bluuebunny/crossref_metadata_2025 huggingface dataset:
Isocitrate dehydrogenase 2 regulates the proliferation of triple-negative breast cancer through the ferroptosis pathway
Authors: Zhang Chengwu , Zhou Yuanhong , Chen Tao , Bhushan Sudhanshu , Sun Shengrong , Zhang Panshi , Yang Yalong
Published: February 2024

Triple-negative breast cancer (TNBC) is currently the type of breast cancer with the worst prognosis; it lacks specific treatments, such as ER/PR antagonistic endocrine and anti-HER2 targeted therapies. Although immunotherapy with immune checkpoints has shown some efficacy in many solid tumors, clinical data in TNBC suggest significant limitations. The essence of ferroptosis is the impaired metabolism of intracellular lipid oxides, which in turn causes the activation and abnormalities of the immune system, including ROS, and not only plays an important role in liver injury and organ aging but also a large amount of data points to the close correlation between the ferroptosis process and tumor development. In this study, through the analysis of large-throughput biological data of breast tumors, combined with the characteristics of the biological process of ferroptosis, the specific gene IDH2 was found to be significantly highly expressed in TNBC and functionally correlated with ferroptosis. Through clinical specimens validated at the gene and protein levels, in vitro tumor cell line validation, and in vivo mouse models, we found that the high expression of IDH2 in TNBC has a role in inhibiting the ferroptosis process in TNBC, thus promoting the proliferation of TNBC cells and other malignant features.
Enhancing two-stage object detection models via data-driven anchor box optimization in UAV-based maritime SAR
Authors: Zhao Beigeng , Song Rui
Published: February 2024

The high-altitude imaging capabilities of Unmanned Aerial Vehicles (UAVs) offer an effective solution for maritime Search and Rescue (SAR) operations. In such missions, the accurate identification of boats, personnel, and objects within images is crucial. While object detection models trained on general image datasets can be directly applied to these tasks, their effectiveness is limited due to the unique challenges posed by the specific characteristics of maritime SAR scenarios. Addressing this challenge, our study leverages the large-scale benchmark dataset SeaDronesSee, specific to UAV-based maritime SAR, to analyze and explore the unique attributes of image data in this scenario. We identify the need for optimization in detecting specific categories of difficult-to-detect objects within this context. Building on this, an anchor box optimization strategy is proposed based on clustering analysis, aimed at enhancing the performance of the renowned two-stage object detection models in this specialized task. Experiments were conducted to validate the proposed anchor box optimization method and to explore the underlying reasons for its effectiveness. The experimental results show our optimization method achieved a 45.8% and a 10% increase in average precision over the default anchor box configurations of torchvision and the SeaDronesSee official sample code configuration respectively. This enhancement was particularly evident in the model’s significantly improved ability to detect swimmers, floaters, and life jackets on boats within the SeaDronesSee dataset’s SAR scenarios. The methods and findings of this study are anticipated to provide the UAV-based maritime SAR research community with valuable insights into data characteristics and model optimization, offering a meaningful reference for future research.
A functional personalised oncology approach against metastatic colorectal cancer in matched patient derived organoids
Authors: Thng Dexter Kai Hao , Hooi Lissa , Siew Bei En , Lee Kai-Yin , Tan Ian Jse-Wei , Lieske Bettina , Lin Norman Sihan , Kow Alfred Wei Chieh , Wang Shi , Rashid Masturah Bte Mohd Abdul , Ang Chermaine , Koh Jasmin Jia Min , Toh Tan Boon , Tan Ker-Kan , Chow Edward Kai-Hua
Published: February 2024

Globally, colorectal cancer (CRC) is the third most frequently occurring cancer. Progression on to an advanced metastatic malignancy (metCRC) is often indicative of poor prognosis, as the 5-year survival rates of patients decline rapidly. Despite the availability of many systemic therapies for the management of metCRC, the long-term efficacies of these regimens are often hindered by the emergence of treatment resistance due to intratumoral and intertumoral heterogeneity. Furthermore, not all systemic therapies have associated biomarkers that can accurately predict patient responses. Hence, a functional personalised oncology (FPO) approach can enable the identification of patient-specific combinatorial vulnerabilities and synergistic combinations as effective treatment strategies. To this end, we established a panel of CRC patient-derived organoids (PDOs) as clinically relevant biological systems, of which three pairs of matched metCRC PDOs were derived from the primary sites (ptCRC) and metastatic lesions (mCRC). Histological and genomic characterisation of these PDOs demonstrated the preservation of histopathological and genetic features found in the parental tumours. Subsequent application of the phenotypic-analytical drug combination interrogation platform, Quadratic Phenotypic Optimisation Platform, in these pairs of PDOs identified patient-specific drug sensitivity profiles to epigenetic-based combination therapies. Most notably, matched PDOs from one patient exhibited differential sensitivity patterns to the rationally designed drug combinations despite being genetically similar. These findings collectively highlight the limitations of current genomic-driven precision medicine in guiding treatment strategies for metCRC patients. Instead, it suggests that epigenomic profiling and application of FPO could complement the identification of novel combinatorial vulnerabilities to target synchronous ptCRC and mCRC.
Zebrafish tumour xenograft models: a prognostic approach to epithelial ovarian cancer
Authors: Lindahl Gabriel , Fjellander Sebastian , Selvaraj Karthik , Vildeval Malin , Ali Zaheer , Almter Rusul , Erkstam Anna , Rodriguez Gabriela Vazquez , Abrahamsson Annelie , Kersley Åsa Rydmark , Fahlgren Anna , Kjølhede Preben , Linder Stig , Dabrosin Charlotta , Jensen Lasse
Published: February 2024

Epithelial ovarian cancer (EOC) is the gynaecological malignancy with highest mortality. Although adjuvant treatment with carboplatin and paclitaxel leads to an objective response in ~80% of these patients, a majority will relapse within two years. Better methods for assessing long-term treatment outcomes are needed. To address this, we established safe and efficacious doses of carboplatin and paclitaxel using IGROV-1 zebrafish-CDX models. Then fluorescently-labelled cell suspensions from 83 tumour biopsies collected at exploratory laparotomy of women with suspected EOC were generated and 37 (45%) were successfully implanted in zebrafish larvae. Among these 19 of 27 pathology-confirmed EOC samples (70%) engrafted. These zebrafish patient-derived tumour xenograft (ZTX) models were treated with carboplatin or paclitaxel and tumour growth/regression and metastatic dissemination were recorded. In a subgroup of nine patients, four ZTX models regressed during carboplatin treatment. All four corresponding patients had >24 months PFS. Furthermore, both ZTX models established from two patients having <24 months PFS failed to regress during carboplatin treatment. Seven of eight models seeding <6 metastatic cells were established from patients having >24 months PFS. In eleven of fourteen patients, FIGO stage I + II or III tumours gave rise to ZTX models seeding <4 or >4 metastatic cells, respectively. In conclusion, ZTX models predicted patients having >24 or <24 months PFS, based on response/no response to carboplatin. Furthermore, high metastatic dissemination in ZTX models correlated to shorter PFS and more advanced disease at diagnosis. These preliminary results suggest that ZTX models could become a useful prognostic tool in EOC treatment planning.
Impact of trauma exposure and depression comorbidity on response to transdiagnostic behavioral therapy for pediatric anxiety and depression
Authors: Angulo Felix , Goger Pauline , Brent David A. , Rozenman Michelle , Gonzalez Araceli , Schwartz Karen T. G. , Porta Giovanna , Lynch Frances L. , Dickerson John F. , Weersing V. Robin
Published: February 2024

By adolescence, two-thirds of youth report exposure to at least one traumatic event, yet the impact of trauma history is not routinely considered when evaluating the effect of psychotherapeutic interventions. Trauma may be a particularly important moderator of the effects of transdiagnostic therapies for emotional disorders, as trauma exposure is associated with risk for the development of comorbid depression and anxiety. The current study examined the history of trauma exposure and the presence of clinically significant depression as moderators of treatment outcomes in the Brief Behavioral Therapy (BBT) trial, the largest study of transdiagnostic psychotherapy for youth. Youths (age 8–16 years) were randomized to BBT (n = 89) based in pediatric primary care or assisted referral to outpatient community care (ARC; n = 86). Clinical response, functioning, anxiety symptoms, and depression symptoms were assessed at post-treatment (Week 16) and at follow-up (Week 32). A significant three-way interaction emerged between the treatment group, comorbid depression, and trauma exposure. BBT was broadly effective for 3/4 of the sample, but, for anxious-depressed youth with trauma exposure, BBT never significantly separated from ARC. Differences in outcome were not accounted for by other participant characteristics or by therapist-rated measures of alliance, youth engagement, or homework completion. Implications for models of learning and for intervention theory and development are discussed.
Evaluation of organo-vermiculites as sorbent phases for solid-phase extraction of ibuprofen from water
Authors: Batista Luis Fernando A. , Gonçalves Sara Renata S. , Bressan Carolina D. , Grassi Marco T. , Abate Gilberto
Published: February 2024

The clay mineral vermiculite was modified using alkylammonium salts to produce the organo-vermiculite (OVT). It was successfully employed for the preconcentration of ibuprofen (IBU) by solid-phase extraction.
Mechanisms of hydrogen evolution by six-coordinate cobalt complexes: a density functional study on the role of a redox-active pyridinyl-substituted diaminotriazine benzamidine ligand as a proton relay
Authors: Thammanatpong Kittimeth , Surawatanawong Panida
Published: February 2024

The proton reduction for hydrogen evolution involves ligand-based reduction in addition to the formation of Co(II)-H. This results in a low acidity of the protonated pyridine moiety of the ligand, which impedes its function as a proton relay.
Ecotoxicity testing of nanomaterials in sediment – suggestions to improve science and regulation
Authors: Thit Amalie , Skjolding Lars M. , Hansen Steffen Foss
Published: February 2024

Sediments generally act as a sink of released manufactured nanomaterials (NMs).
Temperature dependent Raman and photoresponse studies of Bi2Te3 thin films annealed at different temperatures for improved optoelectronic performance
Authors: Das S. , Senapati S. , Alagarasan D. , Naik R.
Published: February 2024

The thermally evaporated Bi2Te3 films under annealing at different temperatures showed increased crystallinity, reduced bandgap and exhibit hydrophilic nature.
Dual-enzyme decorated semiconducting polymer nanoagents for second near-infrared photoactivatable ferroptosis-immunotherapy
Authors: Liu Yue , Lu Renjie , Li Meng , Cheng Danling , Wang Fengshuo , Ouyang Xumei , Zhang Yitian , Zhang Qin , Li Jingchao , Peng Shaojun
Published: February 2024

A dual-enzyme decorated semiconducting polymer nanoagent with second near-infrared photoactivatable therapeutic effects is reported for cancer therapy via enhanced ferroptosis and reversing of the immunosuppressive microenvironment.
Robust multiferroicity and magnetic modulation of the ferroelectric imprint field in heterostructures comprising epitaxial Hf0.5Zr0.5O2 and Co
Authors: Zakusylo Tetiana , Quintana Alberto , Lenzi Veniero , Silva José P. B. , Marques Luís , Yano José Luís Ortolá , Lyu Jike , Sort Jordi , Sánchez Florencio , Fina Ignasi
Published: February 2024

Magnetoelectric composite multiferroic comprising ferroelectric doped HfO2 and ferromagnetic cobalt coupled films is demonstrated to be a promising candidate for energy efficient memory computing.
An experimental and numerical study on adhesion force at the nanoscale
Authors: Kim Su-Hyun , Choi Pan-Kyu , Lee Yong-Bok , Kim Tae-Soo , Jo Min-Seung , Lee So-Young , Min Hyun-Woo , Yoon Jun-Bo
Published: February 2024

A practical prediction adhesion model utilizing iterative and realistic contact analysis with experimental verification.
Tensile benefits of nanofibers in commercial paint films
Authors: Turpin Geosmin , Nguyen Duc , Subramanian Priya , Davey Tim , Cheong Siew Fong , Warr Gregory G. , Neto Chiara , Hawkett Brian
Published: February 2024

Nanofibers synthesized by PISA-RAFT and added into pigmented commercial paint improve stain resistance, extensibility and toughness.
Improved photocatalytic carbon dioxide reduction over Bi-doped CeO2 by strain engineering
Authors: Tian Ang , Mei Ziyu , Wang Luyuan , Liu Guangliang , Liu Zhiguo , Kong Guangming , Tang Wenjun , Liu Chuangwei
Published: February 2024

By creating surface vacancy-dopant-mediated solid frustrated Lewis pairs, efficient photochemical conversion of CO2 to formic acid is achieved on Bi-doped CeO2 in the presence of strain, which is investigated by using density functional theory.
Highly stable all-solid-state batteries with Li–LTO composite anode
Authors: Panneerselvam Thamayanthi , Murugan R. , Sreejith O. V.
Published: February 2024

Schematic representation of lithium metal anode and composite anode.
The role of FAIR nanosafety data and nanoinformatics in achieving the UN sustainable development goals: the NanoCommons experience
Authors: Serrano Beatriz Alfaro , Gheorghe L. Cristiana , Exner Thomas E. , Resch Susanne , Wolf Clemens , Himly Martin , Falk Andreas , Bossa Nathan , Vazquez Socorro , Papadiamantis Anastasios G. , Afantitis Antreas , Melagraki Georgia , Maier Dieter , Saramveis Haralabos , Willighagen Egon , Lobaskin Vladimir , Oldfield Jonathan D. , Lynch Iseult
Published: February 2024

Increasingly Findable, Accessible, Reusable and Interoperable (FAIR) nanomaterials environmental health and safety (nanoEHS) data and demoncratised access to nanoinformatics models will directly support 12 SDGs and indireclty benefit the other 5 SDGs.
Pyridine-induced caused structural reconfiguration forming ultrathin 2D metal–organic frameworks for the oxygen evolution reaction
Authors: Liu Yang , Deng Shuwei , Fu Shihui , Wang Xiaoteng , Liu Gang , Yang Haidong
Published: February 2024

2D Co MOF-Py3 is synthesized by a bottom-up structural reconfiguration strategy by using pyridine for the oxygen evolution reaction.
Introducing phosphorus atoms into MoS2 nanosheets through a vapor-phase hydrothermal process for the hydrogen evolution reaction
Authors: Wu Tianxing , Meng Hanqi
Published: February 2024

Molybdenum disulfide (MoS2)-based electrocatalysts have been considered as promising alternatives to platinum for use in the hydrogen evolution reaction (HER).
PIDA/I2-mediated photo-induced aerobic N-acylation of sulfoximines with methylarenes
Authors: Chakraborty Nikita , Rajbongshi Kamal K. , Gondaliya Amisha , Patel Bhisma K.
Published: February 2024

A visible-light-induced oxidative cross-coupling between methylarenes and NH-sulfoximines leading to N-acyl sulfoximines is presented.
Recent advances of decatungstate photocatalyst in HAT process
Authors: Singh Praveen P. , Sinha Surabhi , Gahtori Prashant , Tivari Shraddha , Srivastava Vishal
Published: February 2024

The decatungstate anion (W10O324−) appears to exhibit especially interesting properties as a photocatalyst.
Highly stable chiral Cr(iii)-based metal–organic frameworks for enantioadsorption separation of aromatic alcohols
Authors: Li Mengna , Wu Benlai , Hong Maochun
Published: February 2024

Highly stable Cr-HMOFs Cr-HMOF-1 and Cr-HMOF-2 were synthesized for the first time directly using enantiomerically pure chiral ligands, showing excellent enantioselective separation performance for aromatic alcohol racemates.
Chemical kinetics and numerical simulation of NO emission characteristics in CH4/NH3/air flame
Authors: Zhang Yupeng , Cui Lixin , Feng Lei , Wang Tiantian , Bian Cuiping , Feng Yifei , Zhao Mengmeng , Han Fenglei
Published: February 2024

By combining chemical kinetics and CFD methods, the combustion characteristics of CH4/NH3/air flame were reported. Important reactions were identified and optimized, and an air-staging injection strategy was proposed to reduce NO emissions.
Shedding light on thermally-activated delayed fluorescence
Authors: Di Maiolo Francesco , Phan Huu D. K. Andrea , Giavazzi Davide , Landi Andrea , Racchi Ottavia , Painelli Anna
Published: February 2024

To exploit the applicative potential of TADF, several intertwined interactions must be understood, fully accounting for the local environment.
An efficient secure predictive demand forecasting system using Ethereum virtual machine
Authors: Saraswat Himani , Manchanda Mahesh , Jasola Sanjay
Published: February 2024

Predictive demand forecasting plays a pivotal role in optimizing supply chain management, enabling businesses to effectively allocate resources and minimize operational inefficiencies. This paper introduces a novel approach to enhancing demand forecasting processes by leveraging the Ethereum virtual machine within a blockchain framework. The proposed system capitalizes on the inherent security, transparency, and decentralized nature of blockchain technology to create a secure and efficient platform for predictive demand forecasting. The system leverages the Ethereum virtual machine to establish a secure, decentralized, and tamper‐resistant platform for demand prediction while ensuring data integrity and privacy. By utilizing the capabilities of smart contracts and decentralized applications within the Ethereum ecosystem, the proposed system offers an efficient and transparent solution for demand forecasting challenges. The current research focused on Ethereum virtual machine characteristics, features, components, and implementation details. A secured framework for the prediction of demand forecasting systems is proposed. Finally, the authors tried to validate and optimize the gas cost by using distinguished statistics and analysis.
A Petri net model for Time‐Delay Attack detection in Precision Time Protocol‐based networks
Authors: Moradi Mohsen , Jahangir Amir Hossein
Published: February 2024

Along with the development of industrial and distributed systems, security concerns have also emerged in industrial communication protocols. PTP, Precision Time Protocol, is one of the most precise time synchronisation protocols for industrial devices. It ensures real‐time activity of the industrial control systems with precision equal to microseconds. In order to address the actual or potential security issues of PTP, this article firstly describes attack models applicable to PTP and then focuses on applying Coloured Petri Net to formally analyse the attack detection methods and also model PTP. The alignment of simulation results with the model and the considered assumptions show the suitability and accuracy of the proposed model.
Improved nonlinear model‐free adaptive iterative learning control in DoS attack environment
Authors: Li Yanni , Li Xiuying
Published: February 2024

This paper investigates the design of a model‐free adaptive iterative learning controller(MFAILC) based on sampled‐data under the presence of denial‐of‐service(DoS) attacks in nonlinear networked control systems. First, the MFAILC is presented only using I/O data, where a compensation mechanism for DoS attacks is proposed. With dynamic linearization techniques, the nonlinear system is transformed into a linear system in the iteration domain. Then an improved MFAILC is designed to actively compensate the lost data caused by DoS attacks, where the estimation of pseudo‐partial derivative (PPD) is improved by establishing the AR model. The proposed algorithm can weaken the adverse effects of the DoS attacks and ensure the excellent tracking performance of the system. Finally, the stability of the method is proved, and the effectiveness of the proposed algorithm is demonstrated by a numerical example.
Robust stabilization for uncertain discrete–time singular Markovian jump systems with time–varying delays
Authors: Chen Wenbin , Gao Fang
Published: February 2024

The stabilization problem for uncertain discrete‐time singular Markovian jump systems (DSMJSs) with time‐varying delays is comprehensively covered in this paper. An updated Lyapunov–Krasovskii functional is presented via a discrete state decomposition method. With the help of this constructed Lyapunov–Krasovskii functional, some delay‐ and mode‐dependent sufficient conditions for the open‐loop DSMJSs are derived. Based on these circumstances, a memory mode‐dependent state feedback control is used to create a closed‐loop DSMJS with parameter uncertainties that is regular and causal. And then, the stochastically admissible conditions are attained. Through the exact calculation of each decomposition component for the designed memory state feedback controller, the intended memory state feedback controller settings are determined. It should be mentioned that the algorithm suggested in this article expands the controller design's feasibility and flexibility. The numerical results show how the approach is superior to previous ones, and the given results are less conservative.
A 0.9 V high‐speed dynamic bias latch‐type comparator employing a voltage‐controlled delay line
Authors: Tai Feng , Liu Yige , Bai Puyi , Li Qiang
Published: February 2024

This paper presents a novel dynamic bias latch‐type comparator combined with a voltage‐controlled delay line (VCDL), designed specifically for low‐power and low‐noise applications in high‐speed analog‐to‐digital converters (ADCs). The incorporation of the VCDL precedes the dynamic bias amplifier in the proposed comparator, thereby achieving a balance between energy efficiency and high‐speed operation. This innovative design enhances the input common voltage of the dynamic bias amplifier through the utilization of the VCDL, surpassing that of a conventional dynamic bias comparator. Furthermore, it demonstrates increased adaptability in technology scaling and efficient operation at lower supply voltages, leveraging inverters and other simple cells. The proposed comparator in 28 nm process technology achieves a 309.7 µV input‐referred noise while consuming approximately 145.8 fJ and completing comparisons in 125 ps with a 0.9 V supply and a 0.45 V input common‐mode voltage.
A digital prediction compensation for DR improvement in CT DSM with digital noise coupling
Authors: Pang Jiaxi , Ou Xilong , Li Qiang
Published: February 2024

This paper presents a prediction‐based dynamic range (DR) compensation technique in continuous‐time (CT) delta ‐sigma modulator (DSM) with digital‐domain noise coupling (DNC) structure. A digital prediction technique is proposed to address the issue of maximum stable amplitude (MSA) loss caused by DNC. The proposed prediction method has been shown to significantly extend the MSA of CT DSM with DNC. Moreover, through the extension of MSA, the DR and SNDR is significantly improved. A CTDSM with proposed compensation achieves a SNDR of 85.1dB at ‐1dBFS and a DR of 89dB.
Research of obstacle vehicles avoidance for automated heavy vehicle platoon by switching the formation
Authors: Kuang Jianjie , Tan Gangfeng , Guo Xuexun , Pei Xiaofei , Peng Dengzhi
Published: February 2024

With the development of automated vehicles, researches related to automated vehicle platoon (AVP) have received more and more attention. AVP is considered one of the effective means to alleviate traffic congestion and reduce vehicle energy consumption. This paper studies a three‐layer method of avoiding obstacle vehicles in traffic by switching the formation for the automated heavy vehicle platoon. In the decision‐making layer, a decision‐making system based on the finite‐state machine is established for formation switching. In the second layer, the lane‐changing trajectory is optimized based on the quantic polynomial curve fitting for vehicles that need to change lanes. In terms of vehicle control layer, each vehicle has a longitudinal controller based on sliding mode control and a lateral controller based on model predictive control to track the planned trajectory to complete the target formation. Finally, the proposed method is simulated in MATLAB/TruckSim. The simulation results show that the proposed method could effectively avoid the obstacle vehicles by switching the formation and has a small average value of errors in speed tracking and trajectory tracking.
Enhancing resilience of advanced power protection systems in smart grids against cyber–physical threats
Authors: Alasali Feras , Hayajneh Ali M. , Ghalyon Salah Abu , El‐Naily Naser , AlMajali Anas , Itradat Awni , Holderbaume William , Zaroure Eyad
Published: February 2024

Recently, smart grids introduce significant challenges to power system protection due to the high integration with distributed energy resources (DERs) and communication systems. To effectively manage the impact of DERs on power networks, researchers are actively formulating adaptive protection strategies, requiring robust communication schemes. However, concerns remain over the occurrence of communication connection failures and the potential risks presented by cyber‐attacks. This work addresses these challenges by investigating the impact of cyber‐attacks on different adaptive overcurrent relays (OCRs) approaches. Here, modern adaptive OCR coordination approaches using different group settings has integrated in evaluating high voltage/medium/low voltage (HV/MV/LV) network model with real network parameters at the MV/LV level. Additionally, a voltage‐based relay is developed and employed to enhance protection system performance under various cyber threats, aiming to reduce tripping time and to minimize energy that is not supplied. The results show that voltage‐based scheme outperform the traditional adaptive OCRs in terms of response time and mis coordination events under cyber‐attacks. In the proposed MV/LV real network scenario characterized by an 89% availability of a 4 MW photovoltaic system, even a brief interruption caused by cyber‐attacks can result in significant cost consequences.
L’optineurine et les dysfonctionnements mitochondriaux dans la neurodégénérescence
Authors: D’Urso Baptiste , Weil Robert , Génin Pierre
Published: February 2024

L’optineurine (OPTN) est une protéine multifonctionnelle jouant un rôle crucial en tant que récepteur dans l’autophagie sélective. Les mutations du gène OPTN sont liées à des maladies telles que le glaucome à tension normale et la sclérose latérale amyotrophique. L’OPTN exerce une fonction essentielle dans la dégradation sélective des mitochondries endommagées. Ce processus est requis pour empêcher leur accumulation, la production d’espèces réactives de l’oxygène et la libération de facteurs pro-apoptotiques. Le contrôle de la qualité de la mitophagie est orchestré par la kinase PINK1 et la ligase de l’ubiquitine cytosolique Parkin, dont les mutations sont associées à la maladie de Parkinson. Cette revue met en lumière des perspectives récentes soulignant le rôle de l’OPTN dans la mitophagie et son implication potentielle dans les maladies neurodégénératives.
Protéasomopathies neurodéveloppementales : une nouvelle classe de maladies du neurodéveloppement causées par une dysfonction du protéasome
Authors: Cuinat Silvestre , Bézieau Stéphane , Deb Wallid , Mercier Sandra , Vignard Virginie , Toutain Bérénice , Isidor Bertrand , Küry Sébastien , Ebstein Frédéric
Published: February 2024

Le système ubiquitine-protéasome (UPS) est une voie conservée chez les eucaryotes qui permet la dégradation, par les protéasomes, des protéines modifiées par l’ubiquitine. Récemment, une corrélation entre des variants pathogènes de gènes codant le protéasome et l’émergence de nouvelles maladies avec troubles neurodéveloppementaux, dénommés « protéasomopathies neurodéveloppementales », a été mise en évidence. Ces maladies rares se manifestent par des retards psychomoteurs, des troubles du comportement, des dysmorphies faciales et des anomalies multi-systémiques. Dans cette synthèse, nous répertorions les biomarqueurs spécifiques d’une dysfonction protéasomale et nous discutons de leur pertinence pour le diagnostic et les traitements de ces troubles neurodéveloppementaux.
VTE Risk Assessment and Prevention in Pregnancy
Authors: O'Rourke Ellen , Faryal Rehman , Blondon Marc , Middeldorp Saskia , Ní Áinle Fionnuala
Published: February 2024

Venous thromboembolism (VTE) remains the leading cause of maternal mortality in pregnancy and the postpartum period. In addition to the higher pregnancy-associated baseline VTE risk, there are several well-established risk factors that can further increase the risk of VTE. At present, a thorough interrogation of these risk factors remains our only tool for estimating which pregnant people may be at an increased risk of VTE, and thus potentially benefit from thromboprophylaxis. However, an important knowledge gap still exists surrounding the duration of increased risk and the interaction of risk factors with each other. Furthermore, up to now, once significant risk has been established, prevention strategies have been largely based on expert opinion rather than high-quality data. Recent trials have successfully bridged a proportion of this knowledge gap; however, the challenge of conducting high-quality clinical trials with pregnant people remains. In this article, we provide an update on the recent evidence surrounding VTE risk factors in pregnancy while concurrently outlining knowledge gaps and current approaches to VTE prevention.
Impact of temperature-controlled endobiliary radiofrequency ablation for inoperable hilar cholangiocarcinoma: A propensity score–matched analysis
Authors: Shin Il Sang , Moon Jong Ho , Lee Yun Nah , Myeong Jun Ho , Lee Tae Hoon , Yang Jae Kook , Cho Young Deok , Park Sang-Heum
Published: February 2024

Background and study aims Endobiliary radiofrequency ablation (RFA) can be an effective palliative treatment, but few studies have evaluated its outcomes for malignant obstruction in the hilar bile duct, which has a thin wall and complex duct–vascular contacts. We evaluated the efficacy and safety of temperature-controlled endobiliary RFA, which can reduce the risk of unintentional thermal injury by maintaining the temperature of the ablation segment, in the treatment of inoperable hilar cholangiocarcinoma (CCA).

Patients and methods After propensity score matching, 64 patients with inoperable hilar CCA were categorized to the RFA + stent group (endobiliary RFA with stenting; n=32) or stent-only group (stenting only; n=32). The evaluated outcomes were the median time to recurrent biliary obstruction (RBO), overall survival (OS), and adverse events (AEs).

Results Technical success was achieved in all patients. The clinical success rate was 93.8% in the RFA + stent group and 87.5% in the stent-only group (P=0.672). The median time to RBO was 242 days in the RFA + stent group and 168 days in the stent-only group (P=0.031). The median OS showed a non-significant tendency to be higher in the RFA + stent group (337 versus 296 days; P=0.260). Overall AE rates were comparable between the two groups (12.5% vs 9.4%, P=1.000).

Conclusions Temperature-controlled endobiliary RFA resulted in favorable stent patency without increasing the rate of AEs but it did not significantly increase OS in patients with inoperable hilar CCA (Clinical trial registration number: KCT0008576).
New Onset Encephalopathy with Toxic Triphasic Waves
Authors: PC Amrutha , Nambiar Poornima Narayanan , KM Navaf , Aslam Sarfaraz , NC Krishnadas , Pillai Deep P , Sureshbabu Sachin
Published: February 2024

New onset encephalopathy can have various causes like stroke, trauma, seizures, infections, demyelination, neoplasms, autoimmune, degenerative, and toxic and metabolic etiologies. Triphasic waves in electroencephalogram (EEG) is usually a clue to an ongoing metabolic process. We report a case of a 69-year-old female with bipolar disorder who presented with altered sensorium for the last 2 days. Her metabolic parameters, imaging, and cerebrospinal fluid findings were normal. Her EEG findings in the clinical setting provided a diagnostic clue to lithium toxicity, even though her serum lithium levels were normal. As her sensorium was progressively worsening, she was given a trial of hemodialysis with which she had significant improvement.
Aggregation-induced emission luminogens for super-resolution imaging
Authors: Zuo Yunfei , Kwok Ryan T. K. , Sun Jianwei , Lam Jacky W. Y. , Tang Ben Zhong
Published: February 2024

Over the past three decades, humanity has successfully surpassed Abbe's diffraction limit through the development of super-resolution microscopy (SRM), which leads to an increasing demand for specialized fluorescent molecules. The concept of aggregation-induced emission (AIE) has emerged as a powerful tool in fluorescence imaging since its inception in 2001. While thousands of distinctive AIE-based fluorescent molecules have been extensively utilized, their application in SRM was not explored until 2013. Although fewer than one hundred works on AIE and SRM have been published so far, this field is experiencing rapid growth. This review provides a comprehensive summary of advancements made by these intersecting domains over the last decade. The recent research is outlined, and four future directions are highlighted to guide the design of high-quality AIE-based probes for SRM applications that can further advance and promote this exciting area of research.
Vectorial phase retrieval in super-resolution polarization microscopy
Authors: Gutiérrez-Cuevas R. , Alemán-Castañeda L. A. , Herrera I. , Brasselet S. , Alonso M. A.
Published: February 2024

In single-molecule orientation localization microscopy, valuable information about the orientation and longitudinal position of each molecule is often encoded in the shape of the point spread function (PSF). Yet, this shape can be significantly affected by aberrations and other imperfections in the imaging system, leading to an erroneous estimation of the measured parameters. A basic solution is to model the aberrations as a scalar mask in the pupil plane that is characterized through phase retrieval algorithms. However, this approach is not suitable for cases involving polarization-dependent aberrations, introduced either through unintentional anisotropy in the elements or by using birefringent masks for PSF shaping. Here, this problem is addressed by introducing a fully vectorial model in which the polarization aberrations are represented via a spatially dependent Jones matrix, commonly used to describe polarization-dependent elements. It is then shown that these aberrations can be characterized by a set of PSF measurements at varying focal planes and for various polarization projections. This PZ-stack of PSFs, which contains diversity in both phase and polarization projection, is used in a phase retrieval algorithm based on nonlinear optimization to determine the aberrations. This methodology is demonstrated with numerical simulations and experimental measurements. The pyPSFstack software developed for modeling and characterization is made freely available.
Training self-learning circuits for power-efficient solutions
Authors: Stern Menachem , Dillavou Sam , Jayaraman Dinesh , Durian Douglas J. , Liu Andrea J.
Published: February 2024

As the size and ubiquity of artificial intelligence and computational machine learning models grow, the energy required to train and use them is rapidly becoming economically and environmentally unsustainable. Recent laboratory prototypes of self-learning electronic circuits, such as “physical learning machines,” open the door to analog hardware that directly employs physics to learn desired functions from examples at a low energy cost. In this work, we show that this hardware platform allows for an even further reduction in energy consumption by using good initial conditions and a new learning algorithm. Using analytical calculations, simulations, and experiments, we show that a trade-off emerges when learning dynamics attempt to minimize both the error and the power consumption of the solution—greater power reductions can be achieved at the cost of decreasing solution accuracy. Finally, we demonstrate a practical procedure to weigh the relative importance of error and power minimization, improving the power efficiency given a specific tolerance to error.
Cross-linking polymerization and carbonization of biomass chlorophyll for carbon dot-based electroluminescent devices with ultra-narrow-emission
Authors: Dang Qi , Zhao Biao , Zheng Mengyun , Zhang Chengyang , Yu Runnan , Qu Songnan , Jia Haoran , Tan Zhan'ao
Published: February 2024

Exploiting narrow-bandwidth-emission fluorescent materials is crucial for next-generation wide-color gamut displays. Inspired by the narrow-bandwidth-emission characteristic of chlorophyll derivates, the present work develops a facile strategy to synthesize a series of red-emitting chlorophyll-structured CDs (CHL-CDs) with ultra-high color purity and good carrier mobility from different traditional Chinese medicine leaves through a simple cross-linking polymerization and carbonization process. The obtained CHL-CDs exhibit bright photoluminescence centered at 671 nm, ultra-high color purity with an FWHM of 23 nm, and a high photoluminescence quantum yield of up to 62%. More importantly, based on in-depth experimental and theoretical studies on the macroscopic host–guest interactions and microscopic interfacial interactions between the CHL-CDs and charge transporting materials, high-performance red electroluminescent light-emitting diodes are successfully prepared, with FWHM of only 28 nm, turn-on voltage of 3.7 V, maximum luminance of 623 cd m−2, and maximum current efficiency of 0.26 cd A−1. This study provides a universal platform for fabricating narrow-bandwidth-emission CDs with significant applications in photoelectric devices.
Revolutionizing biomedical research: The imperative need for heart–kidney-connected organoids
Authors: Song Sun-Sook , Park Hun-Jun , Kim Yong Kyun , Kang Sun-Woong
Published: February 2024

Organoids significantly advanced our comprehension of organ development, function, and disease modeling. This Perspective underscores the potential of heart–kidney-connected organoids in understanding the intricate relationship between these vital organs, notably the cardiorenal syndrome, where dysfunction in one organ can negatively impact the other. Conventional models fall short in replicating this complexity, necessitating an integrated approach. By co-culturing heart and kidney organoids, combined with microfluidic and 3D bioprinting technologies, a more accurate representation of in vivo conditions can be achieved. Such interconnected systems could revolutionize our grasp of multi-organ diseases, drive drug discovery by evaluating therapeutic agents on both organs simultaneously, and reduce the need for animal models. In essence, heart–kidney-connected organoids present a promising avenue to delve deeper into the pathophysiology underlying cardiorenal disorders, bridging existing knowledge gaps, and advancing biomedical research.
Lead-free BaTiO3-based relaxor ferroelectric thin film rendering rapid discharge rate for pulsed power energy application
Authors: Karmegam Shanmuga Priya , Murugavel P.
Published: February 2024

Ferroelectric thin film capacitors have large application potential in pulsed-power electronic and electrical systems due to their high-power density and rapid discharge capabilities. Although lead-based dielectrics are promising, the pursuit of eco-friendly, lead-free alternatives is gaining research attention. Here, the Bi and Li co-doped BaTiO3 thin film exhibiting relaxor ferroelectric properties was investigated for its energy storage properties. The fabricated polycrystalline Ba0.85(Bi0.5Li0.5)0.15TiO3 thin film by pulsed laser deposition revealed good breakdown strength (∼4 MV cm−1), a slim ferroelectric loop, and low leakage characteristics suitable for energy storage applications. The film exhibits a significant value of recoverable energy density (∼70 J cm−3) with better frequency and thermal stability. Notably, the better overall performance parameters of the film, including a sizable power density (261 MW cm−3) and a fast discharge rate (150 ns), along with good energy density and breakdown strength, make the material suitable for pulsed-power energy applications.
The distorting effects of producer strategies: Why engagement does not reveal consumer preferences for misinformation
Authors: Stewart Alexander J. , Arechar Antonio A. , Rand David G. , Plotkin Joshua B.
Published: February 2024

A great deal of empirical research has examined who falls for misinformation and why. Here, we introduce a formal game-theoretic model of engagement with news stories that captures the strategic interplay between (mis)information consumers and producers. A key insight from the model is that observed patterns of engagement do not necessarily reflect the preferences of consumers. This is because producers seeking to promote misinformation can use strategies that lead moderately inattentive readers to engage more with false stories than true ones—even when readers prefer more accurate over less accurate information. We then empirically test people’s preferences for accuracy in the news. In three studies, we find that people strongly prefer to click and share news they perceive as more accurate—both in a general population sample, and in a sample of users recruited through Twitter who had actually shared links to misinformation sites online. Despite this preference for accurate news—and consistent with the predictions of our model—we find markedly different engagement patterns for articles from misinformation versus mainstream news sites. Using 1,000 headlines from 20 misinformation and 20 mainstream news sites, we compare Facebook engagement data with 20,000 accuracy ratings collected in a survey experiment. Engagement with a headline is negatively correlated with perceived accuracy for misinformation sites, but positively correlated with perceived accuracy for mainstream sites. Taken together, these theoretical and empirical results suggest that consumer preferences cannot be straightforwardly inferred from empirical patterns of engagement.
Does automaticity in lexical and grammatical processing predict utterance fluency development?
Authors: Hanzawa Keiko , Suzuki Yuichi
Published: February 2024

In order to understand the development of automatization in second language (L2) acquisition and its role in speaking fluency development, 39 English as foreign language (EFL) learners performed a speaking task (subsequently analyzed for utterance fluency) as well as semantic classification (lexical processing measure) and maze (grammar processing measure) tasks at two time points (Time 1 and Time 2) over six months. The findings indicate that learners significantly speeded up their lexical and grammar processing, as reflected in faster reaction time (RT). However, only lexical processing showed a propensity for more stable processing at Time 1, as indicated by coefficient of variance (CV). Furthermore, multiple regression analyses revealed that more automatized grammar processing (faster RT and smaller CV) at Time 1 significantly predicted a larger reduction in mid-clause pause duration and frequency, respectively. These findings underscore the importance of automatization in grammar processing for developing fluency in an EFL context.
Perception of Japanese accented English segments in words
Authors: Kondo Mariko , Pérez-Ramón Rubén
Published: February 2024

We studied the perception of segmental boundaries in native English and Japanese accents in terms of foreign
accentedness, intelligibility and discrimination accuracy. Five American English vowels /ɪ, æ, ɑ, ə, ɝ/ and seven consonants /r,
l, v, θ, f, t, k/ were extracted from English and Japanese words produced by an American English-Japanese bilingual speaker, and manipulated, with the acoustic properties shifting gradually from 100% Japanese to 100% American English using segmental foreign accent and
gradation techniques. Perception tests were conducted online with native American English speakers, and groups of Japanese
speakers with either low or high English proficiency. All three groups showed a negative correlation between the degree of foreign
accent and intelligibility. Also, there was a greater reduction in intelligibility due to acoustic deviation from the native norm
in consonants than in vowels. The results suggest that more standard-like accent does not necessarily improve intelligibility,
thus highlighting the importance of FA research in terms of segmental accuracy.
Measuring the significance of higher-order dependency in networks
Authors: Li Jiaxu , Lu Xin
Published: February 2024

Higher-order networks (HONs), which go beyond the limitations of pairwise relation modeling by graphs, capture higher-order dependencies involving three or more components for various systems. As the number of potential higher-order dependencies increases exponentially with both network size and the order of dependency, it is of particular importance for HON models to balance their representation power against model complexity. In this study, we propose a method, significant k-order dependencies mining (SkDM), based on hypothesis testing and the Markov chain Monte Carlo (MCMC), to identify significant higher-order dependencies in real systems. Through synthetic clickstreams with elaborately designed higher-order dependencies, SkDM shows a powerful ability to correctly identify all significant dependencies at preset significance levels of

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, performing as the only method, in comparison to the state of the arts, that can robustly maintain the Type I error rate, and without generating any Type II error across all the experimental settings. We further apply the SkDM method to various empirical networks, including journal citations, air traffic, and email communications. Empirical results show that among those tested networks, only 6.03%, 1.47%, and 1.28% of all potential dependencies are of statistical significance (

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). The proposed SkDM method, therefore, provides an efficient tool for higher-order network analysis tasks at reduced computational complexity.
Influence of exchange bias on spin torque ferromagnetic resonance for quantification of spin–orbit torque efficiency
Authors: Zhao 赵 Qian 乾 , Zhang 张 Tengfei 腾飞 , He 何 Bin 斌 , Li 李 Zimu 子木 , Zhang 张 Senfu 森富 , Yu 于 Guoqiang 国强 , Wang 王 Jianbo 建波 , Liu 刘 Qingfang 青芳 , Wei 魏 Jinwu 晋武
Published: February 2024

Antiferromagnet (AFM)/ferromagnet (FM) heterostructure is a popular system for studying the spin–orbit torque (SOT) of AFMs. However, the interfacial exchange bias field induces that the magnetization in FM layer is noncollinear to the external magnetic field, namely the magnetic moment drag effect, which further influences the characteristic of SOT efficiency. In this work, we study the SOT efficiencies of IrMn/NiFe bilayers with strong interfacial exchange bias by using spin-torque ferromagnetic resonance (ST-FMR) method. A full analysis on the AFM/FM systems with exchange bias is performed, and the angular dependence of magnetization on external magnetic field is determined through the minimum rule of free energy. The ST-FMR results can be well fitted by this model. We obtained the relative accurate SOT efficiency ξ
DL = 0.058 for the IrMn film. This work provides a useful method to analyze the angular dependence of ST-FMR results and facilitates the accurate measurement of SOT efficiency for the AFM/FM heterostructures with strong exchange bias.