bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Fluid Distribution and Petrophysics on Geophysical Signatures of CO2 Storage Sandstone Reservoirs
Authors: Falcon‐Suarez I. H. , Mangriotis M.‐D. , Papageorgiou G. , Mondol N. H.
Published: May 2024

Carbon Capture and Storage (CCS) is a key element to achieving net‐zero energy challenge timely. CCS operations require the integration of geophysical data, such as seismic and electromagnetic surveys, numerical reservoir models and fluid flow simulations. However, the 10–100s m resolution of seismic imaging methods complicates the mapping of smaller scale rock heterogeneities, while borehole measurements commonly show large fluctuations at sub‐cm scales. In this study, we combine laboratory data, well‐logging, rock physics theories and a proof‐of‐concept time‐lapse seismic modeling to assess the effect of pore‐scale fluid distribution and petrophysical heterogeneities on the expected performance of whole‐reservoir CCS operations in deep saline aquifers, by analogy to the Aurora CCS site, North Sea. We monitored the elastic and electrical properties of three sandstone samples with slightly different physical and petrographic properties during carbon dioxide (CO2) flow‐through tests under equivalent in situ effective pressure. We inferred the CO2‐induced damage in the rocks from the variations of their hydromechanical properties. We found that the clay fraction, CO2‐clay chemical interactions, and porosity were the main factors affecting both the CO2 distribution in the samples and the hydromechanical response. We used seismic modeling of well‐log data and the laboratory results to estimate the reservoir‐scale time‐lapse seismic response to CO2 injection and to assess the effect of the rock heterogeneities in our interpretation. The results show that disregarding the effect of rock heterogeneities on the CO2‐brine fluids distribution can lead to significant misinterpretations of seismic monitoring surveys during CCS operations in terms of both CO2 quantification and distribution.
A new fabrication method for enhancing the yield of linear micromirror arrays assisted by temporary anchors
Authors: Xiao Xingchen , Mao Ting , Shi Yingchao , Zhou Kui , Hao Jia , Yu Yiting
Published: May 2024

As one of the most common spatial light modulators, linear micromirror arrays (MMAs) based on microelectromechanical system (MEMS) processes are currently utilized in many fields. However, two crucial challenges exist in the fabrication of such devices: the adhesion of silicon microstructures caused by anodic bonding and the destruction of the suspended silicon film due to residual stress. To solve these issues, an innovative processing method assisted by temporary anchors is presented. This approach effectively reduces the span of silicon microstructures and improves the Euler buckling limit of the silicon film. Importantly, these temporary anchors are strategically placed within the primary etching areas, enabling easy removal without additional processing steps. As a result, we successfully achieved wafer-level, high-yield manufacturing of linear MMAs with a filling factor as high as 95.1%. Demonstrating superior capabilities to those of original MMAs, our enhanced version boasts a total of 60 linear micromirror elements, each featuring a length-to-width ratio of 52.6, and the entire optical aperture measures 5 mm × 6 mm. The linear MMA exhibits an optical deflection angle of 20.4° at 110 Vdc while maintaining exceptional deflection flatness and uniformity. This study offers a viable approach for the design and fabrication of thin-film MEMS devices with high yields, and the proposed MMA is promising as a replacement for digital micromirror devices (DMDs, by TI Corp.) in fields such as spectral imaging and optical communication.
SPEED: an integrated, smartphone-operated, handheld digital PCR Device for point-of-care testing
Authors: Zhang Haoqing , Liu Xiaocheng , Wang Xinlu , Yan Zhiqiang , Xu Ying , Gaňová Martina , Řezníček Tomáš , Korabečná Marie , Neuzil Pavel
Published: May 2024

This study elaborates on the design, fabrication, and data analysis details of SPEED, a recently proposed smartphone-based digital polymerase chain reaction (dPCR) device. The dPCR chips incorporate partition diameters ranging from 50 μm to 5 μm, and these partitions are organized into six distinct blocks to facilitate image processing. Due to the superior thermal conductivity of Si and its potential for mass production, the dPCR chips were fabricated on a Si substrate. A temperature control system based on a high-power density Peltier element and a preheating/cooling PCR protocol user interface shortening the thermal cycle time. The optical design employs four 470 nm light-emitting diodes as light sources, with filters and mirrors effectively managing the light emitted during PCR. An algorithm is utilized for image processing and illumination nonuniformity correction including conversion to a monochromatic format, partition identification, skew correction, and the generation of an image correction mask. We validated the device using a range of deoxyribonucleic acid targets, demonstrating its potential applicability across multiple fields. Therefore, we provide guidance and verification of the design and testing of the recently proposed SPEED device.
Temporal dissociation between local and global functional adaptations of the maternal brain to childbirth: a longitudinal assessment
Authors: Lotter Leon D. , Nehls Susanne , Losse Elena , Dukart Juergen , Chechko Natalya
Published: May 2024

The maternal brain undergoes significant reorganization during birth and the postpartum period. However, the temporal dynamics of these changes remain unclear. Using resting-state functional magnetic resonance imaging, we report on local and global brain function alterations in 75 mothers in their first postpartum week, compared to 23 nulliparous women. In a subsample followed longitudinally for the next six months, we observed a temporal and spatial dissociation between changes observed at baseline (cluster mass permutation: pFWE < 0.05). Local activity and connectivity changes in widespread neocortical regions persisted throughout the studied time period (ANCOVAs vs. controls: pFDR < 0.05), with preliminary evidence linking these alterations to behavioral and psychological adaptations (interaction effect with postpartum time: uncorrected p < 0.05). In contrast, the initially reduced whole-brain connectivity of putamen-centered subcortical areas returned to control levels within six to nine weeks postpartum (linear and quadratic mixed linear models: pFDR < 0.05). The whole-brain spatial colocalization with hormone receptor distributions (Spearman correlations: pFDR < 0.05) and preliminary blood hormone associations (interaction effect with postpartum time: uncorrected p < 0.05) suggested that the postpartum restoration of progesterone levels may underlie this rapid normalization. These observations enhance our understanding of healthy maternal brain function, contributing to the identification of potential markers for pathological postpartum adaptation processes, which in turn could underlie postpartum psychiatric disorders.
Tumor biomarkers for diagnosis, prognosis and targeted therapy
Authors: Zhou Yue , Tao Lei , Qiu Jiahao , Xu Jing , Yang Xinyu , Zhang Yu , Tian Xinyu , Guan Xinqi , Cen Xiaobo , Zhao Yinglan
Published: May 2024

Tumor biomarkers, the substances which are produced by tumors or the body’s responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.
Hyperpure chlorine dioxide versus chlorhexidine in intra-oral halitosis (ODOR trial) – protocol of a double-blinded, double-arm, parallel non-inferiority pilot randomized controlled trial
Authors: Szalai Eszter Ágnes , Teutsch Brigitta , Babay Viktória , Galvács Adél , Hegyi Péter , Hársfalvi Péter , Pál Róbert , Varga Gábor , Lohinai Zsolt M. , Kerémi Beáta
Published: May 2024

Introduction

Intra-oral halitosis (IOH) is the most common type of bad breath; its consequences impair quality of life. However, evidence-based treatment protocols and guidelines are lacking. Our aim is to investigate the effectiveness of chlorine dioxide as an applicable complementary treatment modality in IOH after tongue cleaning.

Methods and analysis

The ODOR trial will be a single-center, double-blinded, parallel-group, double-armed pilot randomized controlled trial with a non-inferiority design. The efficacy of hyperpure chlorine dioxide will be compared to chlorhexidine mouthwash. We plan to investigate the short-term effects of the intervention over a 3-h period. The primary endpoint will be changes in organoleptic test scores. At the end of the pilot investigation of the first 30 patients each, sample size calculation will be performed. If feasible, the investigators will continue the study by enrolling more patients.

Trial registration

The trial has been registered at ClinicalTrials.gov (NCT06219226).
CDK9 inhibition as an effective therapy for small cell lung cancer
Authors: Valdez Capuccino L. , Kleitke T. , Szokol B. , Svajda L. , Martin F. , Bonechi F. , Krekó M. , Azami S. , Montinaro A. , Wang Y. , Nikolov V. , Kaiser L. , Bonasera D. , Saggau J. , Scholz T. , Schmitt A. , Beleggia F. , Reinhardt H. C. , George J. , Liccardi G. , Walczak H. , Tóvári J. , Brägelmann J. , Montero J. , Sos M. L. , Őrfi L. , Peltzer N.
Published: May 2024

Treatment-naïve small cell lung cancer (SCLC) is typically susceptible to standard-of-care chemotherapy consisting of cisplatin and etoposide recently combined with PD-L1 inhibitors. Yet, in most cases, SCLC patients develop resistance to first-line therapy and alternative therapies are urgently required to overcome this resistance. In this study, we tested the efficacy of dinaciclib, an FDA-orphan drug and inhibitor of the cyclin-dependent kinase (CDK) 9, among other CDKs, in SCLC. Furthermore, we report on a newly developed, highly specific CDK9 inhibitor, VC-1, with tumour-killing activity in SCLC. CDK9 inhibition displayed high killing potential in a panel of mouse and human SCLC cell lines. Mechanistically, CDK9 inhibition led to a reduction in MCL-1 and cFLIP anti-apoptotic proteins and killed cells, almost exclusively, by intrinsic apoptosis. While CDK9 inhibition did not synergise with chemotherapy, it displayed high efficacy in chemotherapy-resistant cells. In vivo, CDK9 inhibition effectively reduced tumour growth and improved survival in both autochthonous and syngeneic SCLC models. Together, this study shows that CDK9 inhibition is a promising therapeutic agent against SCLC and could be applied to chemo-refractory or resistant SCLC.
Information-based TMS to mid-lateral prefrontal cortex disrupts action goals during emotional processing
Authors: Lapate R. C. , Heckner M. K. , Phan A. T. , Tambini A. , D’Esposito M.
Published: May 2024

The ability to respond to emotional events in a context-sensitive and goal-oriented manner is essential for adaptive functioning. In models of behavioral and emotion regulation, the lateral prefrontal cortex (LPFC) is postulated to maintain goal-relevant representations that promote cognitive control, an idea rarely tested with causal inference. Here, we altered mid-LPFC function in healthy individuals using a putatively inhibitory brain stimulation protocol (continuous theta burst; cTBS), followed by fMRI scanning. Participants performed the Affective Go/No-Go task, which requires goal-oriented action during affective processing. We targeted mid-LPFC (vs. a Control site) based on the individualized location of action-goal representations observed during the task. cTBS to mid-LPFC reduced action-goal representations in mid-LPFC and impaired goal-oriented action, particularly during processing of negative emotional cues. During negative-cue processing, cTBS to mid-LPFC reduced functional coupling between mid-LPFC and nodes of the default mode network, including frontopolar cortex—a region thought to modulate LPFC control signals according to internal states. Collectively, these results indicate that mid-LPFC goal-relevant representations play a causal role in governing context-sensitive cognitive control during emotional processing.
Elevated Na is a dynamic and reversible modulator of mitochondrial metabolism in the heart
Authors: Chung Yu Jin , Hoare Zoe , Baark Friedrich , Yu Chak Shun , Guo Jia , Fuller William , Southworth Richard , Katschinski Doerthe M. , Murphy Michael P. , Eykyn Thomas R. , Shattock Michael J.
Published: May 2024

Elevated intracellular sodium Nai adversely affects mitochondrial metabolism and is a common feature of heart failure. The reversibility of acute Na induced metabolic changes is evaluated in Langendorff perfused rat hearts using the Na/K ATPase inhibitor ouabain and the myosin-uncoupler para-aminoblebbistatin to maintain constant energetic demand. Elevated Nai decreases Gibb’s free energy of ATP hydrolysis, increases the TCA cycle intermediates succinate and fumarate, decreases ETC activity at Complexes I, II and III, and causes a redox shift of CoQ to CoQH2, which are all reversed on lowering Nai to baseline levels. Pseudo hypoxia and stabilization of HIF-1α is observed despite normal tissue oxygenation. Inhibition of mitochondrial Na/Ca-exchange with CGP-37517 or treatment with the mitochondrial ROS scavenger MitoQ prevents the metabolic alterations during Nai elevation. Elevated Nai plays a reversible role in the metabolic and functional changes and is a novel therapeutic target to correct metabolic dysfunction in heart failure.
Heuristics in risky decision-making relate to preferential representation of information
Authors: Russek Evan M. , Moran Rani , Liu Yunzhe , Dolan Raymond J. , Huys Quentin J. M.
Published: May 2024

When making choices, individuals differ from one another, as well as from normativity, in how they weigh different types of information. One explanation for this relates to idiosyncratic preferences in what information individuals represent when evaluating choice options. Here, we test this explanation with a simple risky-decision making task, combined with magnetoencephalography (MEG). We examine the relationship between individual differences in behavioral markers of information weighting and neural representation of stimuli pertinent to incorporating that information. We find that the extent to which individuals (N = 19) behaviorally weight probability versus reward information is related to how preferentially they neurally represent stimuli most informative for making probability and reward comparisons. These results are further validated in an additional behavioral experiment (N = 88) that measures stimulus representation as the latency of perceptual detection following priming. Overall, the results suggest that differences in the information individuals consider during choice relate to their risk-taking tendencies.
Homozygous EPRS1 missense variant causing hypomyelinating leukodystrophy-15 alters variant-distal mRNA m6A site accessibility
Authors: Khan Debjit , Ramachandiran Iyappan , Vasu Kommireddy , China Arnab , Khan Krishnendu , Cumbo Fabio , Halawani Dalia , Terenzi Fulvia , Zin Isaac , Long Briana , Costain Gregory , Blaser Susan , Carnevale Amanda , Gogonea Valentin , Dutta Ranjan , Blankenberg Daniel , Yoon Grace , Fox Paul L.
Published: May 2024

Hypomyelinating leukodystrophy (HLD) is an autosomal recessive disorder characterized by defective central nervous system myelination. Exome sequencing of two siblings with severe cognitive and motor impairment and progressive hypomyelination characteristic of HLD revealed homozygosity for a missense single-nucleotide variant (SNV) in EPRS1 (c.4444 C > A; p.Pro1482Thr), encoding glutamyl-prolyl-tRNA synthetase, consistent with HLD15. Patient lymphoblastoid cell lines express markedly reduced EPRS1 protein due to dual defects in nuclear export and cytoplasmic translation of variant EPRS1 mRNA. Variant mRNA exhibits reduced METTL3 methyltransferase-mediated writing of N6-methyladenosine (m6A) and reduced reading by YTHDC1 and YTHDF1/3 required for efficient mRNA nuclear export and translation, respectively. In contrast to current models, the variant does not alter the sequence of m6A target sites, but instead reduces their accessibility for modification. The defect was rescued by antisense morpholinos predicted to expose m6A sites on target EPRS1 mRNA, or by m6A modification of the mRNA by METTL3-dCas13b, a targeted RNA methylation editor. Our bioinformatic analysis predicts widespread occurrence of SNVs associated with human health and disease that similarly alter accessibility of distal mRNA m6A sites. These results reveal a new RNA-dependent etiologic mechanism by which SNVs can influence gene expression and disease, consequently generating opportunities for personalized, RNA-based therapeutics targeting these disorders.
Concentration-induced spontaneous polymerization of protic ionic liquids for efficient in situ adhesion
Authors: Zhang Jun , Zhou Xuan , Hu Qinyu , Zhou Kaijian , Zhang Yan , Dong Shengyi , Zhao Gai , Zhang Shiguo
Published: May 2024

The advancement of contemporary adhesives is often limited by the balancing act between cohesion and interfacial adhesion strength. This study explores an approach to overcome this trade-off by utilizing the spontaneous polymerization of a protic ionic liquid-based monomer obtained through the neutralization of 2-acrylamide-2-methyl propane sulfonic acid and hydroxylamine. The initiator-free polymerization process is carried out through a gradual increase in monomer concentration in aqueous solutions caused by solvent evaporation upon heating, which results in the in-situ formation of a tough and thin adhesive layer with a highly entangled polymeric network and an intimate interface contact between the adhesive and substrate. The abundance of internal and external non-covalent interactions also contributes to both cohesion and interfacial adhesion. Consequently, the produced protic poly(ionic liquid)s exhibit considerable adhesion strength on a variety of substrates. This method also allows for the creation of advanced adhesive composites with electrical conductivity or visualized sensing functionality by incorporating commercially available fillers into the ionic liquid adhesive. This study provides a strategy for creating high-performance ionic liquid-based adhesives and highlights the importance of in-situ polymerization for constructing adhesive composites.
New insight into tuning magnetic phases of RMn6Sn6 kagome metals
Authors: Riberolles S. X. M. , Han Tianxiong , Slade Tyler J. , Wilde J. M. , Sapkota A. , Tian Wei , Zhang Qiang , Abernathy D. L. , Sanjeewa L. D. , Bud’ko S. L. , Canfield P. C. , McQueeney R. J. , Ueland B. G.
Published: May 2024

Predicting magnetic ordering in kagome compounds offers the possibility of harnessing topological or flat-band physical properties through tuning of the magnetism. Here, we examine the magnetic interactions and phases of ErMn6Sn6 which belongs to a family of RMn6Sn6, R = Sc, Y, Gd–Lu, compounds with magnetic kagome Mn layers, triangular R layers, and signatures of topological properties. Using results from single-crystal neutron diffraction and mean-field analysis, we find that ErMn6Sn6 sits close to the critical boundary separating the spiral-magnetic and ferrimagnetic ordered states typical for non-magnetic versus magnetic R layers, respectively. Finding interlayer magnetic interactions and easy-plane Mn magnetic anisotropy consistent with other members of the family, we predict the existence of a number of temperature and field dependent collinear, noncollinear, and noncoplanar magnetic phases. We show that thermal fluctuations of the Er magnetic moment, which act to weaken the Mn-Er interlayer magnetic interaction and quench the Er magnetic anisotropy, dictate magnetic phase stability. Our results provide a starting point and outline a multitude of possibilities for studying the behavior of Dirac fermions in RMn6Sn6 compounds with control of the Mn spin orientation and real-space spin chirality.
A replicating RNA vaccine confers protection in a rhesus macaque model of Crimean-Congo hemorrhagic fever
Authors: Hawman David W. , Leventhal Shanna S. , Meade-White Kimberly , Khandhar Amit , Murray Justin , Lovaglio Jamie , Shaia Carl , Saturday Greg , Hinkley Troy , Erasmus Jesse , Feldmann Heinz
Published: May 2024

Crimean-Congo hemorrhagic fever (CCHF) is a tick-borne febrile illness with a wide geographic distribution. In recent years the geographic range of Crimean-Congo hemorrhagic fever virus (CCHFV) and its tick vector have increased, placing an increasing number of people at risk of CCHFV infection. Currently, there are no widely available vaccines, and although the World Health Organization recommends ribavirin for treatment, its efficacy is unclear. Here we evaluate a promising replicating RNA vaccine in a rhesus macaque (Macaca mulatta) model of CCHF. This model provides an alternative to the established cynomolgus macaque model and recapitulates mild-to-moderate human disease. Rhesus macaques infected with CCHFV consistently exhibit viremia, detectable viral RNA in a multitude of tissues, and moderate pathology in the liver and spleen. We used this model to evaluate the immunogenicity and protective efficacy of a replicating RNA vaccine. Rhesus macaques vaccinated with RNAs expressing the CCHFV nucleoprotein and glycoprotein precursor developed robust non-neutralizing humoral immunity against the CCHFV nucleoprotein and had significant protection against the CCHFV challenge. Together, our data report a model of CCHF using rhesus macaques and demonstrate that our replicating RNA vaccine is immunogenic and protective in non-human primates after a prime-boost immunization.
Antibody-displaying extracellular vesicles for targeted cancer therapy
Authors: Wiklander Oscar P. B. , Mamand Doste R. , Mohammad Dara K. , Zheng Wenyi , Jawad Wiklander Rim , Sych Taras , Zickler Antje M. , Liang Xiuming , Sharma Heena , Lavado Andrea , Bost Jeremy , Roudi Samantha , Corso Giulia , Lennaárd Angus J. , Abedi-Valugerdi Manuchehr , Mäger Imre , Alici Evren , Sezgin Erdinc , Nordin Joel Z. , Gupta Dhanu , Görgens André , EL Andaloussi Samir
Published: May 2024

Extracellular vesicles (EVs) function as natural delivery vectors and mediators of biological signals across tissues. Here, by leveraging these functionalities, we show that EVs decorated with an antibody-binding moiety specific for the fragment crystallizable (Fc) domain can be used as a modular delivery system for targeted cancer therapy. The Fc-EVs can be decorated with different types of immunoglobulin G antibody and thus be targeted to virtually any tissue of interest. Following optimization of the engineered EVs by screening Fc-binding and EV-sorting moieties, we show the targeting of EVs to cancer cells displaying the human epidermal receptor 2 or the programmed-death ligand 1, as well as lower tumour burden and extended survival of mice with subcutaneous melanoma tumours when systemically injected with EVs displaying an antibody for the programmed-death ligand 1 and loaded with the chemotherapeutic doxorubicin. EVs with Fc-binding domains may be adapted to display other Fc-fused proteins, bispecific antibodies and antibody–drug conjugates.
Estimation of useful-stage energy returns on investment for fossil fuels and implications for renewable energy systems
Authors: Aramendia Emmanuel , Brockway Paul E. , Taylor Peter G. , Norman Jonathan B. , Heun Matthew K. , Marshall Zeke
Published: May 2024

The net energy implications of the energy transition have so far been analysed at best at the final energy stage. Here we argue that expanding the analysis to the useful stage is crucial. We estimate fossil fuelsʼ useful-stage energy returns on investment (EROIs) over the period 1971–2020, globally and nationally, and disaggregate EROIs by end use. We find that fossil fuelsʼ useful-stage EROIs (~3.5:1) are considerably lower than at the final stage (~8.5:1), due to low final-to-useful efficiencies. Further, we estimate the final-stage EROI for which electricity-yielding renewable energy would deliver the same net useful energy as fossil fuels (EROI equivalent) to be approximately 4.6:1. The EROIs of electricity-yielding renewable energy systems, based on published estimations, are found to be higher than the determined EROI equivalent, even considering the effects of intermittency under a range of energy transition scenarios. Results suggest that the energy transition may happen without a decline in net useful energy, countering the view that renewable energy systems cannot replace fossil fuels without incurring a substantial energy penalty.
Testing theory of mind in large language models and humans
Authors: Strachan James W. A. , Albergo Dalila , Borghini Giulia , Pansardi Oriana , Scaliti Eugenio , Gupta Saurabh , Saxena Krati , Rufo Alessandro , Panzeri Stefano , Manzi Guido , Graziano Michael S. A. , Becchio Cristina
Published: May 2024

At the core of what defines us as humans is the concept of theory of mind: the ability to track other people’s mental states. The recent development of large language models (LLMs) such as ChatGPT has led to intense debate about the possibility that these models exhibit behaviour that is indistinguishable from human behaviour in theory of mind tasks. Here we compare human and LLM performance on a comprehensive battery of measurements that aim to measure different theory of mind abilities, from understanding false beliefs to interpreting indirect requests and recognizing irony and faux pas. We tested two families of LLMs (GPT and LLaMA2) repeatedly against these measures and compared their performance with those from a sample of 1,907 human participants. Across the battery of theory of mind tests, we found that GPT-4 models performed at, or even sometimes above, human levels at identifying indirect requests, false beliefs and misdirection, but struggled with detecting faux pas. Faux pas, however, was the only test where LLaMA2 outperformed humans. Follow-up manipulations of the belief likelihood revealed that the superiority of LLaMA2 was illusory, possibly reflecting a bias towards attributing ignorance. By contrast, the poor performance of GPT originated from a hyperconservative approach towards committing to conclusions rather than from a genuine failure of inference. These findings not only demonstrate that LLMs exhibit behaviour that is consistent with the outputs of mentalistic inference in humans but also highlight the importance of systematic testing to ensure a non-superficial comparison between human and artificial intelligences.
A dynamic probabilistic model of the onset and interaction of cardio-metabolic comorbidities on an ageing adult population
Authors: Roversi Chiara , Tavazzi Erica , Vettoretti Martina , Di Camillo Barbara
Published: May 2024

Comorbidity is widespread in the ageing population, implying multiple and complex medical needs for individuals and a public health burden. Determining risk factors and predicting comorbidity development can help identify at-risk subjects and design prevention strategies. Using socio-demographic and clinical data from approximately 11,000 subjects monitored over 11 years in the English Longitudinal Study of Ageing, we develop a dynamic Bayesian network (DBN) to model the onset and interaction of three cardio-metabolic comorbidities, namely type 2 diabetes (T2D), hypertension, and heart problems. The DBN allows us to identify risk factors for developing each morbidity, simulate ageing progression over time, and stratify the population based on the risk of outcome occurrence. By applying hierarchical agglomerative clustering to the simulated, dynamic risk of experiencing morbidities, we identified patients with similar risk patterns and the variables contributing to their discrimination. The network reveals a direct joint effect of biomarkers and lifestyle on outcomes over time, such as the impact of fasting glucose, HbA1c, and BMI on T2D development. Mediated cross-relationships between comorbidities also emerge, showcasing the interconnected nature of these health issues. The model presents good calibration and discrimination ability, particularly in predicting the onset of T2D (iAUC-ROC = 0.828, iAUC-PR = 0.294) and survival (iAUC-ROC = 0.827, iAUC-PR = 0.311). Stratification analysis unveils two distinct clusters for all comorbidities, effectively discriminated by variables like HbA1c for T2D and age at baseline for heart problems. The developed DBN constitutes an effective, highly-explainable predictive risk tool for simulating and stratifying the dynamic risk of developing cardio-metabolic comorbidities. Its use could help identify the effects of risk factors and develop health policies that prevent the occurrence of comorbidities.
Fuzzy analytic hierarchy process based generation management for interconnected power system
Authors: Varshney T. , Waghmare A. V. , Singh V. P. , Meena V. P. , Anand R , Khan Baseem
Published: May 2024

Decision makers consistently face the challenge of simultaneously assessing numerous attributes, determining their respective importance, and selecting an appropriate method for calculating their weights. This article addresses the problem of automatic generation control (AGC) in a two area power system (2-APS) by proposing fuzzy analytic hierarchy process (FAHP), an multi-attribute decision-making (MADM) technique, to determine weights for sub-objective functions. The integral-time-absolute-errors (ITAE) of tie-line power fluctuation, frequency deviations and area control errors, are defined as the sub-objectives. Each of these is given a weight by the FAHP method, which then combines them into an single final objective function. This objective function is then used to design a PID controller. To improve the optimization of the objective function, the Jaya optimization algorithm (JOA) is used in conjunction with other optimization techniques such as sine cosine algorithm (SCA), Luus–Jaakola algorithm (LJA), Nelder–Mead simplex algorithm (NMSA), symbiotic organism search algorithm (SOSA) and elephant herding optimization algorithm (EHOA). Six distinct experimental cases are conducted to evaluate the controller’s performance under various load conditions, with data plotted to show responses corresponding to fluctuations in frequency and tie-line exchange. Furthermore, statistical analysis is performed to gain a better understanding of the effectiveness of the JOA-based PID controller. For non-parametric evaluation, Friedman rank test is also used to validate the performance of the proposed JOA-based controller.
The analysis of pedestrian flow in the smart city by improved DWA with robot assistance
Authors: Hu Yingyue , Long Huizhen , Chen Min
Published: May 2024

With the acceleration of urbanization in China, the urban population continues to grow, leading to frequent occurrences of crowded public spaces, which in turn trigger traffic congestion and even safety accidents. In order to more effectively control pedestrian flow, enhance the efficiency and safety of public spaces, this experiment conducts in-depth research and improvement on the traditional Dynamic Window Approach (DWA), and applies it to the fine control of pedestrian flow. Specifically, this study comprehensively reviews and analyzes the characteristics of pedestrian traffic flow and the working principles of traditional DWA. Based on this, the shortcomings of traditional DWA in dealing with complex pedestrian flow scenarios are identified, and targeted improvement solutions are proposed. The core of this improvement scheme lies in the introduction of a new evaluation function, enabling DWA to more accurately balance various factors in the decision-making process, including pedestrian movement speed, direction, and spatial distribution. Subsequently, the improved DWA is validated through simulation experiments. The experimental scenario is set in an area of 18 m*18 m, and compared with traditional DWA, the improved DWA shows significant advantages in trajectory length and travel time. Specifically, the trajectory length of the traditional DWA robot is 19.4 m, with a required time of 34.8 s, while the trajectory length of the improved DWA robot is shortened to 18.7 m, and the time is reduced to 18.6 s. This result fully demonstrates the effectiveness of the improved DWA in optimizing pedestrian flow control. The improved DWA proposed in this study not only has strong scientific validity but also demonstrates high efficiency in practical applications. This study has important reference value for improving the safety of urban public spaces and improving pedestrian traffic flow conditions, and provides new ideas for the further development of pedestrian flow control technology in the future.
A 3D printed esophageal atresia–tracheoesophageal fistula thorascopy simulator for young surgeons
Authors: Youn Joong Kee , Ko Dayoung , Yang Hee-Beom , Kim Hyun-Young
Published: May 2024

We developed a 3D-printed thoracoscopic surgery simulator for esophageal atresia with tracheoesophageal fistula (EA-TEF) and assessed its effectiveness in educating young pediatric surgeons. Prototype production and modifications were repeated five times before producing the 3-D printed final product based on a patient’s preoperative chest computed tomography. A 24-item survey was used to rate the simulator, adapted from a previous report, with 16 young surgeons with an average of 6.2 years of experience in pediatric surgery for validation. Reusable parts of the thoracic cage were printed to combine with replaceable parts. Each structure was fabricated using diverse printing materials, and subsequently affixed to a frame. In evaluating the simulator, the scores for each factor were 4.33, 4.33, 4.27, 4.31, 4.63, and 4.75 out of 5, respectively, with the highest ratings in value and relevance. The global rating was 3.38 out of 4, with ten stating that it could be used with slight improvements. The most common comment from participants was that the esophageal anastomosis was close to the actual EA-TEF surgery. The 3D-printed thoracoscopic EA-TEF surgery simulator was developed and reflected the actual surgical environment. It could become an effective method of training young pediatric surgeons.
Feasibility of decoding covert speech in ECoG with a Transformer trained on overt speech
Authors: Komeiji Shuji , Mitsuhashi Takumi , Iimura Yasushi , Suzuki Hiroharu , Sugano Hidenori , Shinoda Koichi , Tanaka Toshihisa
Published: May 2024

Several attempts for speech brain–computer interfacing (BCI) have been made to decode phonemes, sub-words, words, or sentences using invasive measurements, such as the electrocorticogram (ECoG), during auditory speech perception, overt speech, or imagined (covert) speech. Decoding sentences from covert speech is a challenging task. Sixteen epilepsy patients with intracranially implanted electrodes participated in this study, and ECoGs were recorded during overt speech and covert speech of eight Japanese sentences, each consisting of three tokens. In particular, Transformer neural network model was applied to decode text sentences from covert speech, which was trained using ECoGs obtained during overt speech. We first examined the proposed Transformer model using the same task for training and testing, and then evaluated the model’s performance when trained with overt task for decoding covert speech. The Transformer model trained on covert speech achieved an average token error rate (TER) of 46.6% for decoding covert speech, whereas the model trained on overt speech achieved a TER of 46.3% $$( p > 0.05; d=0.07)$$

(
p
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0.05
;
d
=
0.07
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. Therefore, the challenge of collecting training data for covert speech can be addressed using overt speech. The performance of covert speech can improve by employing several overt speeches.
Novel inflammatory and insulin resistance indices provide a clue in cerebral amyloid angiopathy
Authors: Zhu Hang-hang , Wang Yun-chao , He Liu-chang , Luo Hai-yang , Zong Ce , Yang Ying-hao , Wu Jing-Hao , Song Bo , Gao Yuan , Xu Yu-ming , Li Yu-sheng
Published: May 2024

This study investigated the correlation of newly identified inflammatory and insulin resistance indices with cerebral amyloid angiopathy (CAA), and explored their potential to differentiate CAA from hypertensive arteriopathy (HA). We retrospectively analyzed 514 consecutive patients with cerebral small vessel disease (CSVD)-related haemorrhage, comparing the differences in novel inflammatory and insulin resistance indices between patients with CAA and HA. Univariate regression, LASSO and multivariate regression were used to screen variables and construct a classification diagnosis nomogram. Additionally, these biomarkers were explored in patients with mixed haemorrhagic CSVD. Inflammatory indices were higher in CAA patients, whereas insulin resistance indices were higher in HA patients. Further analysis identified neutrophil-to-lymphocyte ratio (NLR, OR 1.17, 95% CI 1.07–1.30, P < 0.001), and triglyceride–glucose index (TyG, OR = 0.56, 95% CI 0.36–0.83, P = 0.005) as independent factors for CAA. Therefore, we constructed a CAA prediction nomogram without haemorrhagic imaging markers. The nomogram yielded an area under the curve (AUC) of 0.811 (95% CI 0.764–0.865) in the training set and 0.830 (95% CI 0.718–0.887) in the test set, indicating an ability to identify high-risk CAA patients. These results show that CSVD patients can be phenotyped using novel inflammatory and insulin resistance indices, potentially allowing identification of high-risk CAA patients without haemorrhagic imaging markers.
Time division multiplexing based multi-spectral semantic camera for LiDAR applications
Authors: Kim Sehyeon , Jeong Tae-In , Kim San , Choi Eunji , Yang Eunju , Song Munki , Eom Tae Joong , Kim Chang-Seok , Gliserin Alexander , Kim Seungchul
Published: May 2024

The recent progress in the development of measurement systems for autonomous recognition had a substantial impact on emerging technology in numerous fields, especially robotics and automotive applications. In particular, time-of-flight (TOF) based light detection and ranging (LiDAR) systems enable to map the surrounding environmental information over long distances and with high accuracy. The combination of advanced LiDAR with an artificial intelligence platform allows enhanced object recognition and classification, which however still suffers from limitations of inaccuracy and misidentification. Recently, multi-spectral LiDAR systems have been employed to increase the object recognition performance by additionally providing material information in the short-wave infrared (SWIR) range where the reflection spectrum characteristics are typically very sensitive to material properties. However, previous multi-spectral LiDAR systems utilized band-pass filters or complex dispersive optical systems and even required multiple photodetectors, adding complexity and cost. In this work, we propose a time-division-multiplexing (TDM) based multi-spectral LiDAR system for semantic object inference by the simultaneous acquisition of spatial and spectral information. By utilizing the TDM method, we enable the simultaneous acquisition of spatial and spectral information as well as a TOF based distance map with minimized optical loss using only a single photodetector. Our LiDAR system utilizes nanosecond pulses of five different wavelengths in the SWIR range to acquire sufficient material information in addition to 3D spatial information. To demonstrate the recognition performance, we map the multi-spectral image from a human hand, a mannequin hand, a fabric gloved hand, a nitrile gloved hand, and a printed human hand onto an RGB-color encoded image, which clearly visualizes spectral differences as RGB color depending on the material while having a similar shape. Additionally, the classification performance of the multi-spectral image is demonstrated with a convolution neural network (CNN) model using the full multi-spectral data set. Our work presents a compact novel spectroscopic LiDAR system, which provides increased recognition performance and thus a great potential to improve safety and reliability in autonomous driving.
Addition of anterolateral ligament reconstruction to primary anterior cruciate ligament reconstruction could benefit recovery of functional outcomes
Authors: Lee Jin Hyuck , Lee Gyu Bin , Chung WooYong , Han Seung-Beom , Jang Ki-Mo
Published: May 2024

This study aimed to compare functional outcomes sequentially up to 1 year after combined anterior cruciate ligament reconstruction (ACLR) and anterolateral ligament reconstruction (ALLR) and isolated ACLR. Fifty patients who underwent ACLR with versus without ALLR were analyzed at four different time points (preoperatively and 3, 6, and 12 months postoperatively). For the functional outcomes, muscle strength and acceleration time (AT) were measured using an isokinetic dynamometer. Proprioception was evaluated using joint position sense and dynamic postural stability. Patient-reported outcomes were measured using the Tampa Scale for Kinesiophobia (TSK-11) scores. Functional performance was assessed using single-leg hop distance (SLHD) and Limb Symmetry Index. In the operated knees, quadriceps (at 6 months postoperatively, p = 0.003) and hamstring (at 6 and 12 months postoperatively, p < 0.001) strength were significantly higher in the combined ACLR and ALLR group than the isolated ACLR group. The TSK-11 (at 6 and 12 months postoperatively, p < 0.001) was significantly lower in the combined ACLR and ALLR group than the isolated ACLR group. SLHD was significantly higher in the combined ACLR and ALLR group than the isolated ACLR group (at 6 months, p = 0.022 and at 12 months, p = 0.024). The addition of ALLR to primary ACLR yielded better muscle performance, fear of movement, and functional performance than isolated ACLR.
A novel anti-loosening bolt looseness diagnosis of bolt connections using a vision-based technique
Authors: Luo Jun , Li Kaili , Xie ChengQian , Yan Zhitao , Li Feng , Jia Xiaogang , Wang Yuanlai
Published: May 2024

Bolt looseness detection is a common problem in engineering. Most vision-based detection techniques focus on diagnosing ordinary bolt looseness, i.e., the methods used for diagnosis are based only on the sidelines of nuts. These methods cannot be used for anti-loosening bolt looseness diagnosis because of the simultaneous rotation of screws and nuts. Therefore, a novel anti-loosening bolt looseness diagnosis method based on a vision-based technique is proposed in this paper. First, a regular hexagonal cap was installed on the screw, which can be used as a reference for the nut. Then, to automatically distinguish the hexagonal borders of the screw cap and nut, a new hexagonal border reconstruction algorithm is proposed. Furthermore, the relative rotation angles of the screw cap and nut hexagons can be determined using the sidelines of the reconstructed hexagonal borders of the screw cap and nut. Finally, a novel anti-loosening bolt looseness diagnosis method is established by using the relative rotation angle of the regular hexagonal borders of the screw cap and nut under initial status and loose status. A prototype flange node of the transmission tower was used for experimental verification. The results show that the proposed method can effectively detect the loosening angle of anti-loosening bolts.
Multiomics integration reveals NETosis heterogeneity and TLR2 as a prognostic biomarker in pancreatic cancer
Authors: Fu Yifan , Tao Jinxin , Gu Yani , Liu Yueze , Qiu Jiangdong , Su Dan , Wang Ruobing , Luo Wenhao , Liu Tao , Zhang Feifan , Zhang Taiping , Zhao Yupei
Published: May 2024

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant neoplasm characterized by a poor prognosis and limited therapeutic strategy. The PDAC tumor microenvironment presents a complex heterogeneity, where neutrophils emerge as the predominant constituents of the innate immune cell population. Leveraging the power of single-cell RNA-seq, spatial RNA-seq, and multi-omics approaches, we included both published datasets and our in-house patient cohorts, elucidating the inherent heterogeneity in the formation of neutrophil extracellular traps (NETs) and revealed the correlation between NETs and immune suppression. Meanwhile, we constructed a multi-omics prognostic model that suggested the patients exhibiting downregulated expression of NETs may have an unfavorable outcome. We also confirmed TLR2 as a potent prognosis factor and patients with low TLR2 expression had more effective T cells and an overall survival extension for 6 months. Targeting TLR2 might be a promising strategy to reverse immunosuppression and control tumor progression for an improved prognosis.
Immunophenotyping with (phospho)protein profiling and fluorescent cell barcoding for single-cell signaling analysis and biomarker discovery
Authors: Hermansen Johanne U. , Yin Yanping , Rein Idun Dale , Skånland Sigrid S.
Published: May 2024

The microenvironment of hematologic cancers contributes to tumor cell survival and proliferation, as well as treatment resistance. Understanding tumor- and drug-induced changes to the immune cell composition and functionality is therefore critical for implementing optimal treatment strategies and for the development of novel cancer therapies. The liquid nature of peripheral blood makes this organ uniquely suited for single-cell studies by flow cytometry. (Phospho)protein profiles detected by flow cytometry analyses have been shown to correlate with ex vivo drug sensitivity and to predict treatment outcomes in hematologic cancers, demonstrating that this method is suitable for pre-clinical studies. Here, we present a flow cytometry protocol that combines multi-parameter immunophenotyping with single-cell (phospho)protein profiling. The protocol makes use of fluorescent cell barcoding, which means that multiple cell samples, either collected from different donors or exposed to different treatment conditions, can be combined and analyzed as one experiment. This reduces variability between samples, increases the throughput of the experiment, and lowers experimental costs. This protocol may serve as a guide for the use and further development of assays to study immunophenotype and cell signaling at single-cell resolution in normal and malignant cells. The read-outs may provide biological insight into cancer pathogenesis, identify novel drug targets, and ultimately serve as a biomarker to guide clinical decision-making.