bluuebunny/crossref_metadata_2025 huggingface dataset:
Establishment and application of a rapid visual diagnostic method for Streptococcus agalactiae based on recombinase polymerase amplification and lateral flow strips
Authors: Ji Tuo , Cai Ye , Gao Yuzhi , Wang Gang , Miao Yongchang , Gao Xuzhu
Published: May 2024

This study aims to establish a rapid diagnostic method for Streptococcus agalactiae (GBS) based on recombinase polymerase amplification (RPA) and lateral flow strips (LFS). The best primer pairs designed by SIP gene were screened according to the basic RPA reaction, then the probe was designed. The reaction condition was optimized based on the color development of the LFS detection line. To ascertain the reaction specificity, 10 common clinical pathogens and 10 clinical specimens of GBS were tested. Furthermore, the reaction sensitivity was assessed by utilizing a tenfold gradient dilution of GBS genomic DNA as templates. RPA–LFS method was compared to the qPCR assay and biochemical culture method for the Kappa consistency test. The RPA–LFS technique was able to complete the amplification process within 30 min and the results were observed on lateral flow strips. The method is highly sensitive, with a minimum detection limit of 1.31 ng for GBS. The RPA–LFS method showed consistent accuracy of results compared to qPCR and the culture–biochemical method. The establishment of this method is conducive to the development of on-site immediate detection, which can provide information for the timely development of a reasonable antimicrobial treatment plan, and has a greater potential for clinical application.
Association between intensity of physical activity and cognitive function in hypertensive patients: a case–control study
Authors: Lv Shunxin , Jiao Huachen , Zhong Xia , Qu Ying , Zhang Mengdi , Wang Rui
Published: May 2024

Previous studies have shown that a higher intensity of physical activity (PA) is associated with a lower risk of cognitive impairment (CI), whereas hypertension is associated with higher CI. However, there are few studies on the association between PA intensity and cognitive function in hypertensive patients. This study investigated the association between PA intensity and cognitive function in hypertensive patients. A total of 2035 hypertensive patients were included in this study, including 407 hypertensive patients with CI and 1628 hypertensive patients with normal cognitive function matched 1:4 by age and sex. The International Physical Activity Questionnaire-Long Form and the Mini-mental State Examination were used to evaluate PA intensity, total metabolic equivalents, and cognitive function in patients with hypertension. Multivariate logistic regression was used to analyze the correlation between PA intensity and CI in hypertensive patients. The Spearman correlation coefficient was used to analyze the correlation between PA intensity and the total score of each component of the MMSE and the correlation between PA total metabolic equivalents and cardiac structure in hypertensive patients. After adjusting for all confounding factors, PA intensity was negatively associated with CI in hypertensive patients (OR = 0.608, 95% CI: 0.447–0.776, P < 0.001), and this association was also observed in hypertensive patients with education level of primary school and below and junior high school and above (OR = 0.732, 95% CI: 0.539–0.995, P = 0.047; OR = 0.412, 95% CI: 0.272–0.626, P < 0.001). The intensity of PA in hypertensive patients was positively correlated with orientation (r = 0.125, P < 0.001), memory (r = 0.052, P = 0.020), attention and numeracy (r = 0.151, P < 0.001), recall ability (r = 0.110, P < 0.001), and language ability (r = 0.144, P < 0.001). PA total metabolic equivalents in hypertensive patients were negatively correlated with RVEDD and LAD (r = − 0.048, P = 0.030; r = − 0.051, P = 0.020) and uncorrelated with LVEDD (r = 0.026, P = 0.233). Higher PA intensity reduced the incidence of CI in hypertensive patients. Therefore, hypertensive patients were advised to moderate their PA according to their circumstances.
Structural investigation of Trypanosoma cruzi Akt-like kinase as drug target against Chagas disease
Authors: Stadler Karina A. , Ortiz-Joya Lesly J. , Singh Sahrawat Amit , Buhlheller Christoph , Gruber Karl , Pavkov-Keller Tea , O’Hagan Treasa B. , Guarné Alba , Pulido Sergio , Marín-Villa Marcel , Zangger Klaus , Gubensäk Nina
Published: May 2024

According to the World Health Organization, Chagas disease (CD) is the most prevalent poverty-promoting neglected tropical disease. Alarmingly, climate change is accelerating the geographical spreading of CD causative parasite, Trypanosoma cruzi, which additionally increases infection rates. Still, CD treatment remains challenging due to a lack of safe and efficient drugs. In this work, we analyze the viability of T. cruzi Akt-like kinase (TcAkt) as drug target against CD including primary structural and functional information about a parasitic Akt protein. Nuclear Magnetic Resonance derived information in combination with Molecular Dynamics simulations offer detailed insights into structural properties of the pleckstrin homology (PH) domain of TcAkt and its binding to phosphatidylinositol phosphate ligands (PIP). Experimental data combined with Alpha Fold proposes a model for the mechanism of action of TcAkt involving a PIP-induced disruption of the intramolecular interface between the kinase and the PH domain resulting in an open conformation enabling TcAkt kinase activity. Further docking experiments reveal that TcAkt is recognized by human inhibitors PIT-1 and capivasertib, and TcAkt inhibition by UBMC-4 and UBMC-6 is achieved via binding to TcAkt kinase domain. Our in-depth structural analysis of TcAkt reveals potential sites for drug development against CD, located at activity essential regions.
Multi-level optimal energy management strategy for a grid tied microgrid considering uncertainty in weather conditions and load
Authors: Keshta H. E. , Hassaballah E. G. , Ali A. A. , Abdel-Latif K. M.
Published: May 2024

Microgrids require efficient energy management systems to optimize the operation of microgrid sources and achieve economic efficiency. Bi-level energy management model is proposed in this paper to minimize the operational cost of a grid-tied microgrid under load variations and uncertainties in renewable sources while satisfying the various technical constraints. The first level is day ahead scheduling of generation units based on day ahead forecasting of renewable energy sources and load demand. In this paper, a recent meta-heuristic algorithm called Coronavirus Herd Immunity Optimizer (CHIO) is used to solve the problem of day-ahead scheduling of batteries, which is a complex constrained non-linear optimization problem, while the Lagrange multiplier method is used to determine the set-point of the Diesel Generator (DG). The second level of the proposed EMS is rescheduling and updating the set-points of sources in real-time according to the actual solar irradiance, wind speed, load, and grid tariff. In this paper, a novel real-time strategy is proposed to keep the economic operation during real-time under uncertainties. The obtained results show that the CHIO-based bi-level EMS demonstrates an optimal economic operation for a grid-connected microgrid in real-time when there are uncertainties in weather, utility tariffs, and load forecasts.
Dual-channel fluorescent sensors based on chitosan-coated Mn-doped ZnS micromaterials to detect ampicillin
Authors: Nguyen Son Hai , Nguyen Van-Nhat , Tran Mai Thi
Published: May 2024

The global threat of antibiotic resistance has increased the importance of the detection of antibiotics. Conventional methods to detect antibiotics are time-consuming and require expensive specialized equipment. Here, we present a simple and rapid biosensor for detecting ampicillin, a commonly used antibiotic. Our method is based on the fluorescent properties of chitosan-coated Mn-doped ZnS micromaterials combined with the β-lactamase enzyme. The biosensors exhibited the highest sensitivity in a linear working range of 13.1–72.2 pM with a limit of detection of 8.24 pM in deionized water. In addition, due to the biological specificity of β-lactamase, the proposed sensors have demonstrated high selectivity over penicillin, tetracycline, and glucose through the enhancing and quenching effects at wavelengths of 510 nm and 614 nm, respectively. These proposed sensors also showed promising results when tested in various matrices, including tap water, bottled water, and milk. Our work reports for the first time the cost-effective (Mn:ZnS)Chitosan micromaterial was used for ampicillin detection. The results will facilitate the monitoring of antibiotics in clinical and environmental contexts.
An advanced fast method for the evaluation of multiple immunolabelling using gold nanoparticles based on low-energy STEM
Authors: Kitzberger František , Yang Shun-Min , Týč Jiří , Bílý Tomáš , Nebesářová Jana
Published: May 2024

We present a powerful method for the simultaneous detection of Au nanoparticles located on both sides of ultrathin sections. The method employs a high-resolution scanning electron microscope (HRSEM) operating in scanning transmission electron microscopy (STEM) mode in combination with the detection of backscattered electrons (BSE). The images are recorded simultaneously during STEM and BSE imaging at the precisely selected accelerating voltage. Under proper imaging conditions, the positions of Au nanoparticles on the top or bottom sides can be clearly differentiated, hence showing this method to be suitable for multiple immunolabelling using Au nanoparticles (NPs) as markers. The difference between the upper and lower Au NPs is so large that it is possible to apply common software tools (such as ImageJ) to enable their automatic differentiation. The effects of the section thickness, detector settings and accelerating voltage on the resulting image are shown. Our experimental results correspond to the results modelled in silico by Monte Carlo (MC) simulations.
Cognitive impairment and hippocampal neuronal damage in β-thalassaemia mice
Authors: Pholngam Nuttanan , Jamrus Parinda , Viwatpinyo Kittikun , Kiatpakdee Benjaporn , Vadolas Jim , Chaichompoo Pornthip , Ngampramuan Sukonthar , Svasti Saovaros
Published: May 2024

β-Thalassaemia is one of the most common genetic diseases worldwide. During the past few decades, life expectancy of patients has increased significantly owing to advance in medical treatments. Cognitive impairment, once has been neglected, has gradually become more documented. Cognitive impairment in β-thalassaemia patients is associated with natural history of the disease and socioeconomic factors. Herein, to determined effect of β-thalassaemia intrinsic factors, 22-month-old β-thalassaemia mouse was used as a model to assess cognitive impairment and to investigate any aberrant brain pathology in β-thalassaemia. Open field test showed that β-thalassaemia mice had decreased motor function. However, no difference of neuronal degeneration in primary motor cortex, layer 2/3 area was found. Interestingly, impaired learning and memory function accessed by a Morris water maze test was observed and correlated with a reduced number of living pyramidal neurons in hippocampus at the CA3 region in β-thalassaemia mice. Cognitive impairment in β-thalassaemia mice was significantly correlated with several intrinsic β-thalassaemic factors including iron overload, anaemia, damaged red blood cells (RBCs), phosphatidylserine (PS)-exposed RBC large extracellular vesicles (EVs) and PS-exposed medium EVs. This highlights the importance of blood transfusion and iron chelation in β-thalassaemia patients. In addition, to improve patients’ quality of life, assessment of cognitive functions should become part of routine follow-up.
De-embedding method for a sensing area characterization of planar microstrip sensors without evaluating error networks
Authors: Hasar Ugur C. , Ozturk Hamdullah , Korkmaz Huseyin , Nayyeri Vahid , Ramahi Omar M.
Published: May 2024

A de-embedding method for determining all scattering (S-) parameters (e.g., characterization) of a sensing area of planar microstrip sensors (two-port network or line) is proposed using measurements of S-parameters with no calibration. The method requires only (partially known) non-reflecting line and reflecting line standards to accomplish such a characterization. It utilizes uncalibrated S-parameter measurements of a reflecting line, direct and reversed configurations of a non-reflecting line, and direct and reversed configurations of the sensing area. As different from previous similar studies, it performs such a characterization without any sign ambiguity. The method is first validated by extracting the S-parameters of a bianisotropic metamaterial slab, as for a two-port network (line), constructed by split-ring-resonators (SRRs) from waveguide measurements. Then, it is applied for determining the S-parameters of a sensing area of a microstrip sensor involving double SRRs next to a microstrip line. The root-mean-square-error (RMSE) analysis was utilized to analyze the accuracy of our method in comparison with other techniques in the literature. It has been observed from such an analysis that our proposed de-embedding technique has the lowest RMSE values for the extracted S-parameters of the sensing area of the designed sensor in comparison with those of the compared other de-embedding techniques in the literature, and have similar RMSE values in reference to those of the thru-reflect-line calibration technique. For example, while RMSE values of real and imaginary parts of the forward reflection S-parameter of this sensing area are, respectively, around 0.0271 and 0.0279 for our de-embedding method, those of one of the compared de-embedding techniques approach as high as 0.0318 and 0.0324.
Isolation of nucleic acids using liquid–liquid phase separation of pH-sensitive elastin-like polypeptides
Authors: Díez Pérez Telmo , Tafoya Ashley N. , Peabody David S. , Lakin Matthew R. , Hurwitz Ivy , Carroll Nick J. , López Gabriel P.
Published: May 2024

Extraction of nucleic acids (NAs) is critical for many methods in molecular biology and bioanalytical chemistry. NA extraction has been extensively studied and optimized for a wide range of applications and its importance to society has significantly increased. The COVID-19 pandemic highlighted the importance of early and efficient NA testing, for which NA extraction is a critical analytical step prior to the detection by methods like polymerase chain reaction. This study explores simple, new approaches to extraction using engineered smart nanomaterials, namely NA-binding, intrinsically disordered proteins (IDPs), that undergo triggered liquid–liquid phase separation (LLPS). Two types of NA-binding IDPs are studied, both based on genetically engineered elastin-like polypeptides (ELPs), model IDPs that exhibit a lower critical solution temperature in water and can be designed to exhibit LLPS at desired temperatures in a variety of biological solutions. We show that ELP fusion proteins with natural NA-binding domains can be used to extract DNA and RNA from physiologically relevant solutions. We further show that LLPS of pH responsive ELPs that incorporate histidine in their sequences can be used for both binding, extraction and release of NAs from biological solutions, and can be used to detect SARS-CoV-2 RNA in samples from COVID-positive patients.
Analysis of the retraining strategies for multi-label text message classification in call/contact center systems
Authors: Poczeta Katarzyna , Płaza Mirosław , Zawadzki Michał , Michno Tomasz , Krechowicz Maria
Published: May 2024

Today, in many areas of technology, we can come across applications of various artificial intelligence methods. They usually involve models trained on some specific pool of learning data. Sometimes, however, the data analyzed by these solutions can change its nature over time. This usually results in a decrease in classification efficiency. In such a case, the use of techniques to retrain the originally trained reference models should be considered. One of the industries where the nature of data changes quite dynamically over time is the broadly defined call/contact center systems. An example of a module that is often found in this type of system and that, due to frequently changing marketing campaigns, requires the use of learning techniques is the automatic classification of text data. The paper describes the process of retraining the original reference models used in a multi-label text message classification method dedicated directly to call/contact center systems applications. In order to carry out the retraining process, Polish-language data from the actual archives of a large commercial contact center system and English-language data extracted from a publicly available database were used. The study was conducted for models based on artificial neural networks and bidirectional encoder representations from transformer type models. In addition, two different retraining strategies were studied, the results of which were compared with data obtained from the operation of reference models. As a result of the research work, an improvement of up to 5% in classification efficiency, as described by the metric Emotica was obtained, which means that proper integration of the retraining process brings tangible benefits to the solution tested in the article. Thus, it can also benefit the solutions used in business.
Comparing the quantum witness, the entropic Leggett–Garg inequality and the NCGD
Authors: Tan Xiangguan , Zhang Yuxia , Qiu Tianhui
Published: May 2024

In this paper, we investigate the violation of the quantum witness, the entropic Leggett–Garg inequality (LGI) and the no-coherence-generating-and-detecting (NCGD) dynamics, under projective and coarsening measurements. We consider a qubit in the three scenarios: coherent dynamics, in the presence of dissipation, and in the presence of dephasing. For the pure qubit, we find that in the case of the projective measurement, the non-violation conditions of the quantum witness and the NCGD are the same; while the non-violation conditions of the entropic LGI and the quantum witness do not contain each other, i.e., a suitable conjunction of the quantum witness and the entropic LGI may be better for testing macrorealism. Also, for the pure qubit with coarsening measurement similar results can be obtained. For the dissipative qubit with projective measurement, the quantum witness and the NCGD can be both violated for a wider parameter regime than the entropic LGI. For the dissipative qubit with coarsening measurement, the violation of the NCGD is the most robust compared to the quantum witness and the entropic LGI. For the dephasing qubit with projective and coarsening measurements, the relationship among the quantum witness, the entropic LGI and the NCGD is similar to that of the pure qubit. In addition, we find that for pure, dissipative and dephasing qubits, the robustness of the coarsening measurement in final resolution is more vulnerable than that of the coarsening measurement in reference for the entropic LGI.
A study of extractive summarization of long documents incorporating local topic and hierarchical information
Authors: Wang Ting , Yang Chuan , Zou Maoyang , Liang Jiaying , Xiang Dong , Yang Wenjie , Wang Hongyang , Li Jia
Published: May 2024

In recent years, the transformer-based language models have achieved remarkable success in the field of extractive text summarization. However, there are still some limitations in this kind of research. First, the transformer language model usually regards the text as a linear sequence, ignoring the inherent hierarchical structure information of the text. Second, for long text data, traditional extractive models often focus on global topic information, which poses challenges in how they capturing and integrating local contextual information within topic segments. To address these issues, we propose a long text extractive summarization model that employs a local topic information extraction module and a text hierarchical extraction module to capture the local topic information and document's hierarchical structure information of the original text. Our approach enhances the ability to determine whether a sentence belongs to the summary. In this experiment, ROUGE score is used as the experimental evaluation index, and evaluates the model on three large public datasets. Through experimental validation, the model demonstrates superior performance in terms of ROUGE-1, ROUGE-2, and ROUGE-L scores compared to current mainstream summarization models, affirming the effectiveness of incorporating local topic information and document hierarchical structure into the model.
Artificial intelligence for volumetric measurement of cerebral white matter hyperintensities on thick-slice fluid-attenuated inversion recovery (FLAIR) magnetic resonance images from multiple centers
Authors: Kuwabara Masashi , Ikawa Fusao , Nakazawa Shinji , Koshino Saori , Ishii Daizo , Kondo Hiroshi , Hara Takeshi , Maeda Yuyo , Sato Ryo , Kaneko Taiki , Maeyama Shiyuki , Shimahara Yuki , Horie Nobutaka
Published: May 2024

We aimed to develop a new artificial intelligence software that can automatically extract and measure the volume of white matter hyperintensities (WMHs) in head magnetic resonance imaging (MRI) using only thick-slice fluid-attenuated inversion recovery (FLAIR) sequences from multiple centers. We enrolled 1092 participants in Japan, comprising the thick-slice Private Dataset. Based on 207 randomly selected participants, neuroradiologists annotated WMHs using predefined guidelines. The annotated images of participants were divided into training (n = 138) and test (n = 69) datasets. The WMH segmentation model comprised a U-Net ensemble and was trained using the Private Dataset. Two other models were trained for validation using either both thin- and thick-slice MRI datasets or the thin-slice dataset alone. The voxel-wise Dice similarity coefficient (DSC) was used as the evaluation metric. The model trained using only thick-slice MRI showed a DSC of 0.820 for the test dataset, which is comparable to the accuracy of human readers. The model trained with the additional thin-slice dataset showed only a slightly improved DSC of 0.822. This automatic WMH segmentation model comprising a U-Net ensemble trained on a thick-slice FLAIR MRI dataset is a promising new method. Despite some limitations, this model may be applicable in clinical practice.
Addressing practical challenges of LiB cells in their pack applications
Authors: Tan Cher Ming , Yang Yan , Kumar K. Jithendra Mani , Mishra Debesh Devadutta , Liu Tsung-Yu
Published: May 2024

In a battery pack, several lithium-ion batteries (LiBs) are connected in series and parallel so that sufficient voltage, current and power can be provided for applications. To ensure safe operation, when one of the LiB cells in a pack has its SoH below 80%, the entire pack will have to be discarded. Thus, ensuring all the LiB cells degrade similarly in a pack is crucial to maximize the potential of all the cells in a pack. There are several methods to perform screening on the LiB cells for such purpose, but there exist many practical challenges for estimating and predicting the degradation rate of the cells before they are chosen to be put in a pack which will be described in this work. This work provides solutions to some of these challenges and shows through experiments that one can screen the weak cells from production batch with just the first discharge cycle, and one can also predict the statistical distribution of the degradation rates of LiB cells in a production batch. On-line in-situ determination of the SoH of each cell connected in a pack is also made possible with a solution presented in this work, and this method is verified over many different types of LiB from various manufacturers.
Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer’s disease from cognitively unimpaired amyloid-positive individuals
Authors: Kim Hak Hyeon , Kwon Min Jeong , Jo Sungman , Park Ji Eun , Kim Ji Won , Kim Jae Hyoung , Kim Sang Eun , Kim Ki Woong , Han Ji Won
Published: May 2024

Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer’s disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.
Research on roller monitoring technology based on distributed fiber optic sensing system
Authors: Xie Miao , Li Bo , Ma Suning , Lu Jinnan , Hu Guilin , Meng Qingshuang , Luo Jiaxing
Published: May 2024

As one of the key components of the belt conveyor, the roller bears the task of supporting and rolling the conveyor belt, and monitoring its condition is very important. The traditional monitoring of the conveyor roller group adopts worker inspection, which has strong subjectivity. Monitoring using sensors necessitates the use of numerous sensors, which can pose wiring challenges. The use of inspection robots for monitoring results can be discontinuous, and their performance may be limited. This study proposes a fault diagnosis method for rollers based on a distributed fiber optic sensing system. By improving the traditional Isolation Forest (IForest), a framework called Incremental Majority Voting Isolation Forest (IMV-IForest) is proposed. By analyzing the optical signal, we extracted the variation patterns of roller faults over time and space, and analyzed the abnormal score distribution between fault data and normal data. Using the dataset collected on-site, we compared and analyzed IMV-IForest with the traditional IForest and the Extended Isolation Forest (E-iForest). The results indicate that the variation of the fault of the faulty roller with time and space can be used for early prediction of roller faults; determine an anomaly score threshold of 0.6; improved IForest have faster computation time and higher accuracy. Finally, to verify the effectiveness of the proposed scheme, a 3-month experiment was conducted on a 600 m long belt conveyor in a certain mine, and on-site monitoring results were obtained. By comparing with manual detection results, it was shown that the proposed method has high recognition rate for faulty idlers, with an accuracy rate of 97.92%, and can effectively diagnose faulty idlers.
Stress analysis under centrifugal load of the multiple corrugated diaphragm coupling based on rotating shell thin film model
Authors: Cao Angang , Sun Shiru
Published: May 2024

Centrifugal force is one of the factors that cannot be ignored in high-speed shaft systems. The multiple corrugated diaphragm (MCD) Coupling is suitable for high-power and high-speed situations; hence, it is crucial to investigate the stress and deformation of the wave disc under centrifugal load. This paper first uses the rotating shell thin film model to derive the circumferential stress and deformation displacement of the MCD under centrifugal load. Then, the finite element method is used to verify the results obtained from the analytical solution. The results show the feasibility of using the rotating shell thin film model for centrifugal load analysis of the MCD, providing a new approach for the theoretical analysis of the MCD.
Exosomal miR-493 suppresses MAD2L1 and induces chemoresistance to intraperitoneal paclitaxel therapy in gastric cancer patients with peritoneal metastasis
Authors: Makinoya Masahiro , Miyatani Kozo , Matsumi Yoshiaki , Sakano Yu , Shimizu Shota , Shishido Yuji , Hanaki Takehiko , Kihara Kyoichi , Matsunaga Tomoyuki , Yamamoto Manabu , Tokuyasu Naruo , Takano Shuichi , Sakamoto Teruhisa , Hasegawa Toshimichi , Saito Hiroaki , Nakayama Yuji , Osaki Mitsuhiko , Okada Futoshi , Fujiwara Yoshiyuki
Published: May 2024

Intraperitoneal (IP) chemotherapy with paclitaxel (PTX) for gastric cancer (GC) with peritoneal metastasis (PM) is considered a promising treatment approach, however, there are no useful biomarkers to predict the efficacy of IP therapy. We examined the association between intra-peritoneal exosomes, particularly exosomal micro-RNAs (exo-miRNAs), and IP-chemo sensitivity. MKN45 cells that were cultured with intra-peritoneal exosomes from patients who did not respond to IP therapy with PTX (IPnon-respond group) exhibited resistance to PTX compared with exosomes from responding patients (IPrespond group) (p = 0.002). A comprehensive search for exo-miRNAs indicated that miR-493 was significantly up-regulated in exosomes from the IPnon-respond group compared with those collected from the IPrespond group. The expression of miR-493 in PTX-resistant MKN45 cells (MKN45PTX-res) was higher compared with that in MKN45. In addition, MKN45PTX-res cells exhibited lower MAD2L1 gene and protein expression compared with MKN45. Finally, miR-493 enhancement by transfection of miR-493 mimics significantly down-regulated MAD2L1 expression in MKN45 cells and reduced PTX sensitivity. Our results suggest that intra-peritoneal exo-miR-493 is involved in chemoresistance to PTX by downregulating MAD2L1 in GC with PM. Exo-miR-493 may be a biomarker for chemoresistance and prognosis of GC patients with PM and may also be a promising therapeutic target.
Safe and effective hybrid endoscopic submucosal dissection with ALL IN ONE snare in porcine gastric model (with video)
Authors: Yang Lang , Ma Xian-zong , Su Hui , Zhang Jie , Sheng Jian-qiu , Jin Peng
Published: May 2024

This study aimed to evaluate the safety and efficiency of hybrid endoscopic submucosal dissection (H-ESD) using a newly developed ALL IN ONE (AIO) snare. This was a matched control study in a porcine model. Five paired simulated stomach lesions 2–2.5 cm in size were removed by H-ESD using an AIO snare or conventional ESD (C-ESD) using an endoscopic knife. The outcomes of the two procedures were compared, including en-bloc resection rates, procedure times, intraprocedural bleeding volumes, muscular injuries, perforations, thicknesses of the submucosal layer in resected specimens, and stomach defects. All simulated lesions were resected en-bloc. Specimens resected by H-ESD and C-ESD were similar in size (7.68 ± 2.92 vs. 8.42 ± 2.42 cm2; P = 0.676). H-ESD required a significantly shorter procedure time (13.39 ± 3.78 vs. 25.99 ± 4.52 min; P = 0.031) and submucosal dissection time (3.99 ± 1.73 vs. 13.1 ± 4.58 min; P = 0.003) versus C-ESD; H-ESD also yielded a faster dissection speed (241.37 ± 156.84 vs. 68.56 ± 28.53 mm2/min; P = 0.042) and caused fewer intraprocedural bleeding events (0.40 ± 0.55 vs. 3.40 ± 1.95 times/per lesion; P = 0.016) than C-ESD. The thicknesses of the submucosal layer of the resected specimen (1190.98 ± 134.07 vs. 1055.90 ± 151.76 μm; P = 0.174) and the residual submucosal layer of the stomach defect (1607.94 ± 1026.74 vs. 985.98 ± 445.58 μm; P = 0.249) were similar with both procedures. The AIO snare is a safe and effective device for H-ESD and improves the treatment outcomes of gastric lesions by shortening the procedure time.
Robust language-based mental health assessments in time and space through social media
Authors: Mangalik Siddharth , Eichstaedt Johannes C. , Giorgi Salvatore , Mun Jihu , Ahmed Farhan , Gill Gilvir , V. Ganesan Adithya , Subrahmanya Shashanka , Soni Nikita , Clouston Sean A. P. , Schwartz H. Andrew
Published: May 2024

In the most comprehensive population surveys, mental health is only broadly captured through questionnaires asking about “mentally unhealthy days” or feelings of “sadness.” Further, population mental health estimates are predominantly consolidated to yearly estimates at the state level, which is considerably coarser than the best estimates of physical health. Through the large-scale analysis of social media, robust estimation of population mental health is feasible at finer resolutions. In this study, we created a pipeline that used ~1 billion Tweets from 2 million geo-located users to estimate mental health levels and changes for depression and anxiety, the two leading mental health conditions. Language-based mental health assessments (LBMHAs) had substantially higher levels of reliability across space and time than available survey measures. This work presents reliable assessments of depression and anxiety down to the county-weeks level. Where surveys were available, we found moderate to strong associations between the LBMHAs and survey scores for multiple levels of granularity, from the national level down to weekly county measurements (fixed effects β = 0.34 to 1.82; p < 0.001). LBMHAs demonstrated temporal validity, showing clear absolute increases after a list of major societal events (+23% absolute change for depression assessments). LBMHAs showed improved external validity, evidenced by stronger correlations with measures of health and socioeconomic status than population surveys. This study shows that the careful aggregation of social media data yields spatiotemporal estimates of population mental health that exceed the granularity achievable by existing population surveys, and does so with generally greater reliability and validity.
Experimental investigation of geometric quantum speed limits in an open quantum system
Authors: Pires Diego Paiva , deAzevedo Eduardo R. , Soares-Pinto Diogo O. , Brito Frederico , Filgueiras Jefferson G.
Published: May 2024

The quantum speed limit (QSL) is a fundamental lower bound on the evolution time for quantum systems, and its tightness has been observed to be dependent on the properties of the physical process. However, experimental studies exploring the QSL in open quantum systems are still missing. Here, we studied geometric quantum speed limits of a qubit subject to decoherence in an ensemble of chloroform molecules in a Nuclear Magnetic Resonance experiment. We controlled the system-reservoir interaction and the spin relaxation rates by adding a paramagnetic salt, allowing the observation of both Markovian and non-Markovian open system dynamics for the qubit. We used two distinguishability measures of quantum states to assess the speed of the qubit evolution: the quantum Fisher information (QFI) and Wigner-Yanase skew information (WY). For non-Markovianity and low salt concentrations, we found crossovers between QSLs related to those metrics. The WY metric sets the tighter QSL for high concentrations and Markovian dynamics. We also show that QSLs are sensitive even to small fluctuations in spin magnetization.
Pre-failure operational anomalies of the Kakhovka Dam revealed by satellite data
Authors: Yang Qing , Shen Xinyi , He Kang , Zhang Qingyuan , Helfrich Sean , Straka William , Kellndorfer Josef M. , Anagnostou Emmanouil N.
Published: May 2024

On June 6, 2023, the Kakhovka Dam in Ukraine experienced a catastrophic breach that led to the loss of life and substantial economic values. Prior to the breach, the supporting structures downstream of the spillway had shown signs of being compromised. Here, we use multi-source satellite data, meteorological reanalysis, and dam design criteria to document the dam’s pre-failure condition. We find that anomalous operation of the Kakhovka Dam began in November 2022, following the destruction of a bridge segment, which led to persistent overtopping from late April 2023 up to the breach, contributing to the erosion of the spillway foundation. Moreover, our findings also highlight safety and risk-reduction measures pivotal in avoiding such scenarios. To help prevent future disasters, we advocate for greater transparency in the design parameters of key water structures to enable risk management, and conclude that remote sensing technology can help ensuring water infrastructure safety.
Application of a ferrocene-chelating heteroscorpionate ligand in nickel mediated radical polymerization
Authors: Li Shuangshuang , Davis Ashton R. , Roshandel Hootan , Adhami Nima , Shen Yi , Co Nathalie H. , Morag Leo A. , Etemad Hafez , Liu Yuan , Diaconescu Paula L.
Published: May 2024

A nickel bromide complex supported by a non-innocent ferrocene-chelating heteroscorpionate ligand, [(fc(PPh2)(BH(3,5-Me2pz)2)NiBr)] ((fcP,B)NiBr, fc = 1,1′-ferrocenediyl, pz = pyrazole), was synthesized and characterized.
A superior zinc-air battery performance achieved by CoO/Fe3O4 heterostructured nanosheets
Authors: Long Xue , Tang Wei , Li Chunsheng , Ma Zhiyong , Liu Kai , Li Yi , Chen Yazhou , Sun Yan , Yang Zehui , Luo Fang
Published: May 2024

CoO/Fe3O4 nanosheets exhibit a superior rechargeable zinc-air battery (ZAB) performance of 276 mW cm−2 and stability over 600 h. The all-solid-state ZAB also affords a high power density of 107 mW cm−2.
Rapid growth of SiC single crystals using CVD-SiC block sources via a sublimation method
Authors: Jeong Seong-Min , Kim Yong-Hyeon , Sun Ju-Hyeong , Park Jae-Hyeon , Shin Yun-Ji , Bae Si-Young , Kim Chang-Min , Lee Won-Jae
Published: May 2024

Via the PVT method adopting crushed CVD-SiC block sources, single crystalline SiC was grown with a high growth rate of 1.46 mm h−1 and good crystal quality.
Rapidly convergent quantum Monte Carlo using a Chebyshev projector
Authors: Zhao Zijun , Filip Maria-Andreea , Thom Alex J. W.
Published: May 2024

We present a series of algorithmic changes that can be used to accelerate the MR-CCMC algorithm in particular and QMC algorithms in general.
Fast and accurate nonadiabatic molecular dynamics enabled through variational interpolation of correlated electron wavefunctions
Authors: Atalar Kemal , Rath Yannic , Crespo-Otero Rachel , Booth George H.
Published: May 2024

Efficient multi-state interpolation of many-body wavefunctions enables rigorous nonadiabatic molecular dynamics with analytical forces and nonadiabatic coupling vectors.
Dietary supplementation with non-digestible isomaltooligosaccharide and Lactiplantibacillus plantarum ZDY2013 ameliorates DSS-induced colitis via modulating intestinal barrier integrity and the gut microbiota
Authors: Zhang Zhihong , Hu Yingsheng , Zhang Na , Li Jinmei , Lu Jinlin , Wei Hua
Published: May 2024

Non-digestible isomaltooligosaccharide drives Lactiplantibacillus plantarum ZDY2013 to colonize the gut and alleviate DSS-induced colitis.
Liquid metal–polymer nano-microconjugations as an injectable and photo-activatable drug carrier
Authors: Hirose Tomoka , Rajan Robin , Miyako Eijiro , Matsumura Kazuaki
Published: May 2024

Nanoparticles of photoresponsive liquid–liquid phase-separation polymers complexed with liquid metals can concentrate drugs upon photoirradiation, opening up new DDS horizons.
Novel disulfide-containing diols: synthesis and application in self-healing fluorescent polyurethane elastomers
Authors: Luo Jialu , Liu Jin , Li Zhen , Wei Xiaoyan , Wang Shiwu , Tang Jinyang , Zhang Yajie , Wang Ping , Wang Di , Hu Xianhai , Wang Xianbiao
Published: May 2024

2,2′-Dithiodibenzoic acid ester diol was introduced into the polyurethane main chain in different ways, resulting in polyurethane elastomers that exhibited self-healing capability, fluorescence performance and robust mechanical properties.
Construction of an MIL-101(Fe)/layered bimetallic oxide heterojunction for enhanced ciprofloxacin removal
Authors: Xue Shikai , Zhu Dongying , Zuo Qing , Yang Shuangfeng , Wang Haiyan , Lu Qiujun , Yin Guoxing , Ruan Guihua , Du Fuyou
Published: May 2024

A novel MIL-101(Fe)/ZnCrZr-LBMO heterojunction was successfully constructed and used for the removal of ciprofloxacin (CIP) in this work.
High-yield, fast, and green synthesis of acridine derivatives using a Co/C catalyst from rice husks with a microwave-assisted method
Authors: Nguyen Phat Ngoc , Nguyen Gia-Linh Ngoc , Duong The-Anh Trinh , Le Mai-Phuong Thi , Nguyen Linh Phi , Kim Jinsoo , Tran Phuong Hoang , Truong Huynh-Hoa Thi , Nguyen Hai Truong
Published: May 2024

The concepts about “microwave-assisted synthesis” and “microwave reaction enhancement” have become increasingly popular because of their appropriateness in different organic transformations.
An anthropocene-framed transdisciplinary dialog at the chemistry-energy nexus
Authors: Prévot Mathieu S. , Finelli Valeria , Carrier Xavier , Deplano Gabriele , Cavallo Margherita , Quadrelli Elsje Alessandra , Michel Juliette , Pietraru Marie-Hélène , Camp Clément , Forghieri Giulia , Gagliardi Anna , Seidel Sebastian , Missemer Antoine , Reuillard Bertrand , Centrella Barbara , Bordiga Silvia , Salamanca González María Grace , Artero Vincent , Birkelbach Keanu V. A. , von Wolff Niklas
Published: May 2024

Five molecules at the energy-chemistry nexus, their position in the planetary boundary framework and Anthropocene-spurred interdisciplinary connections between chemistry, social sciences, and humanities to help define sustainability-driven research.
DELLA proteins recruit the Mediator complex subunit MED15 to coactivate transcription in land plants
Authors: Hernández-García Jorge , Serrano-Mislata Antonio , Lozano-Quiles María , Úrbez Cristina , Nohales María A. , Blanco-Touriñán Noel , Peng Huadong , Ledesma-Amaro Rodrigo , Blázquez Miguel A.
Published: May 2024

DELLA proteins are negative regulators of the gibberellin response pathway in angiosperms, acting as central hubs that interact with hundreds of transcription factors (TFs) and regulators to modulate their activities. While the mechanism of TF sequestration by DELLAs to prevent DNA binding to downstream targets has been extensively documented, the mechanism that allows them to act as coactivators remains to be understood. Here, we demonstrate that DELLAs directly recruit the Mediator complex to specific loci in Arabidopsis, facilitating transcription. This recruitment involves DELLA amino-terminal domain and the conserved MED15 KIX domain. Accordingly, partial loss of MED15 function mainly disrupted processes known to rely on DELLA coactivation capacity, including cytokinin-dependent regulation of meristem function and skotomorphogenic response, gibberellin metabolism feedback, and flavonol production. We have also found that the single DELLA protein in the liverwort
Marchantia polymorpha
is capable of recruiting MpMED15 subunits, contributing to transcriptional coactivation. The conservation of Mediator-dependent transcriptional coactivation by DELLA between Arabidopsis and Marchantia implies that this mechanism is intrinsic to the emergence of DELLA in the last common ancestor of land plants.
Pitfalls and possibilities of using Root SedLine for continuous assessment of EEG waveform-based metrics in intensive care research
Authors: Bögli Stefan Yu , Cherchi Marina Sandra , Olakorede Ihsane , Lavinio Andrea , Beqiri Erta , Moyer Ethan , Moberg Dick , Smielewski Peter
Published: May 2024

Objective. The Root SedLine device is used for continuous electroencephalography (cEEG)-based sedation monitoring in intensive care patients. The cEEG traces can be collected for further processing and calculation of relevant metrics not already provided. Depending on the device settings during acquisition, the acquired traces may be distorted by max/min value cropping or high digitization errors. We aimed to systematically assess the impact of these distortions on metrics used for clinical research in the field of neuromonitoring. Approach. A 16 h cEEG acquired using the Root SedLine device at the optimal screen settings was analyzed. Cropping and digitization error effects were simulated by consecutive reduction of the maximum cEEG amplitude by 2 µV or by reducing the vertical resolution. Metrics were calculated within ICM+ using minute-by-minute data, including the total power, alpha delta ratio (ADR), and 95% spectral edge frequency. Data were analyzed by creating violin- or box-plots. Main Results. Cropping led to a continuous reduction in total and band power, leading to corresponding changes in variability thereof. The relative power and ADR were less affected. Changes in resolution led to relevant changes. While the total power and power of low frequencies were rather stable, the power of higher frequencies increased with reducing resolution. Significance. Care must be taken when acquiring and analyzing cEEG waveforms from Root SedLine for clinical research. To retrieve good quality metrics, the screen settings must be kept within the central vertical scale, while pre-processing techniques must be applied to exclude unacceptable periods.
Photoinduced Floquet higher-order Weyl semimetal in C6 symmetric Dirac semimetals
Authors: Xu 许 Xin-Xin 欣欣 , Wang 王 Zi-Ming 梓名 , Xu 许 Dong-Hui 东辉 , Chen 陈 Chui-Zhen 垂针
Published: May 2024

Topological Dirac semimetals are a parent state from which other exotic topological phases of matter, such as Weyl semimetals and topological insulators, can emerge. In this study, we investigate a Dirac semimetal possessing sixfold rotational symmetry and hosting higher-order topological hinge Fermi arc states, which is irradiated by circularly polarized light. Our findings reveal that circularly polarized light splits each Dirac node into a pair of Weyl nodes due to the breaking of time-reversal symmetry, resulting in the realization of the Weyl semimetal phase. This Weyl semimetal phase exhibits rich boundary states, including two-dimensional surface Fermi arc states and hinge Fermi arc states confined to six hinges. Furthermore, by adjusting the incident direction of the circularly polarized light, we can control the degree of tilt of the resulting Weyl cones, enabling the realization of different types of Weyl semimetals.
Review on automated 2D material design
Authors: Al-Maeeni Abdalaziz , Lazarev Mikhail , Kazeev Nikita , Novoselov Kostya S , Ustyuzhanin Andrey
Published: May 2024

Deep learning (DL) methodologies have led to significant advancements in various domains, facilitating intricate data analysis and enhancing predictive accuracy and data generation quality through complex algorithms. In materials science, the extensive computational demands associated with high-throughput screening techniques such as density functional theory, coupled with limitations in laboratory production, present substantial challenges for material research. DL techniques are poised to alleviate these challenges by reducing the computational costs of simulating material properties and by generating novel materials with desired attributes. This comprehensive review document explores the current state of DL applications in materials design, with a particular emphasis on two-dimensional materials. The article encompasses an in-depth exploration of data-driven approaches in both forward and inverse design within the realm of materials science.