bluuebunny/crossref_metadata_2025 huggingface dataset:
The crosstalk between mitochondrial quality control and metal-dependent cell death
Authors: Zhou Qi-yuan , Ren Chao , Li Jing-yan , Wang Lu , Duan Yu , Yao Ren-qi , Tian Ying-ping , Yao Yong-ming
Published: April 2024

Mitochondria are the centers of energy and material metabolism, and they also serve as the storage and dispatch hubs of metal ions. Damage to mitochondrial structure and function can cause abnormal levels and distribution of metal ions, leading to cell dysfunction and even death. For a long time, mitochondrial quality control pathways such as mitochondrial dynamics and mitophagy have been considered to inhibit metal-induced cell death. However, with the discovery of new metal-dependent cell death including ferroptosis and cuproptosis, increasing evidence shows that there is a complex relationship between mitochondrial quality control and metal-dependent cell death. This article reviews the latest research results and mechanisms of crosstalk between mitochondrial quality control and metal-dependent cell death in recent years, as well as their involvement in neurodegenerative diseases, tumors and other diseases, in order to provide new ideas for the research and treatment of related diseases.
Plasma-assisted manipulation of vanadia nanoclusters for efficient selective catalytic reduction of NOx
Authors: Yin Yong , Luo Bingcheng , Li Kezhi , Moskowitz Benjamin M. , Mosevitzky Lis Bar , Wachs Israel E. , Zhu Minghui , Sun Ye , Zhu Tianle , Li Xiang
Published: April 2024

Supported nanoclusters (SNCs) with distinct geometric and electronic structures have garnered significant attention in the field of heterogeneous catalysis. However, their directed synthesis remains a challenge due to limited efficient approaches. This study presents a plasma-assisted treatment strategy to achieve supported metal oxide nanoclusters from a rapid transformation of monomeric dispersed metal oxides. As a case study, oligomeric vanadia-dominated surface sites were derived from the classic supported V2O5-WO3/TiO2 (VWT) catalyst and showed nearly an order of magnitude increase in turnover frequency (TOF) value via an H2-plasma treatment for selective catalytic reduction of NO with NH3. Such oligomeric surface VOx sites were not only successfully observed and firstly distinguished from WOx and TiO2 by advanced electron microscopy, but also facilitated the generation of surface amide and nitrates intermediates that enable barrier-less steps in the SCR reaction as observed by modulation excitation spectroscopy technologies and predicted DFT calculations.
scLENS: data-driven signal detection for unbiased scRNA-seq data analysis
Authors: Kim Hyun , Chang Won , Chae Seok Joo , Park Jong-Eun , Seo Minseok , Kim Jae Kyoung
Published: April 2024

High dimensionality and noise have limited the new biological insights that can be discovered in scRNA-seq data. While dimensionality reduction tools have been developed to extract biological signals from the data, they often require manual determination of signal dimension, introducing user bias. Furthermore, a common data preprocessing method, log normalization, can unintentionally distort signals in the data. Here, we develop scLENS, a dimensionality reduction tool that circumvents the long-standing issues of signal distortion and manual input. Specifically, we identify the primary cause of signal distortion during log normalization and effectively address it by uniformizing cell vector lengths with L2 normalization. Furthermore, we utilize random matrix theory-based noise filtering and a signal robustness test to enable data-driven determination of the threshold for signal dimensions. Our method outperforms 11 widely used dimensionality reduction tools and performs particularly well for challenging scRNA-seq datasets with high sparsity and variability. To facilitate the use of scLENS, we provide a user-friendly package that automates accurate signal detection of scRNA-seq data without manual time-consuming tuning.
The hinge-engineered IgG1-IgG3 hybrid subclass IgGh47 potently enhances Fc-mediated function of anti-streptococcal and SARS-CoV-2 antibodies
Authors: Izadi Arman , Karami Yasaman , Bratanis Eleni , Wrighton Sebastian , Khakzad Hamed , Nyblom Maria , Olofsson Berit , Happonen Lotta , Tang Di , Sundwall Martin , Godzwon Magdalena , Chao Yashuan , Toledo Alejandro Gomez , Schmidt Tobias , Ohlin Mats , Nilges Michael , Malmström Johan , Bahnan Wael , Shannon Oonagh , Malmström Lars , Nordenfelt Pontus
Published: April 2024

Streptococcus pyogenes can cause invasive disease with high mortality despite adequate antibiotic treatments. To address this unmet need, we have previously generated an opsonic IgG1 monoclonal antibody, Ab25, targeting the bacterial M protein. Here, we engineer the IgG2-4 subclasses of Ab25. Despite having reduced binding, the IgG3 version promotes stronger phagocytosis of bacteria. Using atomic simulations, we show that IgG3’s Fc tail has extensive movement in 3D space due to its extended hinge region, possibly facilitating interactions with immune cells. We replaced the hinge of IgG1 with four different IgG3-hinge segment subclasses, IgGhxx. Hinge-engineering does not diminish binding as with IgG3 but enhances opsonic function, where a 47 amino acid hinge is comparable to IgG3 in function. IgGh47 shows improved protection against S. pyogenes in a systemic infection mouse model, suggesting that IgGh47 has promise as a preclinical therapeutic candidate. Importantly, the enhanced opsonic function of IgGh47 is generalizable to diverse S. pyogenes strains from clinical isolates. We generated IgGh47 versions of anti-SARS-CoV-2 mAbs to broaden the biological applicability, and these also exhibit strongly enhanced opsonic function compared to the IgG1 subclass. The improved function of the IgGh47 subclass in two distant biological systems provides new insights into antibody function.
Linear interaction between replication and transcription shapes DNA break dynamics at recurrent DNA break Clusters
Authors: Corazzi Lorenzo , Ionasz Vivien S. , Andrejev Sergej , Wang Li-Chin , Vouzas Athanasios , Giaisi Marco , Di Muzio Giulia , Ding Boyu , Marx Anna J. M. , Henkenjohann Jonas , Allers Michael M. , Gilbert David M. , Wei Pei-Chi
Published: April 2024

Recurrent DNA break clusters (RDCs) are replication-transcription collision hotspots; many are unique to neural progenitor cells. Through high-resolution replication sequencing and a capture-ligation assay in mouse neural progenitor cells experiencing replication stress, we unravel the replication features dictating RDC location and orientation. Most RDCs occur at the replication forks traversing timing transition regions (TTRs), where sparse replication origins connect unidirectional forks. Leftward-moving forks generate telomere-connected DNA double-strand breaks (DSBs), while rightward-moving forks lead to centromere-connected DSBs. Strand-specific mapping for DNA-bound RNA reveals co-transcriptional dual-strand DNA:RNA hybrids present at a higher density in RDC than in other actively transcribed long genes. In addition, mapping RNA polymerase activity uncovers that head-to-head interactions between replication and transcription machinery result in 60% DSB contribution to the head-on compared to 40% for co-directional. Taken together we reveal TTR as a fragile class and show how the linear interaction between transcription and replication impacts genome stability.
Macrophage-fibroblast JAK/STAT dependent crosstalk promotes liver metastatic outgrowth in pancreatic cancer
Authors: Raymant Meirion , Astuti Yuliana , Alvaro-Espinosa Laura , Green Daniel , Quaranta Valeria , Bellomo Gaia , Glenn Mark , Chandran-Gorner Vatshala , Palmer Daniel H. , Halloran Christopher , Ghaneh Paula , Henderson Neil C. , Morton Jennifer P. , Valiente Manuel , Mielgo Ainhoa , Schmid Michael C.
Published: April 2024

Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease for which better therapies are urgently needed. Fibroblasts and macrophages are heterogeneous cell populations able to enhance metastasis, but the role of a macrophage-fibroblast crosstalk in regulating their pro-metastatic functions remains poorly understood. Here we deconvolve how macrophages regulate metastasis-associated fibroblast (MAF) heterogeneity in the liver. We identify three functionally distinct MAF populations, among which the generation of pro-metastatic and immunoregulatory myofibroblastic-MAFs (myMAFs) critically depends on macrophages. Mechanistically, myMAFs are induced through a STAT3-dependent mechanism driven by macrophage-derived progranulin and cancer cell-secreted leukaemia inhibitory factor (LIF). In a reciprocal manner, myMAF secreted osteopontin promotes an immunosuppressive macrophage phenotype resulting in the inhibition of cytotoxic T cell functions. Pharmacological blockade of STAT3 or myMAF-specific genetic depletion of STAT3 restores an anti-tumour immune response and reduces metastases. Our findings provide molecular insights into the complex macrophage–fibroblast interactions in tumours and reveal potential targets to inhibit PDAC liver metastasis.
Lifecycle of a predatory bacterium vampirizing its prey through the cell envelope and S-layer
Authors: Santin Yoann G. , Sogues Adrià , Bourigault Yvann , Remaut Han K. , Laloux Géraldine
Published: April 2024

Predatory bacteria feed upon other bacteria in various environments. Bdellovibrio exovorus is an obligate epibiotic predator that attaches on the prey cell surface, where it grows and proliferates. Although the mechanisms allowing feeding through the prey cell envelope are unknown, it has been proposed that the prey’s proteinaceous S-layer may act as a defensive structure against predation. Here, we use time-lapse and cryo-electron microscopy to image the lifecycle of B. exovorus feeding on Caulobacter crescentus. We show that B. exovorus proliferates by non-binary division, primarily generating three daughter cells. Moreover, the predator feeds on C. crescentus regardless of the presence of an S-layer, challenging its assumed protective role against predators. Finally, we show that apparently secure junctions are established between prey and predator outer membranes.
Evaluating the impacts of climate change and land-use change on future droughts in northeast Thailand
Authors: Khadka Dibesh , Babel Mukand S. , Tingsanchali Tawatchai , Penny Jessica , Djordjevic Slobodan , Abatan Abayomi A. , Giardino Alessio
Published: April 2024

The impacts of climate change (CC) on droughts are well documented, but the effects of land-use change (LUC) are poorly understood. This study compares the projected individual and combined impacts of these stressors on future droughts (2021–2050), with respect to baseline (1981–2010) in one of the major tributaries of the Mekong River. LUC impacts on hydrological droughts are minimal compared to CC, with the latter expected to shorten the recurrence interval of a 20-year return period event to every 14 years. Both CC and LUC have significant impacts on agricultural droughts with heightened sensitivity. ‘Once in a Decade’ agricultural droughts will be 40% (35%) longer and 88% (87%) more severe under the CC (LUC) scenario. Under both stressors, the events occurring every 20 years will be twice as frequent. Results highlight the intensification of future droughts and the urgency for actions to mitigate/adapt to climate change and manage land use. Future policy shall holistically address agricultural water management, sustainable land use management, and crop management to cope with future droughts. We recommend developing resilient agricultural practices, enhanced water resource management strategies, and incorporating drought risk into land-use planning to mitigate the compounded impacts of CC and LUC.
A national evaluation analysis and expert interview study of real-world data sources for research and healthcare decision-making
Authors: Mikl Veronika , Baltic Dejan , Czypionka Thomas , Degelsegger-Márquez Alexander , Forgó Nikolaus , Gouya-Lechner Ghazaleh , Herzog Arnold , Klimek Peter , Lumenta David Benjamin , Mraz Bernhard , Ostermann Herwig , Scharinger Robert , Stamm Tanja , Strassnig Michael , Zeitlinger Markus , Pleiner-Duxneuner Johannes
Published: April 2024

Real-world data (RWD) can provide intel (real-world evidence, RWE) for research and development, as well as policy and regulatory decision-making along the full spectrum of health care. Despite calls from global regulators for international collaborations to integrate RWE into regulatory decision-making and to bridge knowledge gaps, some challenges remain. In this work, we performed an evaluation of Austrian RWD sources using a multilateral query approach, crosschecked against previously published RWD criteria and conducted direct interviews with representative RWD source samples. This article provides an overview of 73 out of 104 RWD sources in a national legislative setting where major attempts are made to enable secondary use of RWD (e.g. law on the organisation of research, "Forschungsorganisationsgesetz"). We were able to detect omnipresent challenges associated with data silos, variable standardisation efforts and governance issues. Our findings suggest a strong need for a national health data strategy and data governance framework, which should inform researchers, as well as policy- and decision-makers, to improve RWD-based research in the healthcare sector to ultimately support actual regulatory decision-making and provide strategic information for governmental health data policies.
Prolonged elevated heart rate and 90-Day mortality in acute pancreatitis
Authors: Xie Shan , Deng Fuxing , Zhang Nuobei , Wen Zhili , Ge Chenglong
Published: April 2024

Prolonged elevated heart rate (peHR) is recognized as a risk factor for poor prognosis among critically ill patients. However, there is currently a lack of studies investigating the association between peHR and patients with acute pancreatitis. Multiparameter Intelligent Monitoring in Intensive Care IV (MIMIC-IV) database was used to identify patients with acute pancreatitis. PeHR was defined as a heart rate exceeding 100 beats per minute for at least 11 out of 12 consecutive hours. Cox regression analysis was used to assess the association between peHR and the 90-Day mortality. A total of 364 patients (48.9%) experienced a peHR episode. The 90-day mortality was 25%. PeHR is an independent risk factor for 90-day mortality (HR, 1.98; 95% CI 1.53–2.56; P < 0.001). KM survival curves exhibited a significant decrease in the survival rate at 90 days among patients who experienced a peHR episode (P < 0.001, 84.5% vs. 65.1%). We revealed a significant association of peHR with decreased survival in a large cohort of ICU patients with acute pancreatitis.
Ultrafast and efficient continuous flow organic synthesis with a modified extruder-grinder system
Authors: Hosseinchi Qareaghaj Omid , Ghaffarzadeh Mohammad , Azizi Najmedin
Published: April 2024

The study introduces a groundbreaking continuous system that combines an extruder and grinder to enable catalyst-free and solvent-free reactions under mild conditions. This temperature-controlled system facilitates the synthesis of highly functionalized chromenes, which have valuable applications in generating combinatorial libraries and complex target molecules. The newly developed mill extruder machine offers several advantages for industrial production on a large scale. It effectively reduces waste, saves energy, and enhances time efficiency. This system represents a significant advancement in the field, providing a new strategy for one-pot synthesis of various types of highly functionalized spirooxindoles and chromenes. Remarkably, these reactions can be accomplished within a short timeframe of 2–10 min, yielding impressive results of 75–98%. The results demonstrate superior performance compared to traditional reaction methods, making it an appealing tool and hotspot area of research in green chemistry.
Early automated detection system for skin cancer diagnosis using artificial intelligent techniques
Authors: Mahmoud Nourelhoda M. , Soliman Ahmed M.
Published: April 2024

Recently, skin cancer is one of the spread and dangerous cancers around the world. Early detection of skin cancer can reduce mortality. Traditional methods for skin cancer detection are painful, time-consuming, expensive, and may cause the disease to spread out. Dermoscopy is used for noninvasive diagnosis of skin cancer. Artificial Intelligence (AI) plays a vital role in diseases’ diagnosis especially in biomedical engineering field. The automated detection systems based on AI reduce the complications in the traditional methods and can improve skin cancer’s diagnosis rate. In this paper, automated early detection system for skin cancer dermoscopic images using artificial intelligent is presented. Adaptive snake (AS) and region growing (RG) algorithms are used for automated segmentation and compared with each other. The results show that AS is accurate and efficient (accuracy = 96%) more than RG algorithm (accuracy = 90%). Artificial Neural networks (ANN) and support vector machine (SVM) algorithms are used for automated classification compared with each other. The proposed system with ANN algorithm shows high accuracy (94%), precision (96%), specificity (95.83%), sensitivity (recall) (92.30%), and F1-score (0.94). The proposed system is easy to use, time consuming, enables patients to make early detection for skin cancer and has high efficiency.
Spatial variability of heavy metals concentrations in soil of auto-mechanic workshop clusters in Nsukka, Nigeria
Authors: Duru Stellamaris Chinenye , Echiegu Emmanuel Amagu , Anyadike Chinenye C. , Alaneme George Uwadiegwu , Okechukwu Michael Emeka
Published: April 2024

The indiscriminate disposal of spent engine oils and other hazardous waste at auto mechanic workshops clusters in Nsukka, Enugu State, Nigeria is an environmental concern. This study examines the concentration of heavy metals in the soil inside the workshop cluster and in the unpolluted soil outside the workshop cluster at approximately 100 m. Ten sampling points were randomly selected from within the cluster and another ten from outside the cluster. Using a hand-held Global Positioning System, the coordinates of the selected points were established and used to create a digital map. Soil samples at depths of 0–30 cm and 30–60 cm, were analyzed for Cu, Fe, Zn, Pb, As and Cd using Spectrophotometer. Moisture content determination and particle size analysis were also done on the samples. Spatial variability of heavy metals concentrations of the studied site was also mapped with ArcGIS 10.2.2 using interpolation methods. Results showed that the soil ranged from sandy loam to sandy clay loam. Cadmium and Zinc had the lowest and highest concentration, respectively, in the studied area. Comparing the concentrations of heavy metals in soils within and outside the auto mechanic cluster revealed notable differences across various depths (0–30 cm and 30–60 cm). The analysis results for soil samples within the cluster exhibited concentration levels (mg/kg) ranging from 0.716–0.751 (Cu), 2.981–3.327 (Fe), 23.464–30.113 (Zn), 1.115–1.21 (Pb), 2.6–2.912 (As), and 0.133–0.365 (Cd) demonstrating a variation pattern in the order of Zn > Fe > As > Pb > Cu > Cd. Conversely, for soil samples outside the cluster, concentration levels (mg/kg) ranged from 0.611–0.618 (Cu), 2.233–2.516 (Fe), 12.841–15.736 (Zn), 0.887–0.903 (Pb), 1.669–1.911 (As), and 0.091–0.091 (Cd). To assess the disparity in heavy metal concentration levels between samples collected within and outside the clusters, ANOVA test was performed. The test showed significant difference in heavy metal concentrations between samples within and outside the auto mechanic cluster (p < 0.05), implying auto mechanic activities significantly impact heavy metal levels within the cluster compared to outside areas. The assessment of soil pollution utilized indices including the Geo-accumulation Index (Igeo), Contamination factor (Cf), and anthropogenic metal concentration (QoC). Zinc, Cadmium, and Arsenic showed the highest contamination factors, indicating significant soil contamination likely due to anthropogenic activities. The concentrations of the metals analyzed were within WHO permissible limits while the metals concentrations were also observed to decrease as depth was increased. Using ArcGIS 10.2.2, spatial maps showing heavy metal distribution were developed, with the Kriging method proving superior. This study suggests that heavy metal levels in the soil at the area be monitored on a regular basis.
Dynamic analysis of a fuzzy Bobwhite quail population model under g-division law
Authors: Ouyang Miao , Zhang Qianhong , Cai Mingji , Zeng Zihao
Published: April 2024

This paper is concerned with a kind of Bobwhite quail population model$$\begin{aligned} x_{n+1}=A+Bx_n+\frac{x_n}{x_{n-1}x_{n-2}},\ \ n=0,1,\cdots , \end{aligned}$$xn+1=A+Bxn+xnxn-1xn-2,n=0,1,⋯,where the parameters and initial values are positive parabolic fuzzy numbers. According to g-division of fuzzy sets and based on the symmetrical parabolic fuzzy numbers, the conditional stability of this model is proved. Besides the existence, boundedness and persistence of its unique positive fuzzy solution. When some fuzzy stability conditions are satisfied, the model evolution exhibits oscillations with return to a fixed fuzzy equilibrium no matter what the initial value is. This phenomena provided a vivid counterexample to Allee effect in density-dependent populations of organisms. As a supplement, two numerical examples with data-table are interspersed to illustrate the effectiveness. Our findings have been verified precise with collected northern bobwhite data in Texas, and will help to form some efficient density estimates for wildlife populations of universal applications.
Mapping urban well-being with Quality Of Life Index (QOLI) at the fine-scale of grid data
Authors: Dobrowolska Ewa , Kopczewska Katarzyna
Published: April 2024

Accessibility of transport infrastructure, commercial amenities, recreational facilities, and green spaces is widely recognised as crucial to the well-being of urban residents. However, these features are often unevenly distributed across the geographical boundaries of a city, leading to disparities in the local quality of life. This study focuses on the city of Warsaw, Poland, and uses the aforementioned characteristics and the framework of the '15-min city' concept to construct a grid-level urban Quality of Life Index (QOLI) that facilitates comparisons between the city’s districts and local neighbourhoods. The results of our study reveal a “high-inside, low-outside” pattern of quality of life, characterised by higher standards of living in the central districts and lower standards at the city's periphery.
A self-supervised framework for cross-modal search in histopathology archives using scale harmonization
Authors: Maleki Danial , Rahnamayan Shahryar , Tizhoosh H. R.
Published: April 2024

The exponential growth of data across various medical domains has generated a substantial demand for techniques to analyze multimodal big data. This demand is particularly pronounced in fields such as computational pathology due to the diverse nature of the tissue. Cross-modal retrieval aims to identify a common latent space where different modalities, such as image-text pairs, exhibit close alignment. The primary challenge, however, often lies in the representation of tissue features. While language models can be trained relatively easily, visual models frequently struggle due to the scarcity of labeled data. To address this issue, the innovative concept of harmonization has been introduced, extending the learning scheme distillation without supervision, known as DINO. The harmonization of scale refines the DINO paradigm through a novel patching approach, overcoming the complexities posed by gigapixel whole slide images in digital pathology. Experiments conducted on diverse datasets have demonstrated that the proposed approach significantly enhances cross-modal retrieval in tissue imaging. Moreover, it exhibits vast potential for other fields that rely on gigapixel imaging.
Broadband unidirectional twin-element MIMO antenna scheme for mid-band 5G and WLAN laptops
Authors: Luadang Bancha , Janpangngern Pisit , Pookkapund Khanet , Dentri Sitthichai , Krairiksh Monai , Phongcharoenpanich Chuwong
Published: April 2024

This research proposes a broadband unidirectional twin-element multiple-input-multiple-output (MIMO) antenna scheme for mid-band 5G and WLAN applications. The twin-element antenna scheme comprises two single-element antennas, and each single-element antenna consists of a T-shaped hemispherical feeding patch, left- and right-arm radiating patches, and a conjoined triangular ground plane. The twin-element MIMO antenna scheme is integrated with a laptop model functioning as the reflector. The measured impedance bandwidth (|S11|, |S22|≤ − 6 dB) are 55.32%, covering 3.4–6.0 GHz, and the measured mutual coupling (|S12|) is less than − 15 dB. The measured gain at the center frequency (4.5 GHz) is 4.585 dBi. Besides, the measured xz- and yz-plane cross-polarization levels are below − 25 dB and − 15 dB, respectively. The half-power beamwidth (HPBW) in the xz-plane at 3.5, 4.5, and 5.5 GHz are 99°, 92.8°, and 84.2°, and the corresponding HPBW in the yz-plane are 102°, 78°, and 102°. The measured xz- and yz-plane back lobe levels are below − 15 dB across the entire operating frequency band (3.5–5.5 GHz). The radiation pattern of the twin-element MIMO antenna scheme is of unidirectionality. Furthermore, the envelope correlation coefficient and diversity gain of the twin-element antenna scheme are < 0.001 and > 9.99 dB, respectively. The proposed broadband unidirectional twin-element MIMO antenna scheme is thus operationally suitable for mid-band 5G/WLAN communication systems. Essentially, this research is the first to propose a broadband twin-element MIMO antenna scheme for mid-band 5G/WLAN applications.
Study of the changes in the microstructures and properties of grease using ball milling to simulate a bearing shear zone on grease
Authors: Ren Jia , Cai Haopeng , Zhao Gaiqing , Xu Zhuang , Wang Xiaobo
Published: April 2024

The effects of shear degradation on the microstructures and properties of grease were investigated using a planetary ball mill to simulate a bearing shear zone on grease. The microstructure, cone penetration, colloidal stability, rheological properties noise properties, water washout characteristics and low-temperature torque of lithium grease were characterized. The microstructure of the initial lithium grease is a three-dimensional network structure formed by the uniform fibers. The entanglement level is high. As the ball milling shear time increases, the network structure of lithium grease is destroyed and the fibers are sheared to become short. Eventually all of them become short fibers. The performance test of lithium grease reveal that the cone penetration increases, colloidal stability, structural strength, noise properties, water washout characteristics of lithium grease gradually decreased with the increase of ball milling shear time. Additionally, the low-temperature starting torque and running torque of the grease gradually decrease. This phenomenon occurs due to changes in the microstructure of lithium grease. The shear degradation of lithium grease was mainly divided into two stages: the rapid stage was the destruction of the thickener network structure and the fibers being shortened by shearing. The slow stage was the process in which short fibers were sheared into shorter fibers.
Factors affecting the work ability of nursing personnel with post-COVID infection
Authors: Tangsathajaroenporn Warunee , Panumasvivat Jinjuta , Wangsan Kampanat , Muangkaew Supang , Kiratipaisarl Wuttipat
Published: April 2024

Post-COVID infection have raised concerns regarding their impact on nursing personnel’s work ability. This study aimed to assess the relationship between post-COVID infection and work ability among nursing personnel. A retrospective observational study from December 2022 to January 2023 involved 609 nursing personnel with a history of COVID-19 infection at a tertiary hospital. An online questionnaire measured post-COVID infection, personal and working factors, and the Work Ability Index (WAI). Long COVID was defined as the continuation or development of new symptoms 1 month post COVID-19 infection. Of 609 personnel, 586 showed post-COVID symptoms (fatigue, cough, difficulty breathing, etc.), with 73.72% in the short COVID group and 26.28% in the long COVID group. A significant association was found between WAI and post-COVID infection (aOR: 3.64, 95% CI 1.59–8.30), with the short COVID group had a significantly higher WAI than the long COVID group (mean difference 2.25, 95% CI 1.44–3.05). The factors related to work ability in the long COVID group were chronic diseases, work limitation, low job control (P < 0.05). Post-COVID infection, especially long COVID, adversely affect nursing personnel's work ability. Enhancing job control and addressing work limitations are crucial for supporting their return to work.
Quantum error channels in high energetic photonic systems
Authors: Hiesmayr B. C. , Krzemień W. , Bała M.
Published: April 2024

In medical applications—such as positron emission tomography (PET)—511 keV photons that experience Compton scattering are studied. We present a consistent framework based on quantum error-correction channels—intensively studied in quantum computing—to fully describe the quantum information-theoretic content of high energetic photons undergoing Compton scattering, characterized by the Klein–Nishina formula in unoriented matter. In this way, we can predict the expected spatial distribution of two or more, pure or mixed, polarization entangled or separable photons. This framework allows us to characterize the accessible and inaccessible information for different parameter ranges. It also answers the question of how to describe successive multi-photon scattering. In addition our formalism provides a complete framework for dealing with single and all multi-partite errors that can occur in the propagation, providing the basis for modeling future dedicated experiments that will then have applications in medicine, such as reducing errors in PET imaging or exploring possibilities for quantum-based diagnostic indicators.
DRA-Net: Medical image segmentation based on adaptive feature extraction and region-level information fusion
Authors: Huang Zhongmiao , Wang Liejun , Xu Lianghui
Published: April 2024

Medical image segmentation is a key task in computer aided diagnosis. In recent years, convolutional neural network (CNN) has made some achievements in medical image segmentation. However, the convolution operation can only extract features in a fixed size region at a time, which leads to the loss of some key features. The recently popular Transformer has global modeling capabilities, but it does not pay enough attention to local information and cannot accurately segment the edge details of the target area. Given these issues, we proposed dynamic regional attention network (DRA-Net). Different from the above methods, it first measures the similarity of features and concentrates attention on different dynamic regions. In this way, the network can adaptively select different modeling scopes for feature extraction, reducing information loss. Then, regional feature interaction is carried out to better learn local edge details. At the same time, we also design ordered shift multilayer perceptron (MLP) blocks to enhance communication within different regions, further enhancing the network’s ability to learn local edge details. After several experiments, the results indicate that our network produces more accurate segmentation performance compared to other CNN and Transformer based networks.
Phosphodiesterase type 5 inhibitors related hearing impairment: a real world study based on the FDA adverse event reporting system
Authors: Zhang Xunyan , Xia Lu , Yang Qiang , Tang Pingxiu
Published: April 2024

Recent studies focused on exploring phosphodiesterase type 5 inhibitors (PDE5Is)-related hearing impairment. This study aimed to comprehensively explore real-world hearing impairment associated with PDE5Is based on the US Food and Drug Administration Adverse Event Reporting System (FAERS). The characteristics and correlation of PDE5Is-related hearing impairment reported in the FAERS database from the fourth quarter of 2003 to the second quarter of 2023 were analyzed using disproportionality analysis. The Standardized Medical Dictionary for Regulatory Activities (MedDRA) Queries (SMQs) were used to analyze the adverse events (AEs) of hearing impairment. A total of 1,438 reported cases of hearing impairment were associated with four PDE5Is, revealing statistically significant reporting odds ratio (ROR), proportional reporting ratio (PRR), and information component (IC) with the SMQ. The average age of all patients was more than 55 years, over 70% of AEs were reported in men. Most of the reported cases were from the United States. Reports for all the drugs indicated an increase since 2008, except for avanafil. This study showed that the disability rates of PDE5Is were 8.14–40%, the rates of initial or prolonged hospitalization were 6.21–10.24%, and the rates of required intervention were 3.31–9.45%. The pharmacovigilance study identified a potential risk of hearing impairment associated with PDE5Is, indicating the need for continuous monitoring and appropriate management.
Effect of salinity on scytonemin yield in endolithic cyanobacteria from the Atacama Desert
Authors: Casero María Cristina , Herrero María Ángeles , De la Roche Juan Pablo , Quesada Antonio , Velázquez David , Cirés Samuel
Published: April 2024

Cyanobacteria inhabiting extreme environments constitute a promising source for natural products with biotechnological applications. However, they have not been studied in-depth for this purpose due to the difficulties in their isolation and mass culturing. The Atacama Desert suffers one of the highest solar irradiances that limits the presence of life on its hyperarid core to endolithic microbial communities supported by cyanobacteria as primary producers. Some of these cyanobacteria are known to produce scytonemin, a UV-screening liposoluble pigment with varied biotechnological applications in cosmetics and other industries. In this work we carried out a strain selection based on growth performance among 8 endolithic cyanobacteria of the genera Chroococcidiopsis, Gloeocapsa and Gloeocapsopsis isolated from non-saline rocks of the Atacama Desert. Then we investigated the influence of NaCl exposure on scytonemin production yield. Results in the selected strain (Chroococcidiopsis sp. UAM571) showed that rising concentrations of NaCl lead to a growth decrease while triggering a remarkable increase in the scytonemin content, reaching maximum values at 20 g L−1 of NaCl over 50-fold higher scytonemin contents than those obtained without NaCl. Altogether, these findings point out to cyanobacteria from the Atacama Desert as potentially suitable candidates for pilot-scale cultivation with biotechnological purposes, particularly to obtain scytonemin.
Mitigating urban heat island and enhancing indoor thermal comfort using terrace garden
Authors: Visvanathan Girish , Patil Kailas , Suryawanshi Yogesh , Meshram Vishal , Jadhav Shrikant
Published: April 2024

The United Nations advocates for sustainable urban planning and design, emphasizing green infrastructure initiatives to mitigate urban heat island effects and enhance the resilience and livability of cities globally. To address urban heat challenges, a study was conducted in Chennai, India, from April to June 2023. The study focused on assessing temperature dynamics on a building's terrace by comparing a well-maintained garden area with an exposed region. Temperature and humidity sensors were deployed in both the garden and exposed areas of the terrace, as well as within rooms beneath it, to monitor hourly temperature fluctuations. The findings indicate a significant reduction in internal room temperatures in areas with rooftop gardens, ranging from 4 to 11 °C, depending on the time of year and sun's position, compared to rooms with fully exposed roof configurations. Additionally, simulation studies were performed to validate these findings, suggesting that optimizing the distribution of soil beds and plant density across the roof could yield an additional temperature reduction of 3–4 °C, resulting in an overall difference of up to 14–15 °C. The study highlights the efficacy of rooftop gardens in providing cooling effects during daylight hours and maintaining temperature parity post-sunset. Through analysis of sensor data, the research elucidates the intricate relationship between green infrastructure and thermal comfort, offering insights for energy-efficient building design and resilient urban planning. The findings underscore the potential of rooftop gardens in fostering a more comfortable, energy-efficient, and sustainable urban living environment.
Vision-based estimation of manipulation forces by deep learning of laparoscopic surgical images obtained in a porcine excised kidney experiment
Authors: Masui Kimihiko , Kume Naoto , Nakao Megumi , Magaribuchi Toshihiro , Hamada Akihiro , Kobayashi Takashi , Sawada Atsuro
Published: April 2024

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

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

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

Liquid marbles are non-wetting, particle-covered microdroplets with a core-shell structure that are used in sample transport, material synthesis, and real-time sensing. Optimizing the distribution of shell particles remains a challenge, due to a tendency for aggregation via spontaneous assembly, which often leads to multilayered structures. Here, we outline a simple method for fabricating water-filled, monolayer liquid marbles with adjustable particle coverage rates, greatly reducing particle consumption. The soft liquid marbles are enclosed by a small quantity of modified polystyrene microspheres and display good atmospheric stability. The rolling behavior of flexible liquid marbles with wide coverage rates is then characterized. Contrary to common perception, the marbles with transparent openings exhibit high maneuverability on hydrophilic surfaces, and also excel in fusion, reaction and surface cleaning, with an elongated operational duration and a wide visualization range. The study provides new insights into the implementation of liquid marble-based miniaturized platforms.
The interaction between manufacturer encroachment and gray market
Authors: Xu Fengmei , Yang Feng , Shan Feifei , Chen Ting
Published: April 2024

With the rapid development of retail platforms, many manufacturers use retail platforms to encroach into the retail market (i.e., a type manufacturer encroachment) and gray market is increasingly prevalent in various industries. This paper considers a manufacturer who directly sells product 1 in the domestic market and sells product 2 through an incumbent retailer in the overseas market and a gray marketer can divert product 1 across markets without authorized (we call it gray market). In this paper, we examine the interaction between manufacturer encroachment and gray market. We find that when the domestic price of product 1 is sufficiently low, the gray marketer can successfully enter the overseas market without and with encroachment. Second, regardless of whether there is a gray market threat, the manufacturer has an incentive to encroach through retail platform when the commission rate is low. Moreover, the manufacturer’s incentive to encroach varies with the domestic price of product 1 and gray market threat. Finally, manufacturer encroachment can reduce the scale of the gray market and even eliminate the gray market under certain conditions. The gray marketer always suffers from manufacturer encroachment while the retailer can benefit from manufacturer encroachment.
Computer Patient-Specific 3D Modeling and Custom-Made Guides for Revision ACL Surgery
Authors: Del Prete Armando , Franco Piero , Innocenti Matteo , Matassi Fabrizio , Leggieri Filippo , Sagliocco Rosario Jr , Civinini Roberto
Published: April 2024

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

We report a visible-light-driven metal-free and photocatalyst-free protocol for the synthesis of phenanthrenes through the intramolecular cyclization of chalcones. The transformation proceeds through light irradiation and base- and oxygen-based promotion, and enables the generation of a series of phenanthrenes. The further functionalization of an as-synthesized phenanthrene to afford a fluorescent molecule was explored.