bluuebunny/crossref_metadata_2025 huggingface dataset:
Contrasting Methane Seepage Dynamics in the Hola Trough Offshore Norway: Insights From Two Different Summers
Authors: Ferré Bénédicte , Barreyre Thibaut , Bünz Stefan , Argentino Claudio , Corrales‐Guerrero Jorge , Dølven Knut Ola , Stetzler Marie , Fallati Luca , Sert Muhammed Fatih , Panieri Giuliana , Rastrick Samuel , Kutti Tina , Moser Manuel
Published: June 2024

This study investigates the temporal variations in methane concentration and flare activity in the Hola trough (offshore Norway) during May 2018 and June 2022. Between these time periods, methane seep activity exhibits 3.5 times increase, as evidenced by hydroacoustic measurements. As the seep area in the Hola trough is constantly within the hydrate stability zone, the observed increase cannot be attributed to migration of its shallow boundary due to temperature increase. However, a combination of low tide conditions resulting in a lower sediment pore pressure and a bottom water temperature increase resulting in a lower methane solubility is likely to explain the increase in the number of seeps observed in June 2022. The hypothesis of tide influence is supported by data collected from a piezometer deployed and recovered during the cruise showing that the tidal effect was observed 3 m below the seafloor. Despite the numerous methane seeps detected, methane concentration and gas flow rates near the seafloor were low (<19 nM and <70 mL min−1, respectively) compared to other areas with methane seep activity. This is likely due to strong currents rapidly dispersing methane in the water column. Sub‐seafloor investigations identified pathways for gas migration in methane seep areas, influenced by topography. This study provides valuable insights into the temporal dynamics of methane concentrations, flare activity, and gas distribution in the Hola trough, contributing to our understanding of offshore methane dynamics in the region.
The Influence of Fresh Submarine Groundwater Discharge on Seawater Acidification Along the Northern Mediterranean Coast of Israel
Authors: Silverman J. , Strauch‐Gozali S. , Asfur M.
Published: June 2024

In the oligotrophic Southeastern Mediterranean Sea (SEMS), it has been shown that dissolved inorganic nutrient (DIN) from fresh submarine groundwater discharge (FSGD) enhance primary production in coastal waters. In this study pH, Total Alkalinity (TA) and DIN of seawater and fresh water in a sea‐cave in the northern part of the Israeli Mediterranean coast and a nearby contact spring, respectively, were measured during October 2018–March 2020. The results show gradients of measured salinity, TA, pH and DIN along the cave axis year‐round, suggesting that they are influenced by FSGD. The seawater near the back of the cave was supersaturated with respect to atmospheric CO2 nearly year‐round and there is a strong positive divergence from its regional open‐water thermal dependence, which suggests that FSGD is also a source of atmospheric CO2 in this region. Comparison of TA, salinity and pCO2 from the back of the sea cave to their corresponding values from an abrasion platform monitoring site, ca. 3 km south of the cave, suggests that FSGD is occurring along the entire shoreline in this region. Thus, despite the increased productivity due to FSGD mediated nutrient enrichment of adjacent coastal waters of the oligotrophic SEMS, they are still a source of atmospheric CO2 nearly year‐round. Finally, the apparent trends of seawater acidification (ΔpH/Δt = −0.006 yrs−1) and pCO2 increase (+8 ppmV yr−1) observed at the nearby monitoring site since 2013 are explained by increased groundwater recharge and resulting FSGD total alkalinity compared to dissolved inorganic carbon inputs (ΔTA/ΔDIC = 1:1.2).
Cold Diffusion Model for Seismic Denoising
Authors: Trappolini Daniele , Laurenti Laura , Poggiali Giulio , Tinti Elisa , Galasso Fabio , Michelini Alberto , Marone Chris
Published: June 2024

Seismic waves contain information about the earthquake source, the geologic structure they traverse, and many forms of noise. Separating the noise from the earthquake is a difficult task because optimal parameters for filtering noise typically vary with time and, if chosen inappropriately, may strongly alter the original seismic waveform. Diffusion models based on Deep Learning have demonstrated remarkable capabilities in restoring images and audio signals. However, those models assume a Gaussian distribution of noise, which is not the case for typical seismic noise. Motivated by the effectiveness of “cold” diffusion models in speech enhancement, medical anomaly detection, and image restoration, we present a cold variant for seismic data restoration. We describe the first Cold Diffusion Model for Seismic Denoising (CDiffSD), including key design aspects, model architecture, and noise handling. Using metrics to quantify the performance of CDiffSD models compared to previous works, we demonstrate that it provides a new standard in performance. CDiffSD significantly improved the Signal to Noise Ratio by about 18% compared to previous models. It also enhanced Cross‐correlation by 6%, showing a better match between denoised and original signals. Moreover, testing revealed a 50% increase in the recall of P‐wave picks for seismic picking. Our work show that CDiffSD outperforms existing benchmarks, further underscoring its effectiveness in seismic data denoising and analysis. Additionally, the versatility of this model suggests its potential applicability across a range of tasks and domains, such as GNSS, Lab Acoustic Emission, and Distributed Acoustic Sensing data, offering promising avenues for further utilization.
The identification of effective tumor-suppressing neoantigens using a tumor-reactive TIL TCR-pMHC ternary complex
Authors: Kim Sang Hoon , Lee Bo Ryeong , Kim Sung-Min , Kim Sungsik , Kim Min-seok , Kim Jaehyun , Lee Inkyu , Kim Hee-Soo , Nam Gi-Hoon , Kim In-San , Song Kyuyoung , Choi Yoonjoo , Lee Dong-Sup , Park Woong-Yang
Published: June 2024

Neoantigens are ideal targets for cancer immunotherapy because they are expressed de novo in tumor tissue but not in healthy tissue and are therefore recognized as foreign by the immune system. Advances in next-generation sequencing and bioinformatics technologies have enabled the quick identification and prediction of tumor-specific neoantigens; however, only a small fraction of predicted neoantigens are immunogenic. To improve the predictability of immunogenic neoantigens, we developed the in silico neoantigen prediction workflows VACINUSpMHC and VACINUSTCR: VACINUSpMHC incorporates physical binding between peptides and MHCs (pMHCs), and VACINUSTCR integrates T cell reactivity to the pMHC complex through deep learning-based pairing with T cell receptors (TCRs) of putative tumor-reactive CD8 tumor-infiltrating lymphocytes (TILs). We then validated our neoantigen prediction workflows both in vitro and in vivo in patients with hepatocellular carcinoma (HCC) and in a B16F10 mouse melanoma model. The predictive abilities of VACINUSpMHC and VACINUSTCR were confirmed in a validation cohort of 8 patients with HCC. Of a total of 118 neoantigen candidates predicted by VACINUSpMHC, 48 peptides were ultimately selected using VACINUSTCR. In vitro validation revealed that among the 48 predicted neoantigen candidates, 13 peptides were immunogenic. Assessment of the antitumor efficacy of the candidate neoepitopes using a VACINUSTCR in vivo mouse model suggested that vaccination with the predicted neoepitopes induced neoantigen-specific T cell responses and enabled the trafficking of neoantigen-specific CD8 + T cell clones into the tumor tissue, leading to tumor suppression. This study showed that the prediction of immunogenic neoantigens can be improved by integrating a tumor-reactive TIL TCR-pMHC ternary complex.
Conditional knockout of Shank3 in the ventral CA1 by quantitative in vivo genome-editing impairs social memory in mice
Authors: Chung Myung , Imanaka Katsutoshi , Huang Ziyan , Watarai Akiyuki , Wang Mu-Yun , Tao Kentaro , Ejima Hirotaka , Aida Tomomi , Feng Guoping , Okuyama Teruhiro
Published: June 2024

Individuals with autism spectrum disorder (ASD) have a higher prevalence of social memory impairment. A series of our previous studies revealed that hippocampal ventral CA1 (vCA1) neurons possess social memory engram and that the neurophysiological representation of social memory in the vCA1 neurons is disrupted in ASD-associated Shank3 knockout mice. However, whether the dysfunction of Shank3 in vCA1 causes the social memory impairment observed in ASD remains unclear. In this study, we found that vCA1-specific Shank3 conditional knockout (cKO) by the adeno-associated virus (AAV)- or specialized extracellular vesicle (EV)- mediated in vivo gene editing was sufficient to recapitulate the social memory impairment in male mice. Furthermore, the utilization of EV-mediated Shank3-cKO allowed us to quantitatively examine the role of Shank3 in social memory. Our results suggested that there is a certain threshold for the proportion of Shank3-cKO neurons required for social memory disruption. Thus, our study provides insight into the population coding of social memory in vCA1, as well as the pathological mechanisms underlying social memory impairment in ASD.
Low-energy electronic structure in the unconventional charge-ordered state of ScV6Sn6
Authors: Kundu Asish K. , Huang Xiong , Seewald Eric , Ritz Ethan , Pakhira Santanu , Zhang Shuai , Sun Dihao , Turkel Simon , Shabani Sara , Yilmaz Turgut , Vescovo Elio , Dean Cory R. , Johnston David C. , Valla Tonica , Birol Turan , Basov Dmitri N. , Fernandes Rafael M. , Pasupathy Abhay N.
Published: June 2024

Kagome vanadates AV3Sb5 display unusual low-temperature electronic properties including charge density waves (CDW), whose microscopic origin remains unsettled. Recently, CDW order has been discovered in a new material ScV6Sn6, providing an opportunity to explore whether the onset of CDW leads to unusual electronic properties. Here, we study this question using angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy (STM). The ARPES measurements show minimal changes to the electronic structure after the onset of CDW. However, STM quasiparticle interference (QPI) measurements show strong dispersing features related to the CDW ordering vectors. A plausible explanation is the presence of a strong momentum-dependent scattering potential peaked at the CDW wavevector, associated with the existence of competing CDW instabilities. Our STM results further indicate that the bands most affected by the CDW are near vHS, analogous to the case of AV3Sb5 despite very different CDW wavevectors.
Three-dimensional hidden phase probed by in-plane magnetotransport in kagome metal CsV3Sb5 thin flakes
Authors: Wei Xinjian , Tian Congkuan , Cui Hang , Zhai Yuxin , Li Yongkai , Liu Shaobo , Song Yuanjun , Feng Ya , Huang Miaoling , Wang Zhiwei , Liu Yi , Xiong Qihua , Yao Yugui , Xie X. C. , Chen Jian-Hao
Published: June 2024

Transition metal compounds with kagome structure have been found to exhibit a variety of exotic structural, electronic, and magnetic orders. These orders are competing with energies very close to each other, resulting in complex phase transitions. Some of the phases are easily observable, such as the charge density wave (CDW) and the superconducting phase, while others are more challenging to identify and characterize. Here we present magneto-transport evidence of a new phase below ~ 35 K in the kagome topological metal CsV3Sb5 (CVS) thin flakes between the CDW and the superconducting transition temperatures. This phase is characterized by six-fold rotational symmetry in the in-plane magnetoresistance (MR) and is connected to the orbital current order in CVS. Furthermore, the phase is characterized by a large in-plane negative magnetoresistance, which suggests the existence of a three-dimensional, magnetic field-tunable orbital current ordered phase. Our results highlight the potential of magneto-transport to reveal the interactions between exotic quantum states of matter and to uncover the symmetry of such hidden phases.
CoHIT: a one-pot ultrasensitive ERA-CRISPR system for detecting multiple same-site indels
Authors: Liu Yin , Liu Xinyi , Wei Dongyi , Dang Lu , Xu Xiaoran , Huang Shisheng , Li Liwen , Wu Sanyun , Wu Jinxian , Liu Xiaoyan , Sun Wenjun , Tao Wanyu , Wei Yongchang , Huang Xingxu , Li Kui , Wang Xinjie , Zhou Fuling
Published: June 2024

Genetic testing is crucial for precision cancer medicine. However, detecting multiple same-site insertions or deletions (indels) is challenging. Here, we introduce CoHIT (Cas12a-based One-for-all High-speed Isothermal Test), a one-pot CRISPR-based assay for indel detection. Leveraging an engineered AsCas12a protein variant with high mismatch tolerance and broad PAM scope, CoHIT can use a single crRNA to detect multiple NPM1 gene c.863_864 4-bp insertions in acute myeloid leukemia (AML). After optimizing multiple parameters, CoHIT achieves a detection limit of 0.01% and rapid results within 30 minutes, without wild-type cross-reactivity. It successfully identifies NPM1 mutations in 30 out of 108 AML patients and demonstrates potential in monitoring minimal residual disease (MRD) through continuous sample analysis from three patients. The CoHIT method is also competent for detecting indels of KIT, BRAF, and EGFR genes. Integration with lateral flow test strips and microfluidic chips highlights CoHIT’s adaptability and multiplexing capability, promising significant advancements in clinical cancer diagnostics.
M6A reduction relieves FUS-associated ALS granules
Authors: Di Timoteo Gaia , Giuliani Andrea , Setti Adriano , Biagi Martina C. , Lisi Michela , Santini Tiziana , Grandioso Alessia , Mariani Davide , Castagnetti Francesco , Perego Eleonora , Zappone Sabrina , Lattante Serena , Sabatelli Mario , Rotili Dante , Vicidomini Giuseppe , Bozzoni Irene
Published: June 2024

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease due to gradual motoneurons (MN) degeneration. Among the processes associated to ALS pathogenesis, there is the formation of cytoplasmic inclusions produced by aggregation of mutant proteins, among which the RNA binding protein FUS. Here we show that, in neuronal cells and in iPSC-derived MN expressing mutant FUS, such inclusions are significantly reduced in number and dissolve faster when the RNA m6A content is diminished. Interestingly, stress granules formed in ALS conditions showed a distinctive transcriptome with respect to control cells, which reverted to similar to control after m6A downregulation. Notably, cells expressing mutant FUS were characterized by higher m6A levels suggesting a possible link between m6A homeostasis and pathological aggregates. Finally, we show that FUS inclusions are reduced also in patient-derived fibroblasts treated with STM-2457, an inhibitor of METTL3 activity, paving the way for its possible use for counteracting aggregate formation in ALS.
UBE2D3 facilitates NHEJ by orchestrating ATM signalling through multi-level control of RNF168
Authors: Yalçin Zeliha , Lam Shiu Yeung , Peuscher Marieke H. , van der Torre Jaco , Zhu Sha , Iyengar Prasanna V. , Salas-Lloret Daniel , de Krijger Inge , Moatti Nathalie , van der Lugt Ruben , Falcone Mattia , Cerutti Aurora , Bleijerveld Onno B. , Hoekman Liesbeth , González-Prieto Román , Jacobs Jacqueline J. L.
Published: June 2024

Maintenance of genome integrity requires tight control of DNA damage response (DDR) signalling and repair, with phosphorylation and ubiquitination representing key elements. How these events are coordinated to achieve productive DNA repair remains elusive. Here we identify the ubiquitin-conjugating enzyme UBE2D3 as a regulator of ATM kinase-induced DDR that promotes non-homologous end-joining (NHEJ) at telomeres. UBE2D3 contributes to DDR-induced chromatin ubiquitination and recruitment of the NHEJ-promoting factor 53BP1, both mediated by RNF168 upon ATM activation. Additionally, UBE2D3 promotes NHEJ by limiting RNF168 accumulation and facilitating ATM-mediated phosphorylation of KAP1-S824. Mechanistically, defective KAP1-S824 phosphorylation and telomeric NHEJ upon UBE2D3-deficiency are linked to RNF168 hyperaccumulation and aberrant PP2A phosphatase activity. Together, our results identify UBE2D3 as a multi-level regulator of NHEJ that orchestrates ATM and RNF168 activities. Moreover, they reveal a negative regulatory circuit in the DDR that is constrained by UBE2D3 and consists of RNF168- and phosphatase-mediated restriction of KAP1 phosphorylation.
Simulating multiple variability in spatially resolved transcriptomics with scCube
Authors: Qian Jingyang , Bao Hudong , Shao Xin , Fang Yin , Liao Jie , Chen Zhuo , Li Chengyu , Guo Wenbo , Hu Yining , Li Anyao , Yao Yue , Fan Xiaohui , Cheng Yiyu
Published: June 2024

A pressing challenge in spatially resolved transcriptomics (SRT) is to benchmark the computational methods. A widely-used approach involves utilizing simulated data. However, biases exist in terms of the currently available simulated SRT data, which seriously affects the accuracy of method evaluation and validation. Herein, we present scCube (https://github.com/ZJUFanLab/scCube), a Python package for independent, reproducible, and technology-diverse simulation of SRT data. scCube not only enables the preservation of spatial expression patterns of genes in reference-based simulations, but also generates simulated data with different spatial variability (covering the spatial pattern type, the resolution, the spot arrangement, the targeted gene type, and the tissue slice dimension, etc.) in reference-free simulations. We comprehensively benchmark scCube with existing single-cell or SRT simulators, and demonstrate the utility of scCube in benchmarking spot deconvolution, gene imputation, and resolution enhancement methods in detail through three applications.
Electrical noise spectroscopy of magnons in a quantum Hall ferromagnet
Authors: Kumar Ravi , Srivastav Saurabh Kumar , Roy Ujjal , Park Jinhong , Spånslätt Christian , Watanabe K. , Taniguchi T. , Gefen Yuval , Mirlin Alexander D. , Das Anindya
Published: June 2024

Collective spin-wave excitations, magnons, are promising quasi-particles for next-generation spintronics devices, including platforms for information transfer. In a quantum Hall ferromagnets, detection of these charge-neutral excitations relies on the conversion of magnons into electrical signals in the form of excess electrons and holes, but if the excess electron and holes are equal, detecting an electrical signal is challenging. In this work, we overcome this shortcoming by measuring the electrical noise generated by magnons. We use the symmetry-broken quantum Hall ferromagnet of the zeroth Landau level in graphene to launch magnons. Absorption of these magnons creates excess noise above the Zeeman energy and remains finite even when the average electrical signal is zero. Moreover, we formulate a theoretical model in which the noise is produced by equilibration between edge channels and propagating magnons. Our model also allows us to pinpoint the regime of ballistic magnon transport in our device.
Programmable melanoma-targeted radio-immunotherapy via fusogenic liposomes functionalized with multivariate-gated aptamer assemblies
Authors: Ren Xijiao , Xue Rui , Luo Yan , Wang Shuang , Ge Xinyue , Yao Xuemei , Li Liqi , Min Junxia , Li Menghuan , Luo Zhong , Wang Fudi
Published: June 2024

Radio-immunotherapy exploits the immunostimulatory features of ionizing radiation (IR) to enhance antitumor effects and offers emerging opportunities for treating invasive tumor indications such as melanoma. However, insufficient dose deposition and immunosuppressive microenvironment (TME) of solid tumors limit its efficacy. Here we report a programmable sequential therapeutic strategy based on multifunctional fusogenic liposomes (Lip@AUR-ACP-aptPD-L1) to overcome the intrinsic radio-immunotherapeutic resistance of solid tumors. Specifically, fusogenic liposomes are loaded with gold-containing Auranofin (AUR) and inserted with multivariate-gated aptamer assemblies (ACP) and PD-L1 aptamers in the lipid membrane, potentiating melanoma-targeted AUR delivery while transferring ACP onto cell surface through selective membrane fusion. AUR amplifies IR-induced immunogenic death of melanoma cells to release antigens and damage-associated molecular patterns such as adenosine triphosphate (ATP) for triggering adaptive antitumor immunity. AUR-sensitized radiotherapy also upregulates matrix metalloproteinase-2 (MMP-2) expression that combined with released ATP to activate ACP through an “and” logic operation-like process (AND-gate), thus triggering the in-situ release of engineered cytosine-phosphate-guanine aptamer-based immunoadjuvants (eCpG) for stimulating dendritic cell-mediated T cell priming. Furthermore, AUR inhibits tumor-intrinsic vascular endothelial growth factor signaling to suppress infiltration of immunosuppressive cells for fostering an anti-tumorigenic TME. This study offers an approach for solid tumor treatment in the clinics.
PRDX6 augments selenium utilization to limit iron toxicity and ferroptosis
Authors: Fujita Hiroaki , Tanaka Yu-ki , Ogata Seiryo , Suzuki Noriyuki , Kuno Sota , Barayeu Uladzimir , Akaike Takaaki , Ogra Yasumitsu , Iwai Kazuhiro
Published: June 2024

Ferroptosis is a form of regulated cell death induced by iron-dependent accumulation of lipid hydroperoxides. Selenoprotein glutathione peroxidase 4 (GPX4) suppresses ferroptosis by detoxifying lipid hydroperoxides via a catalytic selenocysteine (Sec) residue. Sec, the genetically encoded 21st amino acid, is biosynthesized from a reactive selenium donor on its cognate tRNA[Ser]Sec. It is thought that intracellular selenium must be delivered ‘safely’ and ‘efficiently’ by a carrier protein owing to its high reactivity and very low concentrations. Here, we identified peroxiredoxin 6 (PRDX6) as a novel selenoprotein synthesis factor. Loss of PRDX6 decreases the expression of selenoproteins and induces ferroptosis via a reduction in GPX4. Mechanistically, PRDX6 increases the efficiency of intracellular selenium utilization by transferring selenium between proteins within the selenocysteyl-tRNA[Ser]Sec synthesis machinery, leading to efficient synthesis of selenocysteyl-tRNA[Ser]Sec. These findings highlight previously unidentified selenium metabolic systems and provide new insights into ferroptosis.
Alteration of circulating ACE2-network related microRNAs in patients with COVID-19
Authors: Wicik Zofia , Eyileten Ceren , Nowak Anna , Keshwani Disha , Simões Sérgio N. , Martins David C. , Klos Krzysztof , Wlodarczyk Wojciech , Assinger Alice , Soldacki Dariusz , Chcialowski Andrzej , Siller-Matula Jolanta M. , Postula Marek
Published: June 2024

Angiotensin converting enzyme 2 (ACE2) serves as the primary receptor for the SARS-CoV-2 virus and has implications for the functioning of the cardiovascular system. Based on our previously published bioinformatic analysis, in this study we aimed to analyze the diagnostic and predictive utility of miRNAs (miR-10b-5p, miR-124-3p, miR-200b-3p, miR-26b-5p, miR-302c-5p) identified as top regulators of ACE2 network with potential to affect cardiomyocytes and cardiovascular system in patients with COVID-19. The expression of miRNAs was determined through qRT-PCR in a cohort of 79 hospitalized COVID-19 patients as well as 32 healthy volunteers. Blood samples and clinical data of COVID-19 patients were collected at admission, 7-days and 21-days after admission. We also performed SHAP analysis of clinical data and miRNAs target predictions and advanced enrichment analyses. Low expression of miR-200b-3p at the seventh day of admission is indicative of predictive value in determining the length of hospital stay and/or the likelihood of mortality, as shown in ROC curve analysis with an AUC of 0.730 and a p-value of 0.002. MiR-26b-5p expression levels in COVID-19 patients were lower at the baseline, 7 and 21-days of admission compared to the healthy controls (P < 0.0001). Similarly, miR-10b-5p expression levels were lower at the baseline and 21-days post admission (P = 0.001). The opposite situation was observed in miR-124-3p and miR-302c-5p. Enrichment analysis showed influence of analyzed miRNAs on IL-2 signaling pathway and multiple cardiovascular diseases through COVID-19-related targets. Moreover, the COVID-19-related genes regulated by miR-200b-3p were linked to T cell protein tyrosine phosphatase and the HIF-1 transcriptional activity in hypoxia. Analysis focused on COVID-19 associated genes showed that all analyzed miRNAs are strongly affecting disease pathways related to CVDs which could be explained by their strong interaction with the ACE2 network.
Adaptive control for memristive system via compensatory controller and Chebyshev neural network
Authors: Wang Shaofu
Published: June 2024

In this paper, based on linear matrix inequality technique, a simple controller and a compensatory controller are designed. It can track arbitrary fixed points and any periodic orbits. In addition, a synchronization control method via Chebyshev neural network with external disturbances is proposed. An adaptive controller is given. The Chebyshev neural network is used to approximate the uncertain nonlinear function and the adaptive law is used to adjust the corresponding parameters in the system. Taking a 4D memristive chaotic system as examples, the results are in consistent with the simulations. From a framework and control theoretical point of view, the proposed synchronization approach via compensation controller and Chebyshev neural network is firstly presented. From an application point of view, the proposed scheme can simplify the complexity of controller design. It is promising in many applications for mem-systems as secure communications and neural networks.
HCSRL: hyperledger composer system for reducing logistics losses in the pharmaceutical product supply chain using a blockchain-based approach
Authors: Dash Satyabrata , Ghugar Umashankar , Godavarthi Deepthi , Mohanty Sachi Nandan
Published: June 2024

Blockchain technology uses a secure and decentralised framework for transaction management and data sharing within supply chains. This is particularly crucial in the pharmaceutical industry, where product authenticity and traceability are paramount. Blockchain plays a pivotal role in preventing product loss and counterfeiting, while simultaneously enhancing transparency and efficiency throughout the supply chain. The research introduces a step-by-step approach to implementing a proof-of-concept (PoC) for Supply Chain Risk Management (SCRM) through blockchain technology. This PoC involves simulating a supply chain process to assess feasibility and measure key performance indicators. Engaging stakeholders and gathering feedback is integral to refining the blockchain-based SCRM system. The study rigorously evaluates the performance of the SCRM blockchain across various test scenarios, featuring differing numbers of organizations and clients. Multiple fabric networks are employed to assess the system’s scalability and performance under diverse conditions. The results of these comprehensive tests inform practical deployment decisions and highlight areas for potential optimization and further development. So this research provides valuable insights into the application of blockchain in pharmaceutical supply chains, offering a roadmap for implementation and improving supply chain security, efficiency, and transparency.
Endothelial calcium dynamics elicited by ATP release from red blood cells
Authors: Nayak Ananta Kumar , Das Sovan Lal , Misbah Chaouqi
Published: June 2024

Red blood cells (RBCs) exhibit an interesting response to hydrodynamic flow, releasing adenosine triphosphate (ATP). Subsequently, these liberated ATP molecules initiate a crucial interaction with endothelial cells (ECs), thereby setting off a cascade involving the release of calcium ions (Ca$$^{2+}$$

2
+

). Ca$$^{2+}$$

2
+

exerts control over a plethora of cellular functions, and acts as a mediator for dilation and contraction of blood vessel walls. This study focuses on the relationship between RBC dynamics and Ca$$^{2+}$$

2
+

dynamics, based on numerical simulations under Poiseuille flow within a linear two-dimensional channel. It is found that the concentration of ATP depends upon a variety of factors, including RBC density, channel width, and the vigor of the flow. The results of our investigation reveals several features. Firstly, the peak amplitude of Ca$$^{2+}$$

2
+

per EC escalates in direct proportion to the augmentation of RBC concentration. Secondly, increasing the flow strength induces a reduction in the time taken to reach the peak of Ca$$^{2+}$$

2
+

concentration, under the condition of a constant channel width. Additionally, when flow strength remains constant, an increase in channel width corresponds to an elevation in calcium peak amplitude, coupled with a decrease in peak time. This implies that Ca$$^{2+}$$

2
+

signals should transition from relatively unconstrained channels to more confined pathways within real vascular networks. This notion gains support from our examination of calcium propagation in a linear channel. In this scenario, the localized Ca$$^{2+}$$

2
+

release initiates a propagating wave that gradually encompasses the entire channel. Notably, our computed propagation speed agrees with observations.
REST-dependent downregulation of von Hippel-Lindau tumor suppressor promotes autophagy in SHH-medulloblastoma
Authors: Singh Ashutosh , Cheng Donghang , Swaminathan Jyothishmathi , Yang Yanwen , Zheng Yan , Gordon Nancy , Gopalakrishnan Vidya
Published: June 2024

The RE1 silencing transcription factor (REST) is a driver of sonic hedgehog (SHH) medulloblastoma genesis. Our previous studies showed that REST enhances cell proliferation, metastasis and vascular growth and blocks neuronal differentiation to drive progression of SHH medulloblastoma tumors. Here, we demonstrate that REST promotes autophagy, a pathway that is found to be significantly enriched in human medulloblastoma tumors relative to normal cerebella. In SHH medulloblastoma tumor xenografts, REST elevation is strongly correlated with increased expression of the hypoxia-inducible factor 1-alpha (HIF1α)—a positive regulator of autophagy, and with reduced expression of the von Hippel-Lindau (VHL) tumor suppressor protein – a component of an E3 ligase complex that ubiquitinates HIF1α. Human SHH-medulloblastoma tumors with higher REST expression exhibit nuclear localization of HIF1α, in contrast to its cytoplasmic localization in low-REST tumors. In vitro, REST knockdown promotes an increase in VHL levels and a decrease in cytoplasmic HIF1α protein levels, and autophagy flux. In contrast, REST elevation causes a decline in VHL levels, as well as its interaction with HIF1α, resulting in a reduction in HIF1α ubiquitination and an increase in autophagy flux. These data suggest that REST elevation promotes autophagy in SHH medulloblastoma cells by modulating HIF1α ubiquitination and stability in a VHL-dependent manner. Thus, our study is one of the first to connect VHL to REST-dependent control of autophagy in a subset of medulloblastomas.
Visualization of incrementally learned projection trajectories for longitudinal data
Authors: Malepathirana Tamasha , Senanayake Damith , Gautam Vini , Engel Martin , Balez Rachelle , Lovelace Michael D. , Sundaram Gayathri , Heng Benjamin , Chow Sharron , Marquis Christopher , Guillemin Gilles J. , Brew Bruce , Jagadish Chennupati , Ooi Lezanne , Halgamuge Saman
Published: June 2024

Longitudinal studies that continuously generate data enable the capture of temporal variations in experimentally observed parameters, facilitating the interpretation of results in a time-aware manner. We propose IL-VIS (incrementally learned visualizer), a new machine learning pipeline that incrementally learns and visualizes a progression trajectory representing the longitudinal changes in longitudinal studies. At each sampling time point in an experiment, IL-VIS generates a snapshot of the longitudinal process on the data observed thus far, a new feature that is beyond the reach of classical static models. We first verify the utility and correctness of IL-VIS using simulated data, for which the true progression trajectories are known. We find that it accurately captures and visualizes the trends and (dis)similarities between high-dimensional progression trajectories. We then apply IL-VIS to longitudinal multi-electrode array data from brain cortical organoids when exposed to different levels of quinolinic acid, a metabolite contributing to many neuroinflammatory diseases including Alzheimer’s disease, and its blocking antibody. We uncover valuable insights into the organoids’ electrophysiological maturation and response patterns over time under these conditions.
A deep image classification model based on prior feature knowledge embedding and application in medical diagnosis
Authors: Xu Chen , Wu Jiangxing , Zhang Fan , Freer Jonathan , Zhang Zhongqun , Cheng Yihua
Published: June 2024

Aiming at the problem of image classification with insignificant morphological structural features, strong target correlation, and low signal-to-noise ratio, combined with prior feature knowledge embedding, a deep learning method based on ResNet and Radial Basis Probabilistic Neural Network (RBPNN) is proposed model. Taking ResNet50 as a visual modeling network, it uses feature pyramid and self-attention mechanism to extract appearance and semantic features of images at multiple scales, and associate and enhance local and global features. Taking into account the diversity of category features, channel cosine similarity attention and dynamic C-means clustering algorithms are used to select representative sample features in different category of sample subsets to implicitly express prior category feature knowledge, and use them as the kernel centers of radial basis probability neurons (RBPN) to realize the embedding of diverse prior feature knowledge. In the RBPNN pattern aggregation layer, the outputs of RBPN are selectively summed according to the category of the kernel center, that is, the subcategory features are combined into category features, and finally the image classification is implemented based on Softmax. The functional module of the proposed method is designed specifically for image characteristics, which can highlight the significance of local and structural features of the image, form a non-convex decision-making area, and reduce the requirements for the completeness of the sample set. Applying the proposed method to medical image classification, experiments were conducted based on the brain tumor MRI image classification public dataset and the actual cardiac ultrasound image dataset, and the accuracy rate reached 85.82% and 83.92% respectively. Compared with the three mainstream image classification models, the performance indicators of this method have been significantly improved.
Investigating the impact of alumina nanoparticles in coconut oil distillate biodiesel to lessen emissions in direct injection diesel engine
Authors: Rajesh K. , Bibin Chidambaranathan , Soundararajan Gopinath , Ashok Kumar R. , Arunkumar S. , Devarajan Yuvarajan , Kaliappan Nandagopal
Published: June 2024

Petroleum fuels are commonly used for automobiles. However, the continuous depletion and exhaust gas emission causes serious problems. So, there is a need for an alternative eco-friendly fuel. Biodiesel is a type of fuel manufactured through a process called transesterification, which involves converting vegetable oils into a usable form. The process parameters of the transesterification process were optimized using the Taguchi method to achieve maximum biodiesel yield. However, the main problem of biodiesel is its high cost which could be reduced by using low-cost feedstock. To address this challenge, biodiesel (BCFAD) is derived from coconut fatty acid distillate (CFAD), a by-product obtained from refining coconut oil. This work uses BCFAD and BCFAD with Alumina nanoparticles as fuels. Alumina nanoparticles in the mass fraction of 25 ppm, 50 ppm, and 100 ppm are dispersed in BCFAD. The investigation results reveal an increase of 6.5% in brake thermal efficiency for BCFAD with 100 ppm nanoparticles when compared to BCFAD. There is a reduction of 29.29% of hydrocarbon and 34% of Carbon monoxide emissions with BCFAD100 in comparison with diesel. However, there is a marginal increase in NOx emission with the increase in nanoparticles. The heat release rate and cylinder pressure of BCFAD100 are comparable to diesel fuel. It was concluded that the utilization of BCFAD with a nanoparticle dispersion of 100 ppm is suitable for direct use as fuel in diesel engines.
Motor assessment of X-linked dystonia parkinsonism via machine-learning-based analysis of wearable sensor data
Authors: Parisi Federico , Corniani Giulia , Bonato Paolo , Balkwill David , Acuna Patrick , Go Criscely , Sharma Nutan , Stephen Christopher D.
Published: June 2024

X-linked dystonia parkinsonism (XDP) is a neurogenetic combined movement disorder involving both parkinsonism and dystonia. Complex, overlapping phenotypes result in difficulties in clinical rating scale assessment. We performed wearable sensor-based analyses in XDP participants to quantitatively characterize disease phenomenology as a potential clinical trial endpoint. Wearable sensor data was collected from 10 symptomatic XDP patients and 3 healthy controls during a standardized examination. Disease severity was assessed with the Unified Parkinson’s Disease Rating Scale Part 3 (MDS-UPDRS) and Burke-Fahn-Marsden dystonia scale (BFM). We collected sensor data during the performance of specific MDS-UPDRS/BFM upper- and lower-limb motor tasks, and derived data features suitable to estimate clinical scores using machine learning (ML). XDP patients were at varying stages of disease and clinical severity. ML-based algorithms estimated MDS-UPDRS scores (parkinsonism) and dystonia-specific data features with a high degree of accuracy. Gait spatio-temporal parameters had high discriminatory power in differentiating XDP patients with different MDS-UPDRS scores from controls, XDP freezing of gait, and dystonic/non-dystonic gait. These analyses suggest the feasibility of using wearable sensor data for deriving reliable clinical score estimates associated with both parkinsonian and dystonic features in a complex, combined movement disorder and the utility of motion sensors in quantifying clinical examination.
Characterization of resistance and virulence factors in livestock-associated methicillin-resistant Staphylococcus aureus
Authors: Beshiru Abeni , Igbinosa Isoken H. , Akinnibosun Olajide , Ogofure Abraham G. , Dunkwu-Okafor Afamefuna , Uwhuba Kate E. , Igbinosa Etinosa O.
Published: June 2024

The study investigated the economic concerns associated with livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) in livestock (cow), examining its connection to severe infections, antimicrobial resistance (AMR), and virulence factors. The research, conducted in Edo State, Nigeria, analyzed 400 samples (200 rectal and 200 nasal swabs) collected between March 2018 and February 2019. MRSA prevalence was identified using conventional culture-based methods and polymerase chain reaction (PCR) techniques, revealing 63.5% (n = 254) for Staphylococcus aureus and 55% (n = 220) for MRSA. Of the 76 mecA-positive MRSA isolates, 64.5% (n = 49) exhibited multidrug resistance (MDR) while the remaining were sensitive to specific antimicrobials. Key virulence genes, such as PVL (81.6%; n = 62) and tsst-1 (44.7%; n = 34), were prevalent, along with AMR genes like mecC, tetM, ermA, ermC, vanA, and vanC. Staphylococcal chromosomal cassette mec (SCCmec) typing identified different types, notably II, IVa, and IVb. Biofilm formation, a crucial virulence factor varied in strength, is associated with icaA and icaB genes (p < 0.01). The findings highlighted substantial AMR and biofilm-forming capacity within LA-MRSA isolates, emphasizing the importance of ongoing surveillance for informed treatment strategies, AMR policies, and control measures against MDR staphylococcal infections.
Enhancement of ionospheric heating effect by chemical release
Authors: Zhao Hai-Sheng , Feng Jie , Xu Zheng-Wen , Liu Ya-Xin , Xue Kun , Wu Jian , Wang Cheng , Xie Shou-Zhi , Peng Huai-Yun
Published: June 2024

The ionosphere can be artificially modified by employing ground-based high-power high-frequency electromagnetic waves to irradiate the ionosphere. This modification is achieved through the nonlinear interaction between the electromagnetic waves and the ionospheric plasma, leading to changes in the physical properties and structure of the ionosphere. The degree of artificial modification of the ionosphere is closely related to the heating energy density of high-frequency pump waves. Due to the high density of neutral constituents in the lower ionosphere and the high frequency of electron-neutral collisions, the energy of heating pump waves will be absorbed and attenuated during the penetration of the low ionosphere, seriously affecting the heating effect. This paper proposes a method to reduce the absorption of ionospheric heating pump waves by releasing electron attachment chemicals into low ionosphere to form a large-scale electron density hole. A model for mitigating pump waves absorption based on SF6 release is established, and the absorption at different frequencies is quantitatively calculated. The propagation characteristics of high-frequency signals in ionospheric holes are studied using a three-dimensional ray tracing method, and the results demonstrate that the chemical release method not only reduces the absorption attenuation of heating pump waves but also forms spherical electron density holes, which exhibit a focusing effect on the heating beam and enhance the heating effect. The results are of great significance for understanding the nonlinear interaction between electromagnetic wave and ionospheric plasma and improving the ionospheric heating efficiency.
Associations between pain intensity, psychosocial factors, and pain-related disability in 4285 patients with chronic pain
Authors: Landmark Live , Sunde Hans Fredrik , Fors Egil A. , Kennair Leif Edward Ottesen , Sayadian Annahita , Backelin Caroline , Reme Silje Endresen
Published: June 2024

Pain, a widespread challenge affecting daily life, is closely linked with psychological and social factors. While pain clearly influences daily function in those affected, the complete extent of its impact is not fully understood. Given the close connection between pain and psychosocial factors, a deeper exploration of these aspects is needed. In this study, we aim to examine the associations between psychosocial factors, pain intensity, and pain-related disability among patients with chronic pain. We used data on 4285 patients from the Oslo University Hospital Pain Registry, and investigated pain-related disability, pain intensity, pain catastrophizing, psychological distress, perceived injustice, insomnia, fatigue, and self-efficacy. We found significant associations between all psychosocial variables and pain-related disability, even after adjusting for demographic factors. In the multiple regression model, sleep problems and pain intensity were identified as primary contributors, alongside psychological distress, and fatigue. Combined, these factors accounted for 26.5% of the variability in pain-related disability, with insomnia and pain intensity exhibiting the strongest associations. While the direction of causation remains unclear, our findings emphasize the potential of interventions aimed at targeting psychosocial factors. Considering the strong link between psychosocial factors and pain-related disability, interventions targeting these factors—particularly insomnia—could reduce disability and enhance quality of life in those who suffer.
Global soil respiration estimation based on ecological big data and machine learning model
Authors: Liu Jiangnan , Hu Junguo , Liu Haoqi , Han Kanglai
Published: June 2024

Soil respiration (Rs) represents the greatest carbon dioxide flux from terrestrial ecosystems to the atmosphere. However, its environmental drivers are not fully understood, and there are still significant uncertainties in soil respiration model estimates. This study aimed to estimate the spatial distribution pattern and driving mechanism of global soil respiration by constructing a machine learning model method based on ecological big data. First, we constructed ecological big data containing five categories of 27-dimensional environmental factors. We then used four typical machine learning methods to develop the performance of machine learning models under four training strategies and explored the relationship between soil respiration and environmental factors. Finally, we used the RF machine learning algorithm to estimate the global Rs spatial distribution pattern in 2021, driven by multiple dimensions of environmental factors, and derived the annual soil respiration values. The results showed that RF performed better under the four training strategies, with a coefficient of determination R2 = 0.78216, root mean squared error (RMSE) = 285.8964 gCm−2y−1, and mean absolute error (MAE) = 180.4186 gCm−2y−1, which was more suitable for the estimation of large-scale soil respiration. In terms of the importance of environmental factors, unlike previous studies, we found that the influence of geographical location was greater than that of MAP. Another new finding was that enhanced vegetation index 2 (EVI2) had a higher contribution to soil respiration estimates than the enhanced vegetation index (EVI) and normalized vegetation index (NDVI). Our results confirm the potential of utilizing ecological big data for spatially large-scale Rs estimations. Ecological big data and machine learning algorithms can be considered to improve the spatial distribution patterns and driver analysis of Rs.
Real-life effectiveness of sacubitril/valsartan in older Belgians with heart failure, reduced ejection fraction and most severe symptoms
Authors: Maury Eléonore , Belmans Ann , Bogaerts Kris , Vancayzeele Stefaan , Jansen Mieke
Published: June 2024

We assessed the real-world effectiveness of sacubitril/valsartan in patients with chronic heart failure (HF) and reduced ejection fraction (HFrEF) with an emphasis on those with older age (≥ 75 years) or with New York Heart Association (NYHA) class IV, for whom greater uncertainty existed regarding clinical outcomes. We conducted a retrospective cohort study based on patient-level linkage of electronic healthcare datasets. Data from all adults with HFrEF in Belgium receiving a prescription for sacubitril/valsartan between 01-November-2016 and 31-December-2018 were collected, with a follow-up of > 6 years. The total study population comprised 5446 patients, older than the PARADIGM-HF trial participants, and with higher NYHA class (all P < 0.0001). NYHA class improved following sacubitril/valsartan initiation (P < 0.0001 baseline vs. reassessment). Most concomitant medications were reduced. Remarkably, the risk of hospitalization for a cardiovascular reason and for HF was reduced by > 26% in the overall cohort, and in subgroups of patients ≥ 75 years, with NYHA class III/IV (all P < 0.0001) or with NYHA class IV (P < 0.05), vs. baseline. All-cause mortality did not increase in real-world patients with NYHA class III/IV. The results support the long-term beneficial effects of sacubitril/valsartan in older patients and in those experiencing the most severe symptoms.