabling the printing of large‐area, high‐quality flexible perovskite films. The results show that the time window for initialized crystallization is greatly extended by a factor of four (from 2.5 to 11 s), enabling the formation of uniform perovskite films with high crystal uniformity. Consequently, the flexible perovskite solar cells (FPSCs) achieve a record‐breaking power conversion efficiency (PCE) of 25.54% (certified 25.44%) based on 1.01 cm2, with exceptional repeatability. EPM‐printed FPSMs with an active area of 100 cm2 demonstrate a PCE of 16.39% (certified 15.65%), comparable to rigid modules. This advancement significantly enhances the market potential and commercial value of perovskite photovoltaics across diverse applications.
F‐Free Fabrication Novel 2D Mo‐Based MBene Catalyst for Advanced Lithium–Sulfur Batteries
Authors: Pu Jun , Fan Shanshan , Shen Zihan , Yin Jiasen , Tan Yun , Zhang Kai , Wu Bing , Hong Guo , Yao Yagang 
Published: February 2025

AbstractAn efficient electrocatalytic medium is very important for lithium–sulfur (Li–S) batteries. Herein, as a novel MBene‐based material, 2D MoB is employed to facilitate the catalytic conversion of lithium polysulfides (LiPSs). Instead of the HF etching technology of previous MXene, the accordion‐like MoB‐based MBene adopts a hydrothermal‐assisted process. Its F‐free surface property prevents the harm of negative sulfur cathode from −F terminations. The high charge conductivity and abundant electrocatalytic active sites promote the adsorption‐transfer conversion of LiPSs on the MoB surface and accelerate the redox kinetics. Theoretical calculation, visual detection and in situ Raman results show that the stratified MoB‐coated separator inhibits the “shuttle effect” of soluble LiPSs through the coupling of physical and chemical mechanisms. Therefore, this work achieves a commendable stability of 847 mAh g−1 reversible capacity (2.0 C) and 0.0651% attenuation rate per cycle (4.0 C). The area capacity of 4.93 mAh cm−2 is still obtained under high loading. More importantly, this work has uncovered the great potential of promising 2D MBene as a catalyst for the reaction of sulfur species.
High‐Density Accessible Iron Single‐Atom Catalyst for Durable and Temperature‐Adaptive Laminated Zinc‐Air Batteries
Authors: Lan Liansheng , Wu Yonggan , Pei Yangfan , Wei Yuanhao , Hu Ting , Lützenkirchen‐Hecht Dirk , Yuan Kai , Chen Yiwang 
Published: February 2025

AbstractDesigning single‐atom catalysts (SACs) with high density of accessible sites by improving metal loading and sites utilization is a promising strategy to boost the catalytic activity, but remains challenging. Herein, a high site density (SD) iron SAC (D‐Fe‐N/C) with 11.8 wt.% Fe‐loading is reported. The in situ scanning electrochemical microscopy technique attests that the accessible active SD and site utilization of D‐Fe‐N/C reach as high as 1.01 × 1021 site g−1 and 79.8%, respectively. Therefore, D‐Fe‐N/C demonstrates superior oxygen reduction reaction (ORR) activity in terms of a half‐wave potential of 0.918 V and turnover frequency of 0.41 e site−1 s−1. The excellent ORR property of D‐Fe‐N/C is also demonstrated in the liquid zinc‐air batteries (ZABs), which exhibit a high peak power density of 306.1 mW cm−2 and an ultra‐long cycling stability over 1200 h. Moreover, solid‐state laminated ZABs prepared by presetting an air flow layer show a high specific capacity of 818.8 mA h g−1, an excellent cycling stability of 520 h, and a wide temperature‐adaptive from −40 to 60 °C. This work not only offers possibilities by improving metal‐loading and catalytic site utilization for exploring efficient SACs, but also provides strategies for device structure design toward advanced ZABs.
A CFD study of the effect of ridge baffles on the hydrodynamic behavior in gas–solid fluidized system
Authors: Jia Zhiyong , Shen Xiankun , Wang Yuelin , Lan Xiaocheng , Wang Tiefeng 
Published: February 2025

AbstractThis study investigates the impact of ridge baffles on the hydrodynamics of cold hydrogenation fluidized bed reactors (FBRs) using Euler–Euler simulations. The model was validated by comparing predicted pressure drops and bed expansion ratios with literature results. A comparative analysis was performed on 3D FBRs with and without ridge baffles in terms of solid holdup, gas–solid velocity distribution, pressure fluctuation, and residence time distribution (RTD). Ridge baffles were found to effectively break up large bubbles and enhance gas–solid contacting efficiency, as demonstrated by visual observations, reduced pressure standard deviations, and increased bubble frequency. Furthermore, baffled FBRs demonstrated a much narrower RTD and shorter tails than the free FBR, indicating the ability to suppress gas‐phase back‐mixing through the inhibition of solid back‐mixing and improvement of stripping efficiency. Based on sensitivity analysis of the number of baffle layers, one single layer of ridge baffles is the optimal design under the current simulation.
Clinical Insights Into Nabais Sá‐De Vries Syndrome due to a Novel SPOP Mutation: Neuromotor, Cognitive, Adaptive, Behavioral, and Neurovisual Features
Authors: Galli Jessica , Loi Erika , Zanardini Federica , Baldoni Giovanna , Novara Francesca , Panigada Serena , Ciccone Roberto , Cutrì Maria Rosa , Bertoletti Alice , Pinelli Lorenzo , Fazzi Elisa 
Published: February 2025

ABSTRACTNabais Sá‐De Vries syndrome (NSDVS) is an extremely rare autosomal dominant disorder caused by SPOP mutations. To date, only 10 cases have been described presenting with intellectual disability, neurological signs and symptoms, and a variable association of dysmorphic features. In this article, we report a new case of NSDVS involving a novel pathogenic variant of the SPOP gene. We describe the patient's motor, cognitive, adaptive, behavioral, and neurovisual features, as well as her developmental trajectory. The girl, followed‐up from the first months of life to 11 years of age, presented with a de novo heterozygous missense in Exon 5 of the SPOP gene (NM_001007228.2:c.361C>T, p.Arg121Trp) and, thus, classified as NSDVS Type 1. Along with a global developmental delay, she showed microcephaly, dysmorphic features (such as narrow forehead, highly arched eyebrows, and blepharophimosis), moderate intellectual disability, adaptive difficulties, language disorder, and several neurovisual signs and symptoms (such as refractive errors, strabismus, nystagmus, altered oculomotor functions and deficits of visual acuity, and contrast sensitivity). These findings suggest a predominant involvement of the central nervous system in NSDVS and expand the phenotypic spectrum of this syndrome.
Refining the adriamycin‐induced focal segmental glomerulosclerosis mouse model to improve reproducibility and animal welfare
Authors: Jiang Haochen , Althobaiti Salma , Pinkerton Braeden , Fu Xin , Jia Zhenshan , Foster Kirk W. , Thiele Geoffrey M. , Plumb Troy J. , Wang Dong 
Published: February 2025

AbstractBackgroundReliable animal models are crucial to drug development for focal segmental glomerulosclerosis (FSGS), a rare kidney disease. Variability in success rates in literature and significant ethical concerns with animal welfare necessitate further optimization of adriamycin (ADR)–induced FSGS model developed on BALB/c mice.MethodsHigh‐performance liquid chromatography (HPLC) was used to assess ADR stability in water and upon light exposure. To identify the optimal ADR level, single intravenous ADR injections with dosing levels from 10 to 17 mg/kg body weight were administered to BALB/c mice to induce FSGS‐like pathology. Body weight and proteinuria of FSGS mice were monitored and analyzed for FSGS model–associated morbidity. Animals were euthanized for hematological and kidney histological assessments 8 weeks post induction. To identify the suitable experiment time frame of the ADR‐induced FSGS mouse model, a longitudinal study was performed, with an 11‐week continuous monitoring of the symptoms.ResultsADR was found to be unstable in aqueous media and light sensitive. A dosing level of 10.5 mg/kg of ADR was optimal for consistent FSGS mouse model induction on BALB/c strain, characterized by minimal mortality and sustained FSGS‐like symptoms. Findings from the longitudinal study suggest that 6 weeks post ADR induction may represent the peak of FSGS pathology severity in this mouse model. This time frame may be used for FSGS drug development projects.ConclusionBased on the outcome from this study, we identified the optimal ADR dosing level and model testing duration. A standard operating procedure (SOP) for the ADR‐induced FSGS mouse model was established to facilitate FSGS basic research and drug development.
Nigral Neuroinflammation and Dopaminergic Neurons in Parkinson's Disease and Atypical Parkinsonisms
Authors: Backman Emmilotta A. , Gardberg Maria , Luntamo Laura , Peurla Markus , Vahlberg Tero , Borghammer Per , Stefanova Nadia , Wenning Gregor , Kaasinen Valtteri 
Published: February 2025

ObjectiveTo investigate the role of neuroinflammation in the substantia nigra pars compacta (SNc) across different parkinsonian disorders—Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multiple system atrophy (MSA)—by examining SNc dopaminergic neuron counts, neuroinflammatory T cells, and microglial activity.MethodsPostmortem neuropathological samples were collected from 79 individuals (PD, n = 38; PSP, n = 15; MSA, n = 14; controls, n = 12). The density of SNc tyrosine hydroxylase (TH)‐positive neurons, T cells (CD3+, CD4+, and CD8+), and Iba1 expression (Iba1‐positive microglia/macrophages) were examined in the SNc and crus cerebri. Demographic and clinical data were gathered from patient histories.ResultsPSP patients had 89 to 212% more nigral CD3+, CD4+, and CD8+ T cells compared to MSA patients (p < 0.04), 125 to 178% more CD3+ and CD4+ T cells than healthy controls (p < 0.002), and 95% more CD4+ T cells than PD patients (p = 0.001). Iba1 expression in the SNc was higher in PD patients than in MSA patients (p = 0.004), with no significant differences observed across other conditions. There was a negative association between disease duration and SNc CD3+ T cell density (p = 0.002), and a positive correlation between nigral dopaminergic neuron density and CD3+ density, CD8+ density, and Iba1 expression in PD patients.InterpretationThe study reveals distinctive neuroinflammatory patterns in the SNc, with T cell‐mediated inflammation prominent in PSP and microglia‐mediated inflammation in PD. PSP and MSA show greater SNc dopaminergic neuron loss compared to PD. Increased neuroinflammatory response is seen in earlier disease stages, diminishing with greater neuron loss, which may inform disease progression understanding and therapeutic strategies. ANN NEUROL 2025
KCl Supported by γ‐Al2O3 for Selective Adsorption of Gaseous Oxidized Mercury: Flue Gas Influence and Application
Authors: Tong Jiangyi , Li Haiyang , Jin Rui , Liu Xiaoshuo , Hu Haitao , Duan Yufeng , Ma Xiuyuan , Zhong Li , Han Lipeng 
Published: February 2025

ABSTRACTThe KCl supported by γ‐Al2O3 for selective adsorption of gaseous HgCl2 has demonstrated high selectivity and adsorption capacity, which is crucial for mercury speciation partitioning from flue gas. However, its influence and stability in complex flue gas remains uncertain. Therefore, this paper explores the impact of common flue gas components (HCl, SO2, H2O, CO2, NO, O2) on the adsorption process and elucidates the underlying mechanisms from experiment and DFT view. The experimental results demonstrate that the HgCl2 breakthrough rate increases significantly from 2.119% to 17.921% as the concentration of HCl rises from 0 to 200 ppm. Comparatively, the HgCl2 breakthrough rate affected by SO2 and H2O is less than 8%, weakly reducing the adsorption efficiency of HgCl2, and that by CO2, NO, and O2 is less than 5%, showing negligible effects on the HgCl2 adsorption efficiency. The DFT indicates that HCl competes with HgCl2 at the Top‐Cl site in KCl, thereby reducing the adsorption efficiency of HgCl2, with the adsorption energy decreasing from −87.11 to −43.39 kJ/mol. In contrast, SO2 and H2O exhibit relatively weak interactions with Top‐Cl site of KCl, which exerts little influence on HgCl2 adsorption. The 100‐h running in low‐concentration simulated flue gas test in laboratory and on‐site test in coal‐fired flue gas demonstrate that the KCl/γ‐Al2O3 achieves a very low HgCl2 breakthrough rate of less than 10%, highlighting its superior interference immunity for the complex flue gas components and strong suitability and stability for industrial applications. This study provides solid evidence to support the industrial application of KCl/γ‐Al2O3 for highly selective adsorption of gaseous HgCl2 in coal‐fired power plant.
Exploring Ensemble Learning Techniques for Infant Mortality Prediction: A Technical Analysis of XGBoost Stacking AdaBoost and Bagging Models
Authors: Verma Indu , Prasad Sanjeev Kumar 
Published: February 2025

ABSTRACTBackgroundInfant mortality remains a critical public health issue, reflecting the overall health and well‐being of a population. Accurate prediction of infant mortality is crucial, as it enables healthcare providers to identify at‐risk populations and implement targeted interventions. By analyzing factors such as maternal education, prenatal care access, nutrition, and environmental influences, predictions help in designing effective programs aimed at reducing infant deaths.MethodsThis research paper aims to predict infant mortality in India by employing ensemble learning techniques, specifically eXtreme gradient boosting (XGBoost), stacking, adaptive boosting, and bagging. The data for the analysis are sourced from national surveys and demographic studies focusing on infant mortality in India. The collected data underwent rigorous preprocessing steps to prepare it for predictive modeling. Each ensemble learning model is applied to predict infant mortality rates based on the preprocessed data. The XGBoost handles complex and non‐linear relationships within the data, and the stacking model is used for the accurate and robust predictions. The adaptive boosting model iteratively trains multiple weak learners, which makes the predictive model as stronger. The adaptive boosting technique enhances the performance of weak classifiers while effectively addressing class imbalance issues. Further, the bagging approach is implemented to derive the linear and non‐linear relationships of infant mortality. Models were optimized using k‐fold cross‐validation to fine‐tune their hyper parameters. The predictive ability of the ensemble techniques is analyzed by deploying using different performance parameters.ResultsXGBoost attained superior performance results, with a 98.75% accuracy, 98.56% precision, and 98.24% recall. The adaptive boosting model strengthened weak learners and addressed class imbalance issues, while the bagging method captures linear and non‐linear relationships. Ensemble learning models demonstrated effectiveness in predicting infant mortality, with XGBoost excelling in handling complex and non‐linear relationships.ConclusionsThe simulation results revealed that ensemble learning models are highly effective in predicting infant mortality rates in India, with significant regional disparities observed. For example, the Northeast region exhibited the highest predicted infant mortality rates, while the South region recorded the lowest. These findings underscore the need for targeted interventions in high‐mortality areas to reduce disparities. The study highlights the efficacy of ensemble learning models, particularly XGBoost, in predicting infant mortality in India. The findings emphasize the critical role of improving maternal education, access to prenatal care, and reducing socioeconomic disparities.