bluuebunny/crossref_metadata_2025 huggingface dataset:
The anti-tumor effect of trifluridine via induction of aberrant mitosis is unaffected by mutations modulating p53 activity
Authors: Wakasa Takeshi , Nonaka Kentaro , Harada Akihito , Ohkawa Yasuyuki , Kikutake Chie , Suyama Mikita , Kobunai Takashi , Tsunekuni Kenta , Matsuoka Kazuaki , Kataoka Yuki , Ochiiwa Hiroaki , Miyadera Kazutaka , Sagara Takeshi , Oki Eiji , Ohdo Shigehiro , Maehara Yoshihiko , Iimori Makoto , Kitao Hiroyuki
Published: July 2024

The fluorinated thymidine analog trifluridine (FTD) is a chemotherapeutic drug commonly used to treat cancer; however, the mechanism by which FTD induces cytotoxicity is not fully understood. In addition, the effect of gain-of-function (GOF) missense mutations of the TP53 gene (encoding p53), which promote cancer progression and chemotherapeutic drug resistance, on the chemotherapeutic efficacy of FTD is unclear. Here, we revealed the mechanisms by which FTD-induced aberrant mitosis and contributed to cytotoxicity in both p53-null and p53-GOF missense mutant cells. In p53-null mutant cells, FTD-induced DNA double-stranded breaks, single-stranded DNA accumulation, and the associated DNA damage responses during the G2 phase. Nevertheless, FTD-induced DNA damage and the related responses were not sufficient to trigger strict G2/M checkpoint arrest. Thus, these features were carried over into mitosis, resulting in chromosome breaks and bridges, and subsequent cytokinesis failure. Improper mitotic exit eventually led to cell apoptosis, caused by the accumulation of extensive DNA damage and the presence of micronuclei encapsulated in the disrupted nuclear envelope. Upon FTD treatment, the behavior of the p53-GOF-missense mutant, isogenic cell lines, generated by CRISPR/Cas9 genome editing, was similar to that of p53-null mutant cells. Thus, our data suggest that FTD treatment overrode the effect on gene expression induced by p53-GOF mutants and exerted its anti-tumor activity in a manner that was independent of the p53 function.
Perirhinal cortex learns a predictive map of the task environment
Authors: Lee David G. , McLachlan Caroline A. , Nogueira Ramon , Kwon Osung , Carey Alanna E. , House Garrett , Lagani Gavin D. , LaMay Danielle , Fusi Stefano , Chen Jerry L.
Published: July 2024

Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that can progressively be decoded earlier in the trial as training advances and that generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and systemic pharmacological perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.
Accelerating glacier volume loss on Juneau Icefield driven by hypsometry and melt-accelerating feedbacks
Authors: Davies Bethan , McNabb Robert , Bendle Jacob , Carrivick Jonathan , Ely Jeremy , Holt Tom , Markle Bradley , McNeil Christopher , Nicholson Lindsey , Pelto Mauri
Published: July 2024

Globally, glaciers and icefields contribute significantly to sea level rise. Here we show that ice loss from Juneau Icefield, a plateau icefield in Alaska, accelerated after 2005 AD. Rates of area shrinkage were 5 times faster from 2015–2019 than from 1979–1990. Glacier volume loss remained fairly consistent (0.65–1.01 km3 a−1) from 1770–1979 AD, rising to 3.08–3.72 km3 a−1 from 1979–2010, and then doubling after 2010 AD, reaching 5.91 ± 0.80 km3 a−1 (2010–2020). Thinning has become pervasive across the icefield plateau since 2005, accompanied by glacier recession and fragmentation. Rising equilibrium line altitudes and increasing ablation across the plateau has driven a series of hypsometrically controlled melt-accelerating feedbacks and resulted in the observed acceleration in mass loss. As glacier thinning on the plateau continues, a mass balance-elevation feedback is likely to inhibit future glacier regrowth, potentially pushing glaciers beyond a dynamic tipping point.
A unified model-based framework for doublet or multiplet detection in single-cell multiomics data
Authors: Hu Haoran , Wang Xinjun , Feng Site , Xu Zhongli , Liu Jing , Heidrich-O’Hare Elisa , Chen Yanshuo , Yue Molin , Zeng Lang , Rong Ziqi , Chen Tianmeng , Billiar Timothy , Ding Ying , Huang Heng , Duerr Richard H. , Chen Wei
Published: July 2024

Droplet-based single-cell sequencing techniques rely on the fundamental assumption that each droplet encapsulates a single cell, enabling individual cell omics profiling. However, the inevitable issue of multiplets, where two or more cells are encapsulated within a single droplet, can lead to spurious cell type annotations and obscure true biological findings. The issue of multiplets is exacerbated in single-cell multiomics settings, where integrating cross-modality information for clustering can inadvertently promote the aggregation of multiplet clusters and increase the risk of erroneous cell type annotations. Here, we propose a compound Poisson model-based framework for multiplet detection in single-cell multiomics data. Leveraging experimental cell hashing results as the ground truth for multiplet status, we conducted trimodal DOGMA-seq experiments and generated 17 benchmarking datasets from two tissues, involving a total of 280,123 droplets. We demonstrated that the proposed method is an essential tool for integrating cross-modality multiplet signals, effectively eliminating multiplet clusters in single-cell multiomics data—a task at which the benchmarked single-omics methods proved inadequate.
Intrinsic signaling pathways modulate targeted protein degradation
Authors: Mori Yuki , Akizuki Yoshino , Honda Rikuto , Takao Miyu , Tsuchimoto Ayaka , Hashimoto Sota , Iio Hiroaki , Kato Masakazu , Kaiho-Soma Ai , Saeki Yasushi , Hamazaki Jun , Murata Shigeo , Ushijima Toshikazu , Hattori Naoko , Ohtake Fumiaki
Published: July 2024

Targeted protein degradation is a groundbreaking modality in drug discovery; however, the regulatory mechanisms are still not fully understood. Here, we identify cellular signaling pathways that modulate the targeted degradation of the anticancer target BRD4 and related neosubstrates BRD2/3 and CDK9 induced by CRL2VHL- or CRL4CRBN -based PROTACs. The chemicals identified as degradation enhancers include inhibitors of cellular signaling pathways such as poly-ADP ribosylation (PARG inhibitor PDD00017273), unfolded protein response (PERK inhibitor GSK2606414), and protein stabilization (HSP90 inhibitor luminespib). Mechanistically, PARG inhibition promotes TRIP12-mediated K29/K48-linked branched ubiquitylation of BRD4 by facilitating chromatin dissociation of BRD4 and formation of the BRD4–PROTAC–CRL2VHL ternary complex; by contrast, HSP90 inhibition promotes BRD4 degradation after the ubiquitylation step. Consequently, these signal inhibitors sensitize cells to the PROTAC-induced apoptosis. These results suggest that various cell-intrinsic signaling pathways spontaneously counteract chemically induced target degradation at multiple steps, which could be liberated by specific inhibitors.
Non-invasive and noise-robust light focusing using confocal wavefront shaping
Authors: Aizik Dror , Levin Anat
Published: July 2024

Wavefront-shaping is a promising approach for imaging fluorescent targets deep inside scattering tissue despite strong aberrations. It enables focusing an incoming illumination into a single spot inside tissue, as well as correcting the outgoing light scattered from the tissue. Previously, wavefront shaping modulations have been successively estimated using feedback from strong fluorescent beads, which have been manually added to a sample. However, such algorithms do not generalize to neurons whose emission is orders of magnitude weaker. We suggest a wavefront shaping approach that works with a confocal modulation of both the illumination and imaging arms. Since the aberrations are corrected in the optics before the detector, the low photon budget is directed into a single sensor spot and detected with high signal-noise ratio. We derive a score function for modulation evaluation from mathematical principles, and successfully use it to image fluorescence neurons, despite scattering through thick tissue.
Tamm-cavity terahertz detector
Authors: Tu Xuecou , Zhang Yichen , Zhou Shuyu , Tang Wenjing , Yan Xu , Rui Yunjie , Wang Wohu , Yan Bingnan , Zhang Chen , Ye Ziyao , Shi Hongkai , Su Runfeng , Wan Chao , Dong Daxing , Xu Ruiying , Zhao Qing-Yuan , Zhang La-Bao , Jia Xiao-Qing , Wang Huabing , Kang Lin , Chen Jian , Wu Peiheng
Published: July 2024

Efficiently fabricating a cavity that can achieve strong interactions between terahertz waves and matter would allow researchers to exploit the intrinsic properties due to the long wavelength in the terahertz waveband. Here we show a terahertz detector embedded in a Tamm cavity with a record Q value of 1017 and a bandwidth of only 469 MHz for direct detection. The Tamm-cavity detector is formed by embedding a substrate with an Nb5N6 microbolometer detector between an Si/air distributed Bragg reflector (DBR) and a metal reflector. The resonant frequency can be controlled by adjusting the thickness of the substrate layer. The detector and DBR are fabricated separately, and a large pixel-array detector can be realized by a very simple assembly process. This versatile cavity structure can be used as a platform for preparing high-performance terahertz devices and opening up the study of the strong interactions between terahertz waves and matter.
Accurate Prediction of Protein Structural Flexibility by Deep Learning Integrating Intricate Atomic Structures and Cryo-EM Density Information
Authors: Song Xintao , Bao Lei , Feng Chenjie , Huang Qiang , Zhang Fa , Gao Xin , Han Renmin
Published: July 2024

The dynamics of proteins are crucial for understanding their mechanisms. However, computationally predicting protein dynamic information has proven challenging. Here, we propose a neural network model, RMSF-net, which outperforms previous methods and produces the best results in a large-scale protein dynamics dataset; this model can accurately infer the dynamic information of a protein in only a few seconds. By learning effectively from experimental protein structure data and cryo-electron microscopy (cryo-EM) data integration, our approach is able to accurately identify the interactive bidirectional constraints and supervision between cryo-EM maps and PDB models in maximizing the dynamic prediction efficacy. Rigorous 5-fold cross-validation on the dataset demonstrates that RMSF-net achieves test correlation coefficients of 0.746 ± 0.127 at the voxel level and 0.765 ± 0.109 at the residue level, showcasing its ability to deliver dynamic predictions closely approximating molecular dynamics simulations. Additionally, it offers real-time dynamic inference with minimal storage overhead on the order of megabytes. RMSF-net is a freely accessible tool and is anticipated to play an essential role in the study of protein dynamics.
Acquisition of non-olfactory encoding improves odour discrimination in olfactory cortex
Authors: Federman Noel , Romano Sebastián A. , Amigo-Duran Macarena , Salomon Lucca , Marin-Burgin Antonia
Published: July 2024

Olfaction is influenced by contextual factors, past experiences, and the animal’s internal state. Whether this information is integrated at the initial stages of cortical odour processing is not known, nor how these signals may influence odour encoding. Here we revealed multiple and diverse non-olfactory responses in the primary olfactory (piriform) cortex (PCx), which dynamically enhance PCx odour discrimination according to behavioural demands. We performed recordings of PCx neurons from mice trained in a virtual reality task to associate odours with visual contexts to obtain a reward. We found that learning shifts PCx activity from encoding solely odours to a regime in which positional, contextual, and associative responses emerge on odour-responsive neurons that become mixed-selective. The modulation of PCx activity by these non-olfactory signals was dynamic, improving odour decoding during task engagement and in rewarded contexts. This improvement relied on the acquired mixed-selectivity, demonstrating how integrating extra-sensory inputs in sensory cortices can enhance sensory processing while encoding the behavioural relevance of stimuli.
The mastery of details in the workflow of materials machine learning
Authors: Ma Yingying , Xu Pengcheng , Li Minjie , Ji Xiaobo , Zhao Wenyue , Lu Wencong
Published: July 2024

As machine learning (ML) continues to advance in the field of materials science, the variation in strategies for the same steps of the ML workflow becomes increasingly significant. These details can have a substantial impact on results, yet they have not received the deserved attention. This review aims to explore the various strategies available for each detail within the general workflow of materials ML. Firstly, the general workflow of materials ML will be introduced to help readers gain an understanding of potential details. Subsequently, different strategies of details within each step of the workflow will be presented through state-of-the-art case studies. The potential outcomes associated with choosing different strategies to details will be explored. Following this, suitable strategies for details will be recommended based on distinct application scenarios. Finally, directions for the future development of materials ML concerning details will be proposed. Through these discussions, we aspire to offer a comprehensive understanding of the nuances in details within materials ML. This will serve as valuable reference and guidance for researchers in both materials science and ML.
Calcium-rich dairy matrix protects better than mineral calcium against colonic luminal haem-induced alterations in male rats
Authors: Olier Maïwenn , Naud Nathalie , Fouché Edwin , Tondereau Valérie , Ahn Ingrid , Leconte Nadine , Blas-Y-Estrada Florence , Garric Gilles , Heliès-Toussaint Cécile , Harel-Oger Marielle , Marmonier Corinne , Théodorou Vassilia , Guéraud Françoise , Jan Gwénaël , Pierre Fabrice
Published: July 2024

The haemoglobin content in meat is consistently associated with an increased risk of colorectal cancer, whereas calcium may play a role as a chemopreventive agent. Using rodent models, calcium salts have been shown to prevent the promotion of haem-induced and red meat-induced colorectal carcinogenesis by limiting the bioavailability of the gut luminal haem iron. Therefore, this study aimed to compare impacts of dietary calcium provided as calcium salts or dairy matrix on gut homoeostasis perturbations by high haeminic or non-haeminic iron intakes. A 3-week intervention study was conducted using Fischer 344 rats. Compared to the ferric citrate-enriched diet, the haemoglobin-enriched diet led to increased faecal, mucosal, and urinary lipoperoxidation-related biomarkers, resulting from higher gut luminal haem iron bioavailability. This redox imbalance was associated to a dysbiosis of faecal microbiota. The addition of calcium to haemoglobin-enriched diets limited haem iron bioavailability and counteracted redox imbalance, with improved preventive efficacy when calcium was provided in dairy matrix. Data integration revealed correlations between haem-induced lipoperoxidation products and bacterial communities belonging to Peptococcaceae, Eubacterium coprostanoligenes group, and Bifidobacteriaceae. This integrated approach provides evidence of the benefits of dairy matrix as a dietary calcium vehicle to counteract the deleterious side-effects of meat consumption.
Point-of-use filtration units as drinking water distribution system sentinels
Authors: Bai Weiliang , Xu Ruizhe , Podar Mircea , Swift Cynthia M. , Saleh Navid B. , Löffler Frank E. , Alvarez Pedro J. J. , Kumar Manish
Published: July 2024

Municipal drinking water distribution systems (DWDSs) and associated premise plumbing (PP) systems are vulnerable to proliferation of opportunistic pathogens, even when chemical disinfection residuals are present, thus presenting a public health risk. Monitoring the structure of microbial communities of drinking water is challenging because of limited continuous access to faucets, pipes, and storage tanks. We propose a scalable household sampling method, which uses spent activated carbon and reverse osmosis (RO) membrane point-of-use (POU) filters to evaluate mid- to long-term occurrence of microorganisms in PP systems that are relevant to consumer exposure. As a proof of concept, POU filter microbiomes were collected from four different locations and analyzed with 16S rRNA gene amplicon sequencing. The analyses revealed distinct microbial communities, with occasional detection of potential pathogens. The findings highlight the importance of local, and if possible, continuous monitoring within and across distribution systems. The continuous operation of POU filters offers an advantage in capturing species that may be missed by instantaneous sampling methods. We suggest that water utilities, public institutions, and regulatory agencies take advantage of end-of-life POU filters for microbial monitoring. This approach can be easily implemented to ensure drinking water safety, especially from microbes of emerging concerns; e.g., pathogenic Legionella and Mycobacterium species.
Sustained increases in atmospheric oxygen and marine productivity in the Neoproterozoic and Palaeozoic eras
Authors: Stockey Richard G. , Cole Devon B. , Farrell Una C. , Agić Heda , Boag Thomas H. , Brocks Jochen J. , Canfield Don E. , Cheng Meng , Crockford Peter W. , Cui Huan , Dahl Tais W. , Del Mouro Lucas , Dewing Keith , Dornbos Stephen Q. , Emmings Joseph F. , Gaines Robert R. , Gibson Timothy M. , Gill Benjamin C. , Gilleaudeau Geoffrey J. , Goldberg Karin , Guilbaud Romain , Halverson Galen , Hammarlund Emma U. , Hantsoo Kalev , Henderson Miles A. , Henderson Charles M. , Hodgskiss Malcolm S. W. , Jarrett Amber J. M. , Johnston David T. , Kabanov Pavel , Kimmig Julien , Knoll Andrew H. , Kunzmann Marcus , LeRoy Matthew A. , Li Chao , Loydell David K. , Macdonald Francis A. , Magnall Joseph M. , Mills N. Tanner , Och Lawrence M. , O’Connell Brennan , Pagès Anais , Peters Shanan E. , Porter Susannah M. , Poulton Simon W. , Ritzer Samantha R. , Rooney Alan D. , Schoepfer Shane , Smith Emily F. , Strauss Justin V. , Uhlein Gabriel Jubé , White Tristan , Wood Rachel A. , Woltz Christina R. , Yurchenko Inessa , Planavsky Noah J. , Sperling Erik A.
Published: July 2024

A geologically rapid Neoproterozoic oxygenation event is commonly linked to the appearance of marine animal groups in the fossil record. However, there is still debate about what evidence from the sedimentary geochemical record—if any—provides strong support for a persistent shift in surface oxygen immediately preceding the rise of animals. We present statistical learning analyses of a large dataset of geochemical data and associated geological context from the Neoproterozoic and Palaeozoic sedimentary record and then use Earth system modelling to link trends in redox-sensitive trace metal and organic carbon concentrations to the oxygenation of Earth’s oceans and atmosphere. We do not find evidence for the wholesale oxygenation of Earth’s oceans in the late Neoproterozoic era. We do, however, reconstruct a moderate long-term increase in atmospheric oxygen and marine productivity. These changes to the Earth system would have increased dissolved oxygen and food supply in shallow-water habitats during the broad interval of geologic time in which the major animal groups first radiated. This approach provides some of the most direct evidence for potential physiological drivers of the Cambrian radiation, while highlighting the importance of later Palaeozoic oxygenation in the evolution of the modern Earth system.
Quantifying short-range order using atom probe tomography
Authors: He Mengwei , Davids William J. , Breen Andrew J. , Ringer Simon P.
Published: July 2024

Medium- and high-entropy alloys are an emerging class of materials that can exhibit outstanding combinations of strength and ductility for engineering applications. Computational simulations have suggested the presence of short-range order (SRO) in these alloys, and recent experimental evidence is also beginning to emerge. Unfortunately, the difficulty in quantifying the SRO under different heat treatment conditions has generated much debate on the atomic preferencing and implications of SRO on mechanical properties. Here we develop an approach to measure SRO using atom probe tomography. This method balances the limitations of atom probe tomography with the threshold values of SRO to map the regimes where the required atomistic neighbourhood information is preserved and where it is not. We demonstrate the method with a case study of the CoCrNi alloy and use this to monitor SRO changes induced by heat treatments. These species-specific SRO measurements enable the generation of computational simulations of atomic neighbourhood models that are equivalent to the experiment and can contribute to the further understanding and design of medium- and high-entropy alloys and other materials systems where SRO may occur.
High-dimensional single-cell analysis of human natural killer cell heterogeneity
Authors: Rebuffet Lucas , Melsen Janine E. , Escalière Bertrand , Basurto-Lozada Daniela , Bhandoola Avinash , Björkström Niklas K. , Bryceson Yenan T. , Castriconi Roberta , Cichocki Frank , Colonna Marco , Davis Daniel M. , Diefenbach Andreas , Ding Yi , Haniffa Muzlifah , Horowitz Amir , Lanier Lewis L. , Malmberg Karl-Johan , Miller Jeffrey S. , Moretta Lorenzo , Narni-Mancinelli Emilie , O’Neill Luke A. J. , Romagnani Chiara , Ryan Dylan G. , Sivori Simona , Sun Dan , Vagne Constance , Vivier Eric
Published: July 2024

Natural killer (NK) cells are innate lymphoid cells (ILCs) contributing to immune responses to microbes and tumors. Historically, their classification hinged on a limited array of surface protein markers. Here, we used single-cell RNA sequencing (scRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to dissect the heterogeneity of NK cells. We identified three prominent NK cell subsets in healthy human blood: NK1, NK2 and NK3, further differentiated into six distinct subgroups. Our findings delineate the molecular characteristics, key transcription factors, biological functions, metabolic traits and cytokine responses of each subgroup. These data also suggest two separate ontogenetic origins for NK cells, leading to divergent transcriptional trajectories. Furthermore, we analyzed the distribution of NK cell subsets in the lung, tonsils and intraepithelial lymphocytes isolated from healthy individuals and in 22 tumor types. This standardized terminology aims at fostering clarity and consistency in future research, thereby improving cross-study comparisons.
Direct neuronal reprogramming of mouse astrocytes is associated with multiscale epigenome remodeling and requires Yy1
Authors: Pereira Allwyn , Diwakar Jeisimhan , Masserdotti Giacomo , Beşkardeş Sude , Simon Tatiana , So Younju , Martín-Loarte Lucía , Bergemann Franziska , Vasan Lakshmy , Schauer Tamas , Danese Anna , Bocchi Riccardo , Colomé-Tatché Maria , Schuurmans Carol , Philpott Anna , Straub Tobias , Bonev Boyan , Götz Magdalena
Published: July 2024

Direct neuronal reprogramming is a promising approach to regenerate neurons from local glial cells. However, mechanisms of epigenome remodeling and co-factors facilitating this process are unclear. In this study, we combined single-cell multiomics with genome-wide profiling of three-dimensional nuclear architecture and DNA methylation in mouse astrocyte-to-neuron reprogramming mediated by Neurogenin2 (Ngn2) and its phosphorylation-resistant form (PmutNgn2), respectively. We show that Ngn2 drives multilayered chromatin remodeling at dynamic enhancer–gene interaction sites. PmutNgn2 leads to higher reprogramming efficiency and enhances epigenetic remodeling associated with neuronal maturation. However, the differences in binding sites or downstream gene activation cannot fully explain this effect. Instead, we identified Yy1, a transcriptional co-factor recruited by direct interaction with Ngn2 to its target sites. Upon deletion of Yy1, activation of neuronal enhancers, genes and ultimately reprogramming are impaired without affecting Ngn2 binding. Thus, our work highlights the key role of interactors of proneural factors in direct neuronal reprogramming.
LMBiS-Net: A lightweight bidirectional skip connection based multipath CNN for retinal blood vessel segmentation
Authors: Matloob Abbasi Mufassir , Iqbal Shahzaib , Aurangzeb Khursheed , Alhussein Musaed , Khan Tariq M.
Published: July 2024

Blinding eye diseases are often related to changes in retinal structure, which can be detected by analysing retinal blood vessels in fundus images. However, existing techniques struggle to accurately segment these delicate vessels. Although deep learning has shown promise in medical image segmentation, its reliance on specific operations can limit its ability to capture crucial details such as the edges of the vessel. This paper introduces LMBiS-Net, a lightweight convolutional neural network designed for the segmentation of retinal vessels. LMBiS-Net achieves exceptional performance with a remarkably low number of learnable parameters (only 0.172 million). The network used multipath feature extraction blocks and incorporates bidirectional skip connections for the information flow between the encoder and decoder. In addition, we have optimised the efficiency of the model by carefully selecting the number of filters to avoid filter overlap. This optimisation significantly reduces training time and improves computational efficiency. To assess LMBiS-Net’s robustness and ability to generalise to unseen data, we conducted comprehensive evaluations on four publicly available datasets: DRIVE, STARE, CHASE_DB1, and HRF The proposed LMBiS-Net achieves significant performance metrics in various datasets. It obtains sensitivity values of 83.60%, 84.37%, 86.05%, and 83.48%, specificity values of 98.83%, 98.77%, 98.96%, and 98.77%, accuracy (acc) scores of 97.08%, 97.69%, 97.75%, and 96.90%, and AUC values of 98.80%, 98.82%, 98.71%, and 88.77% on the DRIVE, STARE, CHEASE_DB, and HRF datasets, respectively. In addition, it records F1 scores of 83.43%, 84.44%, 83.54%, and 78.73% on the same datasets. Our evaluations demonstrate that LMBiS-Net achieves high segmentation accuracy (acc) while exhibiting both robustness and generalisability across various retinal image datasets. This combination of qualities makes LMBiS-Net a promising tool for various clinical applications.
Model test study of bridge pile horizontal bearing behavior under landslide deformation
Authors: Zhao Yan-yan , Fu Hai-ying , Yang Tao , Zhou Ming-zhe , Li Huan
Published: July 2024

Pile is a common foundation on the slope, which poses a serious threat to the construction and operation if the slope deformation and causes landslide. In this study, a model device of pile foundation on landslide was independently developed by relative displacement loading between pile and soil to explore the influence of landslide deformation on pile and analysis the soil failure rule and the deformation characteristics of pile in different stages of landslide deformation, a few model tests were completed including the relative displacement between soil and pile from 1 to 17 cm, and the pile diameter and the modulus of slide bed were also considered. The results indicated that: the evolution process of landslide deformation with pile foundation on could be divided into four stages including soil compaction, cracks growth, yield stage, and failure stage; ratios of the maximum soil pressure and bending moment growth from the soil compaction stage to the cracks growth stage to the total growth in these four stages are both exceeding 60%; the soil pressure increases with the increase of pile diameter and sliding bed modulus. Therefore, it is best to effectively monitor and control the landslide in the initial soil compression stage that in soil compaction stage and methods such as increasing pile foundations or reinforcing the sliding bed can be used for protection.
Heavy metal concentrations and clinical symptoms in patients diagnosed with schizophrenia related to cigarette smoking
Authors: Ghaderi Amir , Khoshakhlagh Amir Hossein , Gruszecka-Kosowska Agnieszka , Askari-Lemjiri Fatemeh , Alemi Fatemeh , Molavi Nader , Hazegh Pooya , Farokhi Bahareh , Dehkohneh Somayeh Ghadami , Ghoreishi Fatemeh Sadat
Published: July 2024

In our study, blood concentrations of lead (Pb), arsenic (As), and cadmium (Cd) and urine concentrations of thallium (Tl) were measured together with related symptoms of heavy metal poisoning in cigarette smoking volunteers diagnosed with schizophrenia, in cigarette smokers not diagnosed with schizophrenia, and in the control group of non-smokers and not diagnosed with schizophrenia volunteers. Our study was performed on 171 volunteers divided into the following subgroups: patients diagnosed with schizophrenia with at least 1 year of continuous cigarette smoking experience (56 participants), cigarette smokers not diagnosed with schizophrenia with at least one year of continuous smoking experience (58), and control group (not diagnosed with schizophrenia and non-smoking volunteers) (57). Smoking durations of cigarette smokers diagnosed with schizophrenia and cigarette smokers not diagnosed with schizophrenia are not similar (p = 0.431). Blood Pb, As, and Cd concentrations and urine Tl concentrations were the highest in the subgroup of cigarette smokers not diagnosed with schizophrenia, followed by the subgroup of cigarette smokers diagnosed with schizophrenia, and the control group. Only blood Pb concentrations were significantly higher (probability value p < 0.05) in the group of cigarette smokers not diagnosed with schizophrenia (5.16 μg/dL), comparing to the group of cigarette smokers diagnosed with schizophrenia (3.83 μg/dL) and to the control group (3.43 μg/dL). Blood Cd and As concentrations and urine Tl concentrations were significantly higher (p < 0.05) in cigarette smokers not diagnosed with schizophrenia than in the control group. The results revealed a statistically significant positive correlation (p < 0.001) in the cigarette smokers in the schizophrenia diagnosed group between blood Pb, blood As, and urine Tl concentrations and the duration of cigarette smoking.
Epidemiological exploration of fleas and molecular identification of flea-borne viruses in Egyptian small ruminants
Authors: Barghash Safaa M. , Yassin Samah E. , Sadek Al-Shaimaa M. , Mahmoud Dalia M. , Salama Mohamed S.
Published: July 2024

The study aimed to investigate molecularly the presence of flea-borne viruses in infested small ruminants with fleas. It was carried out in Egypt’s Northern West Coast (NWC) and South Sinai Governorate (SSG). Three specific primers were used targeting genes, ORF103 (for Capripoxvirus and Lumpy skin disease virus), NS3 (for Bluetongue virus), and Rdrp (for Coronavirus), followed by gene sequencing and phylogenetic analyses. The results revealed that 78.94% of sheep and 65.63% of goats were infested in the NWC area, whereas 49.76% of sheep and 77.8% of goats were infested in the SSG region. Sheep were preferable hosts for flea infestations (58.9%) to goats (41.1%) in the two studied areas. Sex and age of the animals had no effects on the infestation rate (p > 0.05). The season and site of infestation on animals were significantly different between the two areas (p < 0.05). Ctenocephalides felis predominated in NWC and Ctenocephalides canis in SSG, and males of both flea species were more prevalent than females. Molecular analysis of flea DNA revealed the presence of Capripoxvirus in all tested samples, while other viral infections were absent. Gene sequencing identified three isolates as sheeppox viruses, and one as goatpox virus. The findings suggest that Capripoxvirus is adapted to fleas and may be transmitted to animals through infestation. This underscores the need for ongoing surveillance of other pathogens in different regions of Egypt.
Automated eyeball volume measurement based on CT images using neural network-based segmentation and simple estimation
Authors: Han Sujeong , Lee Jeong Kyu , Lee Daewon , Lee Jaesung
Published: July 2024

With the increase in the dependency on digital devices, the incidence of myopia, a precursor of various ocular diseases, has risen significantly. Because myopia and eyeball volume are related, myopia progression can be monitored through eyeball volume estimation. However, existing methods are limited because the eyeball shape is disregarded during estimation. We propose an automated eyeball volume estimation method from computed tomography images that incorporates prior knowledge of the actual eyeball shape. This study involves data preprocessing, image segmentation, and volume estimation steps, which include the truncated cone formula and integral equation. We obtained eyeball image masks using U-Net, HFCN, DeepLab v3 +, SegNet, and HardNet-MSEG. Data from 200 subjects were used for volume estimation, and manually extracted eyeball volumes were used for validation. U-Net outperformed among the segmentation models, and the proposed volume estimation method outperformed comparative methods on all evaluation metrics, with a correlation coefficient of 0.819, mean absolute error of 0.640, and mean squared error of 0.554. The proposed method surpasses existing methods, provides an accurate eyeball volume estimation for monitoring the progression of myopia, and could potentially aid in the diagnosis of ocular diseases. It could be extended to volume estimation of other ocular structures.
Multi-branch CNN and grouping cascade attention for medical image classification
Authors: Liu Shiwei , Yue Wenwen , Guo Zhiqing , Wang Liejun
Published: July 2024

Visual Transformers(ViT) have made remarkable achievements in the field of medical image analysis. However, ViT-based methods have poor classification results on some small-scale medical image classification datasets. Meanwhile, many ViT-based models sacrifice computational cost for superior performance, which is a great challenge in practical clinical applications. In this paper, we propose an efficient medical image classification network based on an alternating mixture of CNN and Transformer tandem, which is called Eff-CTNet. Specifically, the existing ViT-based method still mainly relies on multi-head self-attention (MHSA). Among them, the attention maps of MHSA are highly similar, which leads to computational redundancy. Therefore, we propose a group cascade attention (GCA) module to split the feature maps, which are provided to different attention heads to further improves the diversity of attention and reduce the computational cost. In addition, we propose an efficient CNN (EC) module to enhance the ability of the model and extract the local detail information in medical images. Finally, we connect them and design an efficient hybrid medical image classification network, namely Eff-CTNet. Extensive experimental results show that our Eff-CTNet achieves advanced classification performance with less computational cost on three public medical image classification datasets.
The severity of dry eye symptoms and risk factors among university students in Saudi Arabia: a cross-sectional study
Authors: Alqurashi Anas , Almaghrabi Hatim , Alahmadi Muath , Alotaibi Abdulaziz , Alotaibi Bandar , Jastaniah Abdulaziz , Bukhari Ameera , Binhussein Mohammad , Othman Basant , Khojah Amer
Published: July 2024

Dry eye syndrome (DES) is a tear film disorder caused by increased tear evaporation or decreased production. The heavy workload on the eye and the increased usage of digital screens may decrease blink frequency, leading to an increased evaporation rate and an upsurge in the incidence and severity of DES. This study aims to assess the severity of DES symptoms and the risk factors among university students. A cross-sectional study was conducted at Umm AlQura University to evaluate the severity of DES among students and explore its potential association with digital screen use. Validated questionnaires were used to assess the severity of DES and digital screen usage. The study included 457 participants, of which 13% had symptoms suggestive of severe DES. Furthermore, multiple risk factors had a significant association with the severity of DES, including gender, use of monitor filters, monitor and room brightness, and smoking habits. DES symptoms were prevalent among university students, particularly female students. Although there was no significant association with the duration of screen usage and collage distribution. Other factors however, such as the usage of screen monitors and the brightness of both the monitor and the room, were significantly associated with the severity of DES symptoms.
The influence mechanism analysis on the farmers’ intention to adopt Internet of Things based on UTAUT-TOE model
Authors: Li Lianying , Min Xin , Guo Jinyong , Wu Feng
Published: July 2024

Internet of Things (IoT) technologies are widely recognized as one of the most important infrastructures for economic development and technological innovation. By analyzing the influencing factors of vegetable farmers’ intention to adopt agricultural IoT, it helps to formulate effective IoT promotion policies and accelerate the realization of agricultural modernization. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology-Organization-Environment (TOE) theory, this study constructed for the first time a mechanism model of the influence of vegetable farmers’ intention to adopt IoT, expanding the scope of current research on agricultural IoT and revealing the intrinsic influence mechanism of farmers’ adoption of IoT technologies. In this study, 357 quantitative data were obtained by a questionnaire survey, and structural equation modeling was used to test the direct and indirect effects of each factor on vegetable farmers’ intention to adopt IoT. The results show that almost all variables in TOE have significant direct impacts on the intention, while no variables in UTAUT have significant direct impacts. Among variables in TOE, government support and complexity are the two most important elements influencing the intention. Although the interactions among variables in TOE and UTAUT are also found, the indirect effects of variables are non-significant. Therefore, it is proposed to reduce the complexity of operation and use of IoT technologies; improve rural information infrastructure and compatibility of IoT platforms and devices; and governments should increase subsidies, and incentives to promote the use of IoT in agriculture and agricultural practices.
Real-Time multifaceted artificial intelligence vs In-Person instruction in teaching surgical technical skills: a randomized controlled trial
Authors: Yilmaz Recai , Bakhaidar Mohamad , Alsayegh Ahmad , Abou Hamdan Nour , Fazlollahi Ali M. , Tee Trisha , Langleben Ian , Winkler-Schwartz Alexander , Laroche Denis , Santaguida Carlo , Del Maestro Rolando F.
Published: July 2024

Trainees develop surgical technical skills by learning from experts who provide context for successful task completion, identify potential risks, and guide correct instrument handling. This expert-guided training faces significant limitations in objectively assessing skills in real-time and tracking learning. It is unknown whether AI systems can effectively replicate nuanced real-time feedback, risk identification, and guidance in mastering surgical technical skills that expert instructors offer. This randomized controlled trial compared real-time AI feedback to in-person expert instruction. Ninety-seven medical trainees completed a 90-min simulation training with five practice tumor resections followed by a realistic brain tumor resection. They were randomly assigned into 1-real-time AI feedback, 2-in-person expert instruction, and 3-no real-time feedback. Performance was assessed using a composite-score and Objective Structured Assessment of Technical Skills rating, rated by blinded experts. Training with real-time AI feedback (n = 33) resulted in significantly better performance outcomes compared to no real-time feedback (n = 32) and in-person instruction (n = 32), .266, [95% CI .107 .425], p < .001; .332, [95% CI .173 .491], p = .005, respectively. Learning from AI resulted in similar OSATS ratings (4.30 vs 4.11, p = 1) compared to in-person training with expert instruction. Intelligent systems may refine the way operating skills are taught, providing tailored, quantifiable feedback and actionable instructions in real-time.
Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm
Authors: Karbasi Masoud , Ali Mumtaz , Bateni Sayed M. , Jun Changhyun , Jamei Mehdi , Farooque Aitazaz Ahsan , Yaseen Zaher Mundher
Published: July 2024

Electrical conductivity (EC) is widely recognized as one of the most essential water quality metrics for predicting salinity and mineralization. In the current research, the EC of two Australian rivers (Albert River and Barratta Creek) was forecasted for up to 10 days using a novel deep learning algorithm (Convolutional Neural Network combined with Long Short-Term Memory Model, CNN-LSTM). The Boruta-XGBoost feature selection method was used to determine the significant inputs (time series lagged data) to the model. To compare the performance of Boruta-XGB-CNN-LSTM models, three machine learning approaches—multi-layer perceptron neural network (MLP), K-nearest neighbour (KNN), and extreme gradient boosting (XGBoost) were used. Different statistical metrics, such as correlation coefficient (R), root mean square error (RMSE), and mean absolute percentage error, were used to assess the models' performance. From 10 years of data in both rivers, 7 years (2012–2018) were used as a training set, and 3 years (2019–2021) were used for testing the models. Application of the Boruta-XGB-CNN-LSTM model in forecasting one day ahead of EC showed that in both stations, Boruta-XGB-CNN-LSTM can forecast the EC parameter better than other machine learning models for the test dataset (R = 0.9429, RMSE = 45.6896, MAPE = 5.9749 for Albert River, and R = 0.9215, RMSE = 43.8315, MAPE = 7.6029 for Barratta Creek). Considering the better performance of the Boruta-XGB-CNN-LSTM model in both rivers, this model was used to forecast 3–10 days ahead of EC. The results showed that the Boruta-XGB-CNN-LSTM model is very capable of forecasting the EC for the next 10 days. The results showed that by increasing the forecasting horizon from 3 to 10 days, the performance of the Boruta-XGB-CNN-LSTM model slightly decreased. The results of this study show that the Boruta-XGB-CNN-LSTM model can be used as a good soft computing method for accurately predicting how the EC will change in rivers.
Understanding the value of monocyte distribution width (MDW) in acutely ill medical patients presenting to the emergency department: a prospective single center evaluation
Authors: Kralovcova Marcela , Müller Jiri , Hajsmanova Zdenka , Sigutova Pavla , Bultasova Lenka , Palatova Jana , Matejovic Martin
Published: July 2024

The monocyte distribution width (MDW) has emerged as a promising biomarker for accurate and early identification of patients with potentially life-threatening infections. Here we tested the diagnostic performance of MDW in adult patients requiring hospital admission for community-acquired infections and sepsis, evaluated sources of heterogeneity in the estimates of diagnostic accuracy, and assessed the meaning of MDW in a patient population presenting to the emergency department (ED) for acute non-infectious conditions. 1925 consecutive patients were categorized into three groups: non-infection (n = 1507), infection (n = 316), and sepsis/septic shock (n = 102). Diagnostic performance for infection or sepsis of MDW alone or in combination with components of SOFA was tested using AUC of ROC curves, sensitivity, and specificity. The relationship between MDW and different pathogens as well as the impact of non-infectious conditions on MDW values were explored. For the prediction of infection, the AUC/ROC of MDW (0.84) was nearly overlapping that of procalcitonin (0.83), and C-reactive protein (0.89). Statistical optimal cut-off value for MDW was 21 for predicting infection (sensitivity 73%, specificity 82%) and 22 for predicting sepsis (sensitivity 79%, specificity 83%). The best threshold to rule out infection was MDW ≤ 17 (NPV 96.9, 95% CI 88.3–100.0), and ≤ 18 (NPV 99.5, 95% CI 98.3–100.0) to rule out sepsis. The combination of MDW with markers of organ dysfunction (creatinine, bilirubin, platelets) substantially improved the AUC (0.96 (95% CI 0.94–0.97); specificity and sensitivity of 88% and 94%, respectively). In conclusion, MDW has a good diagnostic performance in diagnosing infection and sepsis in patients presenting in ED. Its use as an infection marker even increases when combined with other markers of organ dysfunction. Understanding the impact of interactions of non-infectious conditions and comorbidities on MDW and its diagnostic accuracy requires further elucidation.
Real-time and video-recorded pain assessment in beef cattle: clinical application and reliability in young, adult bulls undergoing surgical castration
Authors: Tomacheuski Rubia Mitalli , de Oliveira Alice Rodrigues , Trindade Pedro Henrique Esteves , Lopez-Soriano Magdiel , Merenda Victoria Rocha , Luna Stelio P. Loureiro , Pairis-Garcia Monique D.
Published: July 2024

Bovine pain assessment relies on validated behavioral scales related to normal and pain-related behaviors. This study investigated the reliability and applicability of real-time and video-recorded pain assessment, and their agreement, in young, adult bulls undergoing surgical castration. Ten Nelore and nine Angus bulls underwent general anesthesia and surgical castration. Three-minute real-time observations and simultaneous videos were recorded at − 48 h (M0), before sedation, under fasting (M1), after surgery, 3 h after sternal recumbency (M2), after rescue analgesia (M3) and at 24 h (M4). Animals received morphine (after M2), dipyrone (after M3), and flunixin meglumine after surgical castration (M4). Two trained evaluators assessed real-time (n = 95) and video-recorded time-points (n = 95) using the Unesp-Botucatu Cattle Pain Scale (UCAPS). Both assessment methods inferred ‘very good’ reliability (≥ 0.81) with minimal bias, however, video-recorded assessment (4.33 ± 2.84) demonstrated slightly higher scores compared to real-time (3.08 ± 2.84). The results from this study suggest that UCAPS can be used in real-time or video-recorded to assess pain and guide analgesic therapy in cattle.