bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vision-based estimation of manipulation forces by deep learning of laparoscopic surgical images obtained in a porcine excised kidney experiment
Authors: Masui Kimihiko , Kume Naoto , Nakao Megumi , Magaribuchi Toshihiro , Hamada Akihiro , Kobayashi Takashi , Sawada Atsuro 
Published: April 2024

AbstractIn robot-assisted surgery, in which haptics should be absent, surgeons experience haptics-like sensations as “pseudo-haptic feedback”. As surgeons who routinely perform robot-assisted laparoscopic surgery, we wondered if we could make these “pseudo-haptics” explicit to surgeons. Therefore, we created a simulation model that estimates manipulation forces using only visual images in surgery. This study aimed to achieve vision-based estimations of the magnitude of forces during forceps manipulation of organs. We also attempted to detect over-force, exceeding the threshold of safe manipulation. We created a sensor forceps that can detect precise pressure at the tips with three vectors. Using an endoscopic system that is used in actual surgery, images of the manipulation of excised pig kidneys were recorded with synchronized force data. A force estimation model was then created using deep learning. Effective detection of over-force was achieved if the region of the visual images was restricted by the region of interest around the tips of the forceps. In this paper, we emphasize the importance of limiting the region of interest in vision-based force estimation tasks.
Hypothermia on the first day of ICU admission leads to increased in-hospital mortality in patients with subarachnoid hemorrhage
Authors: Du Wenyuan , Yang Jingmian , Lou Yanfang , You Jiahua 
Published: April 2024

AbstractThe relationship between early spontaneous hypothermia and adverse clinical outcomes in patients with subarachnoid hemorrhage (SAH) has not been paid much attention. We designed this retrospective cohort study to determine this relationship by analyzing the association between the lowest body temperature (T-lowest) on the first day of ICU admission and in-hospital mortality. In this study, 550 participants with non-traumatic SAH were chosen from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Multivariate Cox regression analysis showed that T-lowest was nonlinearity correlated with in-hospital mortality (HR = 0.72, 95% CI: 0.59–0.86, p < 0.001). We divided the T-lowest into quartile groups. In comparison to reference group Q1 (31.30–36.06 ℃), group Q3 (36.56–36.72 ℃) had a 50% lower risk of death in the hospital (HR: 0.5, 95% CI: 0.28–0.87, p = 0.014). We further confirmed the curve-like relationship between T-lowest and in-hospital mortality using restricted cubic splines. The mortality is lowest when the T-lowest is close to 36.5 °C, and the risk of death is increased when the temperature is lower or higher than that. Our study demonstrates that in-hospital mortality is associated with T-lowest. Patients with non-traumatic SAH are at increased risk of death if their body temperature on the first day of ICU admission is too low.
Soft ground micro TBM jack speed and torque prediction using machine learning models through operator data and micro TBM-log data synchronization
Authors: Kilic Kursat , Narihiro Owada , Ikeda Hajime , Adachi Tsuyoshi , Kawamura Youhei 
Published: April 2024

AbstractTunnel Boring Machines (TBMs) are pivotal in underground projects like subways, highways, and water supply tunnels. Predicting and monitoring jack speed and torque is crucial for optimizing TBM excavation efficiency. Conventionally, skilled operators manually adjust numerous tunnelling parameters to regulate the machine's progress. In contrast, machine learning (ML) algorithms offer a promising avenue where computers learn from operator actions to establish parameter relationships autonomously. This study introduces an innovative approach to enhancing operator monitoring and TBM data comprehension. A robust correlation between TBM operator behaviour and TBM logged data is established by leveraging an Optuna-assisted ML methodology—the research light on the intricate dynamics influencing TBM advance rate parameters. Operational data is collected from micro slurry tunnel boring machine (MSTBM) umbrella support excavations. The proposed framework harnesses Optuna, an advanced hyperparameter optimization platform, to dynamically refine jack speed and torque settings. Through meticulous analysis of the interplay between TBM operator decisions and real-time logged data, the AI model discerns patterns, empowering informed decision-making. Using Optuna, a range of models, including random forest (RF), K-nearest neighbours (kNN), decision tree (DT), XGBoost, Support Vector Machine (SVM), and Artificial Neural Network (ANN) were automatically compared and tuned. The best model's (RF) performance is evaluated through a correlation coefficient (R2) of 96%, mean squared error (MSE) of 119.7, and mean absolute error (MAE) of 4.42 for jack speed decision making while 83% of R2, MSE of 0.62, and MAE of 0.42 for the torque decision making. This intelligent model can assist the TBM operator in making decisions about TBM control.
Fabrication of stable monolayer liquid marbles with reduced particle coverage and locomotion on hydrophilic surface
Authors: Jin Jing , Huang Zheng , Xie Yuanhao , Shen Zheng , Liu Bo , Chen Huaying 
Published: April 2024

AbstractLiquid marbles are non-wetting, particle-covered microdroplets with a core-shell structure that are used in sample transport, material synthesis, and real-time sensing. Optimizing the distribution of shell particles remains a challenge, due to a tendency for aggregation via spontaneous assembly, which often leads to multilayered structures. Here, we outline a simple method for fabricating water-filled, monolayer liquid marbles with adjustable particle coverage rates, greatly reducing particle consumption. The soft liquid marbles are enclosed by a small quantity of modified polystyrene microspheres and display good atmospheric stability. The rolling behavior of flexible liquid marbles with wide coverage rates is then characterized. Contrary to common perception, the marbles with transparent openings exhibit high maneuverability on hydrophilic surfaces, and also excel in fusion, reaction and surface cleaning, with an elongated operational duration and a wide visualization range. The study provides new insights into the implementation of liquid marble-based miniaturized platforms.
Computer Patient-Specific 3D Modeling and Custom-Made Guides for Revision ACL Surgery
Authors: Del Prete Armando , Franco Piero , Innocenti Matteo , Matassi Fabrizio , Leggieri Filippo , Sagliocco Rosario Jr , Civinini Roberto 
Published: April 2024

AbstractRevision anterior cruciate ligament reconstruction (ACLR) is a challenging surgery occurring in 3 to 24% of primary reconstructions. A meticulous planning to study the precise size and location of both femoral and tibial bone tunnels is mandatory. The aim of the study was to evaluate the intra- and interoperator differences in the decision-making process between experienced surgeons after they were asked to make preoperative planning for ACL revision reconstruction with the use of both the computed tomography (CT) scan and a three-dimensional (3D)-printed model of the knee. Data collected from 23 consecutive patients undergoing revision of ACLR for graft failure at a single institute between September 2018 and February 2020 were prospectively reviewed. The double-blinded collected data were presented to three board-certificate attending surgeons. Surgeons were asked to decide whether to perform one-stage or two-stage revision ACLR based on the evaluation of the CT scan images and the 3D-printed custom-made models at two different rounds, T0 and T1, respectively, 7 days apart one from the other. Interoperator consensus following technical mistake was 52% at T0 and 56% at T1 using the CT scans, meanwhile concordance was 95% at T0 and 94% at T1 using the 3D models. Concordance between surgeons following new knee injury was 66% at T0 and 70% at T1 using CT scans, while concordance was 96% both at T0 and T1 using 3D models. Intraoperative variability using 3D models was extremely low: concordance at T0 and T1 was 98%. McNemar test showed a statistical significance in the use of 3D model for preoperative planning (p < 0.005). 3D-printed model reliability resulted to be higher compared with CT as intraoperator surgery technique selection was not modified throughout time from T0 to T1 (p < 0.005). The use of 3D-printed models had the most impact when evaluating femoral and tibial tunnels, resulting to be a useful instrument during preoperative planning of revision ACLR between attending surgeons with medium-high workflow.
Visible-Light-Driven Metal-Free and Photocatalyst-Free Intra­molecular Cyclization of Chalcones to Access Phenanthrenes
Authors: Yi Miaoyan , Zhang Chen , Sun Bing , Liao Saihu 
Published: April 2024

AbstractWe report a visible-light-driven metal-free and photocatalyst-free protocol for the synthesis of phenanthrenes through the intramolecular cyclization of chalcones. The transformation proceeds through light irradiation and base- and oxygen-based promotion, and enables the generation of a series of phenanthrenes. The further functionalization of an as-synthesized phenanthrene to afford a fluorescent molecule was explored.
Innovation capital disclosure and independent directors: evidence from France
Authors: Lahyani Fathia Elleuch , Ayadi Salma Damak 
Published: April 2024

Abstract
This study aims to understand whether corporate governance mechanisms affect innovation capital disclosure (ICD) provided voluntarily on corporate websites by SBF 120 listed firms in France. The study tests multivariate models using pooled OLS, random effects, and generalized method of moments models. Firms use ICD as a useful, timely communication tool to highlight their innovation efforts. Our findings suggest that independent non-executive directors (INEDs) exhibit a conservative approach to the nature of innovation that requires extensive investigations with risky outcomes. They support discretion by limiting the extent of publicly disclosed information about research and development (R&D) progress, technological advances, and innovation output to protect the firms’ intellectual proprietary. INEDs seem to balance preserving firms’ competitive advantage and ensuring higher transparency levels to satisfy stakeholders’ needs. Additionally, board tenure moderates the relationship between INEDs and ICD. This study underscores the importance of the financial reporting of information about innovation capital that captures firms’ innovation capacities in a knowledge-based economy. It provides significant insights for management, policy-makers, and regulators who are involved in refining corporate reporting policies. This study is the first to examine the incentives of INEDs in influencing reporting practices related to a firm’s innovation investments, particularly in high-technology firms.
Commemorative textiles: an African narrative of identity and power
Authors: Lemi Ladu D. M. 
Published: April 2024

AbstractCommemorative textiles play a significant role in shaping Africa’s cultural identity and expressions of power. Embedded within the cultural fabric of Africa, these textiles represent the intellectual and artistic vitality of Africa, serving as powerful symbols of its rich heritage and diversity. Through the lens of memory and commemoration, this study investigated how African cultural memory and identity are negotiated and conveyed through textiles. Drawing upon Bodnar’s theoretical framework, the study examines secondary data, using a content analysis approach to discern how commemorative textiles recollect both official and vernacular cultural memories. The result showed that African commemorative textiles are mirrors of local cultures expressing social status, political authority, and economic worth, which play a crucial role in shaping collective memory, preserving cultural knowledge, and fostering a sense of belonging among communities. As preservers of the past and inspirations for the future, the textiles weave the African narrative of identity and power, perpetuating cultural heritage across generations.
Dissipation-Driven Superradiant Phase Transition of a Two-Dimensional Bose–Einstein Condensate in a Double Cavity
Authors: Wu Bo-Hao , Yang Xin-Xin , Chen Yu , Zhang Wei 
Published: April 2024

Abstract
We study superradiant phase transitions in a hybrid system of a two-dimensional Bose–Einstein condensate of atoms and two cavities arranged with a tilt angle. By adjusting the loss rate of cavities, we map out the phase diagram of steady states within a mean field framework. It is found that when the loss rates of the two cavities are different, superradiant transitions may not occur at the same time in the two cavities. A first-order phase transition is observed between the states with only one cavity in superradiance and both in superradiance. In the case that both cavities are superradiant, a net photon current is observed flowing from the cavity with small decay rate to the one with large decay rate. The photon current shows a non-monotonic dependence on the loss rate difference, owing to the competition of photon number difference and cavity field phase difference. Our findings can be realized and detected in experiments.
High-density lipoprotein (HDL) as an indicator for alcohol use in a psychiatrically ill population
Authors: Benson Nicole M , Yakubu Amin , Ren Boyu , Aboud Carol , Vargas Victoria , Greenfield Shelly F , Busch Alisa B 
Published: April 2024

Abstract

Aims
To examine the cross sectional and longitudinal associations between the Alcohol Use Disorders Identification Test-Concise (AUDIT-C) and differences in high-density lipoprotein (HDL) in a psychiatrically ill population.

Methods
Retrospective observational study using electronic health record data from a large healthcare system, of patients hospitalized for a mental health/substance use disorder (MH/SUD) from 1 July 2016 to 31 May 2023, who had a proximal AUDIT-C and HDL (N = 15 915) and the subset who had a repeat AUDIT-C and HDL 1 year later (N = 2915). Linear regression models examined the association between cross-sectional and longitudinal AUDIT-C scores and HDL, adjusting for demographic and clinical characteristics that affect HDL.

Results
Compared with AUDIT-C score = 0, HDL was higher among patients with greater AUDIT-C severity (e.g. moderate AUDIT-C score = 8.70[7.65, 9.75] mg/dl; severe AUDIT-C score = 13.02 [12.13, 13.90] mg/dL[95% confidence interval (CI)] mg/dl). The associations between cross-sectional HDL and AUDIT-C scores were similar with and without adjusting for patient demographic and clinical characteristics. HDL levels increased for patients with mild alcohol use at baseline and moderate or severe alcohol use at follow-up (15.06[2.77, 27.69] and 19.58[2.77, 36.39] mg/dL[95%CI] increase for moderate and severe, respectively).

Conclusions
HDL levels correlate with AUDIT-C scores among patients with MH/SUD. Longitudinally, there were some (but not consistent) increases in HDL associated with increases in AUDIT-C. The increases were within range of typical year-to-year variation in HDL across the population independent of alcohol use, limiting the ability to use HDL as a longitudinal clinical indicator for alcohol use in routine care.
Synthesis, growth inhibitory activity against tumor cells, and structure-activity relationship of CGK733 and its analogs
Authors: Inagaki Yuta , Hashimoto Kohki , Wakamori Shinnosuke , Katsuta Ryo , Yajima Arata , Kaida Daisuke , Ishigami Ken 
Published: April 2024

ABSTRACT
CGK733 was reported as a compound that inhibited ATM/ATR kinase activities and blocked their checkpoint signaling pathways with great selectivity. However, this paper was subsequently retracted, and the truth about the activity of CGK733 remains unclear. We synthesized various analogs of CGK733 with a modification of the carboxylic acid moiety and/or the aniline derivative moiety to accumulate knowledge of the structure-activity relationship of this compound. Growth inhibitory activity of CGK733 and novel 35 analogs against HeLa S3 cells was evaluated, and the structure-activity relationship revealed that analogs with the 2-naphthyl or 4-fluorophenyl group instead of the benzhydryl group have activity comparable to CGK733 and that the 3-nitro group on the aniline moiety significantly affects the activity.
Short-term heat waves have long-term consequences for parents and offspring in stickleback
Authors: Barrett Rachel , Stein Laura R 
Published: April 2024

Abstract
Extreme temperature events, such as heat waves, can have lasting effects on the behavior, physiology, and reproductive success of organisms. Here, we examine the impact of short-term exposure to a simulated heat wave on condition, parental care, and reproductive success in a population of threespine stickleback (Gasterosteus aculeatus), a small fish with exclusive paternal care, currently experiencing regular heat waves. Males were either exposed to a simulated heat wave (23 °C) for 5 d or held at an ideal temperature (18 °C). Following this 5-d treatment, all males were transferred to 18 °C, where they completed a full parenting cycle. Offspring were raised at 18 °C. We found that while mass and body condition were unaffected in males exposed to a heat wave, cortisol responses were dampened across the nesting cycle compared to control males. In addition, heat wave males had longer latency for eggs to hatch, lower hatching success, and showed lower levels of parental care behavior compared to control males. Offspring of heat wave males had lower body condition, affecting swimming performance. Altogether, our results highlight the long-term impact that even short-term events can have on reproductive success, parental behavior, and subsequent generations, providing insight into population responses to rapid environmental change.
DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery
Authors: Lan Wei , Liao Haibo , Chen Qingfeng , Zhu Lingzhi , Pan Yi , Chen Yi-Ping Phoebe 
Published: April 2024

Abstract
Deep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models. Therefore, there is an urgent need for a deep learning-based multi-omics integration method to explore the potential correlations between samples and provide model interpretability. Herein, we propose a novel interpretable multi-omics data integration method (DeepKEGG) for cancer recurrence prediction and biomarker discovery. In DeepKEGG, a biological hierarchical module is designed for local connections of neuron nodes and model interpretability based on the biological relationship between genes/miRNAs and pathways. In addition, a pathway self-attention module is constructed to explore the correlation between different samples and generate the potential pathway feature representation for enhancing the prediction performance of the model. Lastly, an attribution-based feature importance calculation method is utilized to discover biomarkers related to cancer recurrence and provide a biological interpretation of the model. Experimental results demonstrate that DeepKEGG outperforms other state-of-the-art methods in 5-fold cross validation. Furthermore, case studies also indicate that DeepKEGG serves as an effective tool for biomarker discovery. The code is available at https://github.com/lanbiolab/DeepKEGG.
CPPLS-MLP: a method for constructing cell–cell communication networks and identifying related highly variable genes based on single-cell sequencing and spatial transcriptomics data
Authors: Zhang Tianjiao , Wu Zhenao , Li Liangyu , Ren Jixiang , Zhang Ziheng , Wang Guohua 
Published: April 2024

Abstract
In the growth and development of multicellular organisms, the immune processes of the immune system and the maintenance of the organism’s internal environment, cell communication plays a crucial role. It exerts a significant influence on regulating internal cellular states such as gene expression and cell functionality. Currently, the mainstream methods for studying intercellular communication are focused on exploring the ligand–receptor–transcription factor and ligand–receptor–subunit scales. However, there is relatively limited research on the association between intercellular communication and highly variable genes (HVGs). As some HVGs are closely related to cell communication, accurately identifying these HVGs can enhance the accuracy of constructing cell communication networks. The rapid development of single-cell sequencing (scRNA-seq) and spatial transcriptomics technologies provides a data foundation for exploring the relationship between intercellular communication and HVGs. Therefore, we propose CPPLS-MLP, which can identify HVGs closely related to intercellular communication and further analyze the impact of Multiple Input Multiple Output cellular communication on the differential expression of these HVGs. By comparing with the commonly used method CCPLS for constructing intercellular communication networks, we validated the superior performance of our method in identifying cell-type-specific HVGs and effectively analyzing the influence of neighboring cell types on HVG expression regulation. Source codes for the CPPLS_MLP R, python packages and the related scripts are available at ‘CPPLS_MLP Github [https://github.com/wuzhenao/CPPLS-MLP]’.
The interaction of ER stress and autophagy in trophoblasts: navigating pregnancy outcome
Authors: Zheng Yi , Zha Xia , Zhang Bei , Elsabagh Mabrouk , Wang Hongrong , Wang Mengzhi , Zhang Hao 
Published: April 2024

AbstractThe endoplasmic reticulum is a complex and dynamic organelle that initiates unfolded protein response and endoplasmic reticulum stress in response to the accumulation of unfolded or misfolded proteins within its lumen. Autophagy is a paramount intracellular degradation system that facilitates the transportation of proteins, cytoplasmic components, and organelles to lysosomes for degradation and recycling. Preeclampsia and intrauterine growth retardation are two common complications of pregnancy associated with abnormal trophoblast differentiation and placental dysfunctions and have a major impact on fetal development and maternal health. The intricate interplay between endoplasmic reticulum stress, and autophagy and their impact on pregnancy outcomes, through mediating trophoblast differentiation and placental development, has been highlighted in various reports. Autophagy controls trophoblast regulation through a variety of gene expressions and signaling pathways while excessive endoplasmic reticulum stress triggers downstream apoptotic signaling, culminating in trophoblast apoptosis. This comprehensive review delves into the intricacies of placental development and explores the underlying mechanisms of preeclampsia and intrauterine growth retardation. In addition, this review will elucidate the molecular mechanisms of endoplasmic reticulum stress and autophagy, both individually and in their interplay, in mediating placental development and trophoblast differentiation, particularly highlighting their roles in preeclampsia and intrauterine growth retardation development. This research seeks to the interplay between endoplasmic reticulum stress and impaired autophagy in the placental trophoderm, offering novel insights into their contribution to pregnancy complications.