bluuebunny/crossref_metadata_2025 huggingface dataset:
Normative body mass-adjusted reference ranges of magnetic resonance imaging signs commonly used in diagnosing idiopathic intracranial hypertension in a healthy standard population
Authors: Kobrow Rike , Gross Stefan , Fleischmann Robert , Baldauf Jörg , Langner Sönke , Strauss Sebastian
Published: February 2024

Patients with chronic daily headaches (CDH) are often a diagnostic challenge and frequently undergo neuroimaging. One common underlying cause of CDH is idiopathic intracranial hypertension (IIH). However, certain neuroimaging abnormalities that suggest IIH, such as optic nerve sheath diameters (ONSD), pituitary gland height, and venous sinus diameter, require interpretation due to the absence of established normative values. Notably, intracranial pressure is known to varies with age, sex and weight, further complicating the determination of objectively abnormal findings within a specific patient group. This study aims to assist clinical neuroradiologists in differentiating neuroimaging results in CDH by providing weight-adjusted normative values for imaging characteristics of IIH. In addition to age and BMI we here assessed 1924 population-based T1-weighted MRI datasets of healthy participants for relevant MRI aspects of IIH. Association to BMI was analyzed using linear/logistic regression controlled for age and stratified for sex. ONSD was 4.3 mm [2.8; 5.9]/4.6 mm [3.6; 5.7] and diameter of transverse sinus was 4.67 mm [1.6; 6.5]/4.45 mm [3.0; 7.9]. Height of pituitary gland was 5.1 mm [2.2;8.1]/4.6 mm [1.9;7.1] for female and male respectively. Values generally varied with BMI with regression slopes spanning 0.0001 to 0.05 and were therefor presented as normative values stratified by BMI. Protrusion of ocular papilla, empty sella and transverse sinus occlusion were rare in total. Our data show an association between BMI and commonly used MRI features for diagnosing IIH. We provide categorized normative BMI values for ONSD, pituitary gland height, and transverse sinus diameter. This distinction helps objectively identify potential IIH indicators compared to regular population norms, enhancing diagnostic accuracy for suspected IIH patients. Notably, optic nerve head protrusion, empty sella, and transverse sinus occlusion are rare in healthy individuals, solidifying their importance as imaging markers regardless of BMI.
Role of substrate temperature on the performance of BaTiO3/Si photodetector prepared by pulsed laser deposition
Authors: Abed Nadheer Z. , Ismail Raid A. , Shaker Suaad S.
Published: February 2024

In this study, the pulsed laser deposition (PLD) method was employed to fabricate nanostructured BaTiO3 films on glass and silicon substrates at varying temperatures. The structural analysis confirmed the formation of crystalline nanostructured BaTiO3 with mixed tetragonal and hexagonal phases, and the film deposited at 150 °C has the best crystallinity and largest particle size. The optical energy gap of the BaTiO3 nanostructure decreases from 3.94 to 3.84 eV, with increasing substrate temperature from 60 to 150 °C. Photoluminescence spectra of BaTiO3 films deposited at 25, 60, 100, and 150 °C exhibit emission peaks centered at 450, 512, 474, and 531 nm, respectively. Raman spectra of BaTiO3 films show E (LO), A (TO), E (LO) + TO, and B1 vibration modes. Hall measurements reveal that the mobility of the BaTiO3 film increases with temperature up to 100 °C and then decreases at 150 °C. The current–voltage characteristics of the BaTiO3/p-Si heterojunction, deposited over a temperature range of 25 to 150 °C, were investigated in the dark and under illumination. The heterojunctions exhibit rectifying properties, with the best rectification factor observed for the heterojunction prepared at 100 °C. The values of the ideality factor for the heterojunctions fabricated at 25, 60, 100, and 150 °C were 4.3, 3.8, 2.8, and 5, respectively. The study reveals an improvement in both the figures of merit and the photodetector performance with increased substrate temperature. The responsivity increases from 2.2 to 9.25 A/W as the deposition temperature rises from 25 to 100 °C. The detectivity (D*) and external quantum efficiency (EQE) of the photodetector prepared at the optimum substrate temperature of 100 °C, were found to be 4.62 × 1012 Jones and 114%, respectively, at 500 nm.
A cognitive deep learning approach for medical image processing
Authors: Fakhouri Hussam N. , Alawadi Sadi , Awaysheh Feras M. , Alkhabbas Fahed , Zraqou Jamal
Published: February 2024

In ophthalmic diagnostics, achieving precise segmentation of retinal blood vessels is a critical yet challenging task, primarily due to the complex nature of retinal images. The intricacies of these images often hinder the accuracy and efficiency of segmentation processes. To overcome these challenges, we introduce the cognitive DL retinal blood vessel segmentation (CoDLRBVS), a novel hybrid model that synergistically combines the deep learning capabilities of the U-Net architecture with a suite of advanced image processing techniques. This model uniquely integrates a preprocessing phase using a matched filter (MF) for feature enhancement and a post-processing phase employing morphological techniques (MT) for refining the segmentation output. Also, the model incorporates multi-scale line detection and scale space methods to enhance its segmentation capabilities. Hence, CoDLRBVS leverages the strengths of these combined approaches within the cognitive computing framework, endowing the system with human-like adaptability and reasoning. This strategic integration enables the model to emphasize blood vessels, accurately segment effectively, and proficiently detect vessels of varying sizes. CoDLRBVS achieves a notable mean accuracy of 96.7%, precision of 96.9%, sensitivity of 99.3%, and specificity of 80.4% across all of the studied datasets, including DRIVE, STARE, HRF, retinal blood vessel and Chase-DB1. CoDLRBVS has been compared with different models, and the resulting metrics surpass the compared models and establish a new benchmark in retinal vessel segmentation. The success of CoDLRBVS underscores its significant potential in advancing medical image processing, particularly in the realm of retinal blood vessel segmentation.
Behavioral analysis of kainate receptor KO mice and the role of GluK3 subunit in anxiety
Authors: Iida Izumi , Konno Kohtarou , Natsume Rie , Abe Manabu , Watanabe Masahiko , Sakimura Kenji , Terunuma Miho
Published: February 2024

Kainate receptors (KARs) are one of the ionotropic glutamate receptors in the central nervous system (CNS) comprised of five subunits, GluK1-GluK5. There is a growing interest in the association between KARs and psychiatric disorders, and there have been several studies investigating the behavioral phenotypes of KAR deficient mice, however, the difference in the genetic background has been found to affect phenotype in multiple mouse models of human diseases. Here, we examined GluK1-5 single KO mice in a pure C57BL/6N background and identified that GluK3 KO mice specifically express anxiolytic-like behavior with an alteration in dopamine D2 receptor (D2R)-induced anxiety, and reduced D2R expression in the striatum. Biochemical studies in the mouse cortex confirmed that GluK3 subunits do not assemble with GluK4 and GluK5 subunits, that can be activated by lower concentration of agonists. Overall, we found that GluK3-containing KARs function to express anxiety, which may represent promising anti-anxiety medication targets.
Building integrated diffusers’ area ratio optimization
Authors: Elbakheit Abdel Rahman
Published: February 2024

This paper presents an investigation into the effect of area ratio parameter of diffusers on its energy output through power coefficient Cp. This parameter has effect both on diffusers’ energy yield, besides diffuser’s size for architectural integration prospects. A systematic increase in diffusers area ratio is adopted following standardized diffuser profile presented by NACA 1244 aerofoil. A series of area ratios were investigated (i.e., 1.25, 1.5, 1.75, 2, 2.5, 3 and 3.5). Area ratio of 1.5 (i.e., outlet/inlet, 0.75 m/0.50 m) exhibited the highest power coefficient Cp of 4.2, in addition to achieving highest resulting velocity of 25.8 m/s under incident velocity of 16m/s. Considerable wind separation inside inner walls of diffusers occurred from area ratio 1.75 onwards, which impacted resulting velocities. Simulations performed with ANSYS CFD Academic to standalone diffusers. A series of incident velocities employed from 1 to 16 m/s that resulted in velocity increase by 120–156% respectively.
High-dose exposure to butylparaben impairs thyroid ultrastructure and function in rats
Authors: Jiang Qi-Lan , Li Sha , Zeng Yang , Zhang Bo-Tao , Cao Yu , Li Tao , Jiang Jun
Published: February 2024

Parabens (PBs) are a class of preservatives commonly used in cosmetics and pharmaceuticals. Studies have shown that these compounds may act as endocrine disruptors, affecting thyroxine levels in humans. PBs with longer chain substituents, such as butylparaben (BuP), are less prone to complete biotransformation and are therefore more likely to accumulate in the body. In this study, the effect of high-dose exposure to BuP on thyroid microstructure, ultrastructure, and function was investigated in rats. 50 mg/kg bw per day of BuP was injected subcutaneously into the neck of rats for 4 weeks. Rat thyroid weight, microstructure, and ultrastructure were determined, and the levels of thyroid sodium/iodide symporter (NIS), serum thyroid hormones, and thyroid autoantibodies were measured. The human thyroid cell line was used to study the mechanism of BuP on thyroid epithelial cells. The weight of the thyroid gland of BuP-exposed rats was increased, the structure of the thyroid follicles was irregular and damaged, the mitochondria and rough endoplasmic reticulum were swollen and damaged, and the microvilli at the tip of the epithelium were reduced and disappeared. Serum total T3, total T4, free T3, and free T4 were decreased in BuP-exposed rats, and TSH, peroxidase antibody, and thyroglobulin antibody were increased. In vitro, BuP decreased the level of NIS in thyroid epithelial cells, inhibited proliferation and viability, and induced apoptosis in a dose-dependent manner. This study demonstrated that high-dose exposure to BuP induced structural, ultrastructural, and functional impairment to the thyroid gland of rats, which may be one of the factors leading to hypothyroidism.
A nationwide cohort study on the association between intensive care treatments and mental distress linked psychiatric disorders
Authors: Mossberg Rasmus , Ahlström Björn , Lipcsey Miklos
Published: February 2024

Given the psychic strain patients experience in the intensive care unit (ICU), a potential risk of mental disorders has been suggested. However, the effects of intensive care treatment per se are unknown. We investigated whether the level of intensive care treatments is an independent risk factor for developing long-term mental disorders after intensive care. In a national cohort of adult ICU patients we combined data on diagnoses, treatment, and causes of death. We defined extensive ICU treatment as being treated with invasive ventilation for > 24 h, continuous renal replacement therapy, or both. The primary outcome was incident mental disorder 1 year after ICU admission. Extensive ICU treatment was found to be associated with a decreased risk of developing a mental disorder ≥ 1 year after ICU admission (HR 0.90, 95% CI 0.82–0.99, p = 0.04), and increasing severity of acute illness (HR 1.18, 95% CI 1.06–1.32, p < 0.001) were associated with an increased risk of mental disorders. Because death acted as a competing risk for mental illness, mortality might help explain the apparent protective effect of extensive ICU care.

Trial registration Clinical Trials Registry (Identification number NCT05137977). Registered 16 November 2021. As a registry trial the patients were already included at the trial registration i.e. it was retrospectively registered.
Optimizing warfarin dosing for patients with atrial fibrillation using machine learning
Authors: Petch Jeremy , Nelson Walter , Wu Mary , Ghassemi Marzyeh , Benz Alexander , Fatemi Mehdi , Di Shuang , Carnicelli Anthony , Granger Christopher , Giugliano Robert , Hong Hwanhee , Patel Manesh , Wallentin Lars , Eikelboom John , Connolly Stuart J.
Published: February 2024

While novel oral anticoagulants are increasingly used to reduce risk of stroke in patients with atrial fibrillation, vitamin K antagonists such as warfarin continue to be used extensively for stroke prevention across the world. While effective in reducing the risk of strokes, the complex pharmacodynamics of warfarin make it difficult to use clinically, with many patients experiencing under- and/or over- anticoagulation. In this study we employed a novel implementation of deep reinforcement learning to provide clinical decision support to optimize time in therapeutic International Normalized Ratio (INR) range. We used a novel semi-Markov decision process formulation of the Batch-Constrained deep Q-learning algorithm to develop a reinforcement learning model to dynamically recommend optimal warfarin dosing to achieve INR of 2.0–3.0 for patients with atrial fibrillation. The model was developed using data from 22,502 patients in the warfarin treated groups of the pivotal randomized clinical trials of edoxaban (ENGAGE AF-TIMI 48), apixaban (ARISTOTLE) and rivaroxaban (ROCKET AF). The model was externally validated on data from 5730 warfarin-treated patients in a fourth trial of dabigatran (RE-LY) using multilevel regression models to estimate the relationship between center-level algorithm consistent dosing, time in therapeutic INR range (TTR), and a composite clinical outcome of stroke, systemic embolism or major hemorrhage. External validation showed a positive association between center-level algorithm-consistent dosing and TTR (R2 = 0.56). Each 10% increase in algorithm-consistent dosing at the center level independently predicted a 6.78% improvement in TTR (95% CI 6.29, 7.28; p < 0.001) and a 11% decrease in the composite clinical outcome (HR 0.89; 95% CI 0.81, 1.00; p = 0.015). These results were comparable to those of a rules-based clinical algorithm used for benchmarking, for which each 10% increase in algorithm-consistent dosing independently predicted a 6.10% increase in TTR (95% CI 5.67, 6.54, p < 0.001) and a 10% decrease in the composite outcome (HR 0.90; 95% CI 0.83, 0.98, p = 0.018). Our findings suggest that a deep reinforcement learning algorithm can optimize time in therapeutic range for patients taking warfarin. A digital clinical decision support system to promote algorithm-consistent warfarin dosing could optimize time in therapeutic range and improve clinical outcomes in atrial fibrillation globally.
Kinetic characterization of human mRNA guanine-N7 methyltransferase
Authors: Perveen Sumera , Yazdi Aliakbar Khalili , Hajian Taraneh , Li Fengling , Vedadi Masoud
Published: February 2024

The 5′-mRNA-cap formation is a conserved process in protection of mRNA in eukaryotic cells, resulting in mRNA stability and efficient translation. In humans, two methyltransferases, RNA cap guanine-N7 methyltransferase (hRNMT) and cap-specific nucleoside-2′-O-methyltransferase 1 (hCMTr1) methylate the mRNA resulting in cap0 (N7mGpppN-RNA) and cap1 (N7mGpppN2′-Om-RNA) formation, respectively. Coronaviruses mimic this process by capping their RNA to evade human immune systems. The coronaviral nonstructural proteins, nsp14 and nsp10-nsp16, catalyze the same reactions as hRNMT and hCMTr1, respectively. These two viral enzymes are important targets for development of inhibitor-based antiviral therapeutics. However, assessing the selectivity of such inhibitors against human corresponding proteins is crucial. Human RNMTs have been implicated in proliferation of cancer cells and are also potential targets for development of anticancer therapeutics. Here, we report the development and optimization of a radiometric assay for hRNMT, full kinetic characterization of its activity, and optimization of the assay for high-throughput screening with a Z-factor of 0.79. This enables selectivity determination for a large number of hits from various screening of coronaviral methyltransferases, and also screening hRNMT for discovery of inhibitors and chemical probes that potentially could be used to further investigate the roles RNMTs play in cancers.
Dynamic and distinct histone modifications facilitate human trophoblast lineage differentiation
Authors: Lee Bum-Kyu , Salamah Joudi , Cheeran Elisha , Adu-Gyamfi Enoch Appiah
Published: February 2024

The placenta serves as an essential organ for fetal growth throughout pregnancy. Histone modification is a crucial regulatory mechanism involved in numerous biological processes and development. Nevertheless, there remains a significant gap in our understanding regarding the epigenetic regulations that influence trophoblast lineage differentiation, a fundamental aspect of placental development. Here, through comprehensive mapping of H3K4me3, H3K27me3, H3K9me3, and H3K27ac loci during the differentiation of trophoblast stem cells (TSCs) into syncytiotrophoblasts (STs) and extravillous trophoblasts (EVTs), we reveal dynamic reconfiguration in H3K4me3 and H3K27ac patterns that establish an epigenetic landscape conducive to proper trophoblast lineage differentiation. We observe that broad H3K4me3 domains are associated with trophoblast lineage-specific gene expression. Unlike embryonic stem cells, TSCs lack robust bivalent domains. Notably, the repression of ST- and EVT-active genes in TSCs is primarily attributed to the weak H3K4me3 signal rather than bivalent domains. We also unveil the inactivation of TSC enhancers precedes the activation of ST enhancers during ST formation. Our results provide a comprehensive global map of diverse histone modifications, elucidating the dynamic histone modifications during trophoblast lineage differentiation.
Biomarker screening using integrated bioinformatics for the development of “normal—impaired glucose intolerance—type 2 diabetes mellitus”
Authors: Luo Dongqiang , Gao Xiaolu , Zhu Xianqiong , Xu Jiongbo , Gao Pengfei , Zou Jiayi , Fan Qiaoming , Xu Ying , Liu Tian
Published: February 2024

Type 2 diabetes mellitus (T2DM) is a progressive disease. We utilized bioinformatics analysis and experimental research to identify biomarkers indicative of the progression of T2DM, aiming for early detection of the disease and timely clinical intervention. Integrating Mfuzz analysis with differential expression analysis, we identified 76 genes associated with the progression of T2DM, which were primarily enriched in signaling pathways such as apoptosis, p53 signaling, and necroptosis. Subsequently, using various analytical methods, including machine learning, we further narrowed down the hub genes to STK17A and CCT5. Based on the hub genes, we calculated the risk score for samples and interestingly found that the score correlated with multiple programmed cell death (PCD) pathways. Animal experiments revealed that the diabetes model exhibited higher levels of MDA and LDH, with lower expression of SOD, accompanied by islet cell apoptosis. In conclusion, our study suggests that during the progression of diabetes, STK17A and CCT5 may contribute to the advancement of the disease by regulating oxidative stress, programmed cell death pathways, and critical signaling pathways such as p53 and MAPK, thereby promoting the death of islet cells. This provides substantial evidence in support of further disease prevention and treatment strategies.
Modeling the Brazilian Cerrado land use change highlights the need to account for private property sizes for biodiversity conservation
Authors: Colman Carina Barbosa , Guerra Angélica , Almagro André , de Oliveira Roque Fabio , Rosa Isabel M. D. , Fernandes Geraldo Wilson , Oliveira Paulo Tarso S.
Published: February 2024

Simulating future land use changes can be an important tool to support decision-making, especially in areas that are experiencing rapid anthropogenic pressure, such as the Cerrado–Brazilian savanna. Here we used a spatially-explicit model to identify the main drivers of native vegetation loss in the Cerrado and then extrapolate this loss for 2050 and 2070. We also analyzed the role of property size in complex Brazilian environmental laws in determining different outcomes of these projections. Our results show that distance to rivers, roads, and cities, agricultural potential, permanent and annual crop agriculture, and cattle led to observed/historical loss of vegetation, while protected areas prevented such loss. Assuming full adoption of the current Forest Code, the Cerrado may lose 26.5 million ha (± 11.8 95% C.I.) of native vegetation by 2050 and 30.6 million ha (± 12.8 95% C.I.) by 2070, and this loss shall occur mainly within large properties. In terms of reconciling conservation and agricultural production, we recommend that public policies focus primarily on large farms, such as protecting 30% of the area of properties larger than 2500 ha, which would avoid a loss of more than 4.1 million hectares of native vegetation, corresponding to 13% of the predicted loss by 2070.
Circulating miR-let7a levels predict future diagnosis of chronic thromboembolic pulmonary hypertension
Authors: Kenneweg Franziska , Hobohm Lukas , Bang Claudia , Gupta Shashi K. , Xiao Ke , Thum Sabrina , Ten Cate Vincent , Rapp Steffen , Hasenfuß Gerd , Wild Philipp , Konstantinides Stavros , Wachter Rolf , Lankeit Mareike , Thum Thomas
Published: February 2024

Distinct patterns of circulating microRNAs (miRNAs) were found to be involved in misguided thrombus resolution. Thus, we aimed to investigate dysregulated miRNA signatures during the acute phase of pulmonary embolism (PE) and test their diagnostic and predictive value for future diagnosis of chronic thromboembolic pulmonary hypertension (CTEPH). Microarray screening and subsequent validation in a large patient cohort (n = 177) identified three dysregulated miRNAs as potential biomarkers: circulating miR-29a and miR-720 were significantly upregulated and miR-let7a was significantly downregulated in plasma of patients with PE. In a second validation study equal expression patterns for miR-29a and miR-let7a regarding an acute event of recurrent venous thromboembolism (VTE) or deaths were found. MiR-let7a concentrations significantly correlated with echocardiographic and laboratory parameters indicating right ventricular (RV) dysfunction. Additionally, circulating miR-let7a levels were associated with diagnosis of CTEPH during follow-up. Regarding CTEPH diagnosis, ROC analysis illustrated an AUC of 0.767 (95% CI 0.54–0.99) for miR-let7a. Using logistic regression analysis, a calculated patient-cohort optimized miR-let7a cut-off value derived from ROC analysis of ≥ 11.92 was associated with a 12.8-fold increased risk for CTEPH. Therefore, miR-let7a might serve as a novel biomarker to identify patients with haemodynamic impairment and as a novel predictor for patients at risk for CTEPH.
The potato rhizosphere microbiota correlated to the yield of three different regions in Korea
Authors: Bak Gye-Ryeong , Lee Kiseok Keith , Clark Ian M. , Mauchline Tim H. , Kavamura Vanessa Nessner , Lund George , Jee Samnyu , Lee Jeong-Tae , Kim Hyun , Lee Yong-Hwan
Published: February 2024

We examined potato rhizosphere bacterial and fungal communities across three regions: Cheongju, Pyeongchang, and Gangneung. These regions have varying soil and climate conditions, resulting in different yields. We found that precipitation was the main limiting factor in our study while soil physiochemical factors affect bacterial and fungal microbiota in correlation with yield. Both bacterial and fungal microbiota showed distinct patterns according to the regions. ASVs positively correlated with yield were predominantly found in the Pyeongchang region which also produced the highest yields, while ASVs negatively correlated with yield were associated with Gangneung where the lowest yields were observed. The greatest bacterial and fungal diversity was detected in Pyeongchang consisting of Propionibacteriales, Burkholderiales, and Vicinamibacteriales. Gangneung, on the other hand primarily belong to Sordariales, Mortierellales, Cystofilobasidiales, and Tremellales. The putative yield-negative ASVs detected in Gangneung may have been influenced by drought stress. This work has highlighted key bacterial and fungal taxa as well as core taxa that may potentially be associated with high and low yields of potato in relation to metadata which includes soil chemical and physical parameters as well as weather data. Taken together we suggest that this information can be used to assess site suitability for potato production.
An improved sparrow search algorithm and CNN-BiLSTM neural network for predicting sea level height
Authors: Li Xiao , Zhou Shijian , Wang Fengwei , Fu Laiying
Published: February 2024

Accurate prediction of sea level height is critically important for the government in assessing sea level risk in coastal areas. However, due to the nonlinear, time-varying and highly uncertain characteristics of sea level change data, sea level prediction is challenging. To improve the accuracy of sea level prediction, this paper uses a new swarm intelligence algorithm named the sparrow search algorithm (SSA), which can imitate the foraging behavior and antipredation behavior of sparrows, to determine optimal solutions. To avoid the algorithm falling into a local optimal situation, this paper integrates the sine–cosine algorithm and the Cauchy variation strategy into the SSA to obtain an algorithm named the SCSSA. The SCSSA is used to optimize the parameter values of the CNN-BiLSTM (convolutional neural network combined with bidirectional long short-term memory neural network) model; finally, a combined neural network model (named SCSSA-CNN-BiLSTM) is proposed. In this paper, the time series data of seven tidal stations located in coastal China are used for experimental analysis. First, the SCSSA-CNN-BiLSTM model is compared with the CNN-BiLSTM model to predict the time series data of SHANWEI Station. With respect to the training and test sets of data, the SCSSA-CNN-BiLSTM model outperforms the other models on all the evaluation metrics. In addition, the remaining six tide station datasets and five neural network models, including the SCSSA-CNN-BiLSTM model, are used to further study the performance of the proposed prediction model. Four evaluation indices including the root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of determination (R2) are adopted. For six stations, the RMSE, MAE, MAPE and R2of SCSSA-CNN-BiLSTM model are ranged from 20.9217 ~ 27.8427 mm, 9.4770 ~ 17.8603 mm, 0.1322% ~ 0.2482% and 0.9119 ~ 0.9759, respectively. The experimental analysis results show that the SCSSA-CNN-BiLSTM model makes effective predictions at all stations, and the prediction performance is better than that of the other models. Even though the combination of SCSSA algorithm may increase the complexity of the model, indeed the proposed model is a new prediction method with good accuracy and robustness for predicting sea level change.
Implantable theranostic device for in vivo real-time NMR evaluation of drug impact in brain tumors
Authors: Deborne Justine , Benkhaled Imad , Bouchaud Véronique , Pinaud Noël , Crémillieux Yannick
Published: February 2024

The evaluation of the efficacy of a drug is a fundamental step in the development of new treatments or in personalized therapeutic strategies and patient management. Ideally, this evaluation should be rapid, possibly in real time, easy to perform and reliable. In addition, it should be associated with as few adverse effects as possible for the patient. In this study, we present a device designed to meet these goals for assessing therapeutic response. This theranostic device is based on the use of magnetic resonance imaging and spectroscopy for the diagnostic aspect and on the application of the convection-enhanced delivery technique for the therapeutic aspect. The miniaturized device is implantable and can be used in vivo in a target tissue. In this study, the device was applied to rodent glioma models with local administration of choline kinase inhibitor and acquisition of magnetic resonance images and spectra at 7 Tesla. The variations in the concentration of key metabolites measured by the device during the administration of the molecules demonstrate the relevance of the approach and the potential of the device.
Extracting interpretable features for pathologists using weakly supervised learning to predict p16 expression in oropharyngeal cancer
Authors: Adachi Masahiro , Taki Tetsuro , Sakamoto Naoya , Kojima Motohiro , Hirao Akihiko , Matsuura Kazuto , Hayashi Ryuichi , Tabuchi Keiji , Ishikawa Shumpei , Ishii Genichiro , Sakashita Shingo
Published: February 2024

One drawback of existing artificial intelligence (AI)-based histopathological prediction models is the lack of interpretability. The objective of this study is to extract p16-positive oropharyngeal squamous cell carcinoma (OPSCC) features in a form that can be interpreted by pathologists using AI model. We constructed a model for predicting p16 expression using a dataset of whole-slide images from 114 OPSCC biopsy cases. We used the clustering-constrained attention-based multiple-instance learning (CLAM) model, a weakly supervised learning approach. To improve performance, we incorporated tumor annotation into the model (Annot-CLAM) and achieved the mean area under the receiver operating characteristic curve of 0.905. Utilizing the image patches on which the model focused, we examined the features of model interest via histopathologic morphological analysis and cycle-consistent adversarial network (CycleGAN) image translation. The histopathologic morphological analysis evaluated the histopathological characteristics of image patches, revealing significant differences in the numbers of nuclei, the perimeters of the nuclei, and the intercellular bridges between p16-negative and p16-positive image patches. By using the CycleGAN-converted images, we confirmed that the sizes and densities of nuclei are significantly converted. This novel approach improves interpretability in histopathological morphology-based AI models and contributes to the advancement of clinically valuable histopathological morphological features.
The diagnostic performance evaluation of Panbio and STANDARD Q coronavirus disease 2019 antigen tests against real-time polymerase chain reaction in southern Ethiopia
Authors: Tamene Elias , Beyene Alemitu , Atsbeha Hanibale , Shimelis Techalew
Published: February 2024

The coronavirus disease 2019 (COVID-19) pandemic has created a public health crisis. This study aimed to evaluate the diagnostic performance of the Panbio and STANDARD Q COVID-19 antigen rapid diagnostic tests (RDTs) against the real-time polymerase chain reaction (RT-PCR) at one of the largest hospitals in southern Ethiopia. Nasopharyngeal samples, which were collected during the pandemic from individuals suspected of COVID-19 and stored at − 70 °C, were analyzed in June and July 2022. The performance of the Panbio COVID-19 antigen tests was evaluated in 200 randomly selected nasopharyngeal samples (100 positives and 100 negatives for severe acute respiratory syndrome 2 by RT-PCR). The STANDARD Q test was evaluated using 100 positive and 50 negative samples. The respective sensitivity, specificity, positive predictive value and negative predictive values were 88%, 99%, 98.9% and 89.2% for the Panbio test and 91%, 98%, 98.9% and 84.5%, for the STANDARD Q test. The kappa values were 0.87 for the Panbio and 0.86 for the STANDARD Q test. Based on the findings presented here, the RDTs could be utilized as an alternative to conventional RT-PCR when it is challenging to diagnose COVID-19 owing to a lack of time, skilled lab personnel, or suitable equipment or electricity.
Efficiency optimization in quantum computing: balancing thermodynamics and computational performance
Authors: Śmierzchalski Tomasz , Mzaouali Zakaria , Deffner Sebastian , Gardas Bartłomiej
Published: February 2024

We investigate the computational efficiency and thermodynamic cost of the D-Wave quantum annealer under reverse-annealing with and without pausing. Our demonstration on the D-Wave 2000Q annealer shows that the combination of reverse-annealing and pausing leads to improved computational efficiency while minimizing the thermodynamic cost compared to reverse-annealing alone. Moreover, we find that the magnetic field has a positive impact on the performance of the quantum annealer during reverse-annealing but becomes detrimental when pausing is involved. Our results, which are reproducible, provide strategies for optimizing the performance and energy consumption of quantum annealing systems employing reverse-annealing protocols.
Diabetes mellitus modifies the association between chronic kidney disease–mineral and bone disorder biomarkers and aortic stiffness in peritoneal dialysis patients
Authors: Huang Hsiang-Jung , Hsu Bang-Gee , Wang Chih-Hsien , Tsai Jen-Pi , Chen Yi-Hsin , Hung Szu-Chun , Lin Yu-Li
Published: February 2024

This study aimed to investigate the relationship of four chronic kidney disease–mineral and bone disorder (CKD–MBD) biomarkers, including intact parathyroid hormone (PTH), fibroblast growth factor 23 (FGF23), soluble klotho, and fetuin-A, with aortic stiffness in peritoneal dialysis (PD) patients, comparing those with and without diabetes mellitus (DM). A total of 213 patients (mean age 58 ± 14 years; 81 (38.0%) patients with DM) were enrolled. Their aortic pulse wave velocity (PWV) was measured using pressure applanation tonometry, while serum intact PTH, FGF23, α-klotho, and fetuin-A levels were measured using enzyme-linked immunosorbent assay. Overall, patients with DM had higher aortic PWV than those without (9.9 ± 1.8 vs. 8.6 ± 1.4 m/s, p < 0.001). Among the four CKD–MBD biomarkers, FGF23 levels were significantly lower in DM group (462 [127–1790] vs. 1237 [251–3120] pg/mL, p = 0.028) and log-FGF23 independently predicted aortic PWV in DM group (β: 0.61, 95% confidence interval: 0.06–1.16, p = 0.029 in DM group; β: 0.10, 95% confidence interval: − 0.24–0.45, p = 0.546 in nonDM group; interaction p = 0.016). In conclusion, the association between FGF23 and aortic PWV was significantly modified by DM status in PD patients.
Assessing the role of dryness and burning sensation in diagnosing laryngopharyngeal reflux
Authors: Zheng Xiaowei , Chen Zhiwei , Chen Ting , Zhou Liqun , Liu Chaofeng , Zheng Jingyi , Hu Renyou
Published: February 2024

Laryngopharyngeal reflux disease (LPRD) is a condition characterized by the regurgitation of stomach and duodenal contents into the laryngopharynx, with variable and non-specific symptoms. Therefore, developing an accurate symptom scale for different regions is essential. Notably, the symptoms of “dryness and burning sensation in the laryngopharynx or mouth” are prevalent among the Chinese population but are often omitted from conventional symptom assessment scales, such as the Reflux Symptom Index (RSI) and Reflux Symptom Score-12 (RSS-12) scales. To address this gap, our study incorporated the symptoms into the RSI and RSS-12 scales, developing the RSI-10/RSS-13 scales. Afterward, we assessed the role of the new scale’s reliability (Cronbach’s α and test–retest reliability), construct validity (confirmatory factor analysis and confirmatory factor analysis), and diagnostic efficiency. Our study encompassed 479 participants (average = 39.5 ± 13.4 years, 242 female) and 91 (average = 34.01 ± 13.50 years, 44 female) completed 24 h MII-pH monitoring. The Cronbach’s α values of 0.80 and 0.82 for the RSI-10 and RSS-13 scales, respectively. RSI-10 and RSS-13 exhibited strong test–retest reliability (ICCs = 0.82–0.96) and diagnostic efficacy (AUC = 0.84–0.85). Furthermore, the factor analysis identified the RSS-13 and its three sub-scales (ear-nose-throat, digestive tract, respiratory tract) exhibited good to excellent structural validity (χ2/df = 1.95, P < 0.01; CFI = 0.95, RMSEA = 0.06, SRMR = 0.05). The AUC optimal thresholds for the RSI-10 and RSS-13 in the Chinese population were 13 and 36, respectively. Besides, the inclusion of the new item significantly improved the diagnostic efficiency of the RSI scale (P = 0.04), suggesting that RSI-10 holds promise as a more effective screening tool for LPRD, and global validation is needed to demonstrate the impact of this new symptom on the diagnosis of LPRD.
Glymphatic and lymphatic communication with systemic responses during physiological and pathological conditions in the central nervous system
Authors: Licastro Ester , Pignataro Giuseppe , Iliff Jeffrey J. , Xiang Yanxiao , Lo Eng H. , Hayakawa Kazuhide , Esposito Elga
Published: February 2024

Crosstalk between central nervous system (CNS) and systemic responses is important in many pathological conditions, including stroke, neurodegeneration, schizophrenia, epilepsy, etc. Accumulating evidence suggest that signals for central-systemic crosstalk may utilize glymphatic and lymphatic pathways. The glymphatic system is functionally connected to the meningeal lymphatic system, and together these pathways may be involved in the distribution of soluble proteins and clearance of metabolites and waste products from the CNS. Lymphatic vessels in the dura and meninges transport cerebrospinal fluid, in part collected from the glymphatic system, to the cervical lymph nodes, where solutes coming from the brain (i.e., VEGFC, oligomeric α-syn, β-amyloid) might activate a systemic inflammatory response. There is also an element of time since the immune system is strongly regulated by circadian rhythms, and both glymphatic and lymphatic dynamics have been shown to change during the day and night. Understanding the mechanisms regulating the brain-cervical lymph node (CLN) signaling and how it might be affected by diurnal or circadian rhythms is fundamental to find specific targets and timing for therapeutic interventions.
Stepwise on-surface synthesis of nitrogen-doped porous carbon nanoribbons
Authors: Xu Jin , Xing Shuaipeng , Hu Jun , Shi Ziliang
Published: February 2024

Precise synthesis of carbon-based nanostructures with well-defined structural and chemical properties is of significance towards organic nanomaterials, but remains challenging. Herein, we report on a synthesis of nitrogen-doped porous carbon nanoribbons through a stepwise on-surface polymerization. Scanning tunneling microscopy revealed that the selectivity in molecular conformation, intermolecular debrominative aryl-aryl coupling and inter-chain dehydrogenative cross-coupling determined the well-defined topology and chemistry of the final products. Density functional theory calculations predict that the ribbons are semiconductors, and the band gap can be tuned by the width of the ribbons.
Oscillating photonic Bell state from a semiconductor quantum dot for quantum key distribution
Authors: Pennacchietti Matteo , Cunard Brady , Nahar Shlok , Zeeshan Mohd , Gangopadhyay Sayan , Poole Philip J. , Dalacu Dan , Fognini Andreas , Jöns Klaus D. , Zwiller Val , Jennewein Thomas , Lütkenhaus Norbert , Reimer Michael E.
Published: February 2024

An on-demand source of bright entangled photon pairs is desirable for quantum key distribution (QKD) and quantum repeaters. The leading candidate to generate such pairs is based on spontaneous parametric down-conversion (SPDC) in non-linear crystals. However, its pair extraction efficiency is limited to 0.1% when operating at near-unity fidelity due to multiphoton emission at high brightness. Quantum dots in photonic nanostructures can in principle overcome this limit, but the devices with high entanglement fidelity (99%) have low pair extraction efficiency (0.01%). Here, we show a measured peak entanglement fidelity of 97.5% ± 0.8% and pair extraction efficiency of 0.65% from an InAsP quantum dot in an InP photonic nanowire waveguide. We show that the generated oscillating two-photon Bell state can establish a secure key for peer-to-peer QKD. Using our time-resolved QKD scheme alleviates the need to remove the quantum dot energy splitting of the intermediate exciton states in the biexciton-exciton cascade.
Observational features of charge distribution in Earth’s inner magnetosphere
Authors: Gao Lai , Shen Chao , Zhou Yufei , Ji Yong , Pu Zuyin , Parks George , Russell Christopher T. , Zeng Gang , Ma Lan , Torbert Roy B. , Yang Yanyan , Burch James L.
Published: February 2024

Understanding the motion of charged particles in the electromagnetic field in the inner magnetosphere is essential for space science and space weather. Charge accumulation can occur due to the dipole magnetic and convective electric fields in this region. However, until the recent Magnetospheric Multiscale (MMS) mission, there were few means to detect charge distribution in situ. We report unambiguous in situ observation of the spatial distribution of the excess charge density in the inner magnetosphere by the MMS mission. We find that a positive (negative) charge accumulates in the dusk (dawn) side inner magnetospheres, which is contrary to the long assumed overall quasi-neutrality of space plasma. These observations and results offer insight into magnetosphere–ionosphere coupling.
Antarctic-wide ice-shelf firn emulation reveals robust future firn air depletion signal for the Antarctic Peninsula
Authors: Dunmire Devon , Wever Nander , Banwell Alison F. , Lenaerts Jan T. M.
Published: February 2024

Antarctic firn is critical for ice-shelf stability because it stores meltwater that would otherwise pond on the surface. Ponded meltwater increases the risk of hydrofracture and subsequent potential ice-shelf collapse. Here, we use output from a firn model to build a computationally simpler emulator that uses a random forest to predict ice-shelf effective firn air content, which considers impermeable ice layers that make deeper parts of the firn inaccessible to meltwater, based on climate conditions. We find that summer air temperature and precipitation are the most important climatic features for predicting firn air content. Based on the climatology from an ensemble of Earth System Models, we find that the Larsen C Ice Shelf is most at risk of firn air depletion during the 21st century, while the larger Ross and Ronne-Filchner ice shelves are unlikely to experience substantial firn air content change. This work demonstrates the utility of emulation for computationally efficient estimations of complicated ice sheet processes.
Machine learning reveals regime shifts in future ocean carbon dioxide fluxes inter-annual variability
Authors: Couespel Damien , Tjiputra Jerry , Johannsen Klaus , Vaittinada Ayar Pradeebane , Jensen Bjørnar
Published: February 2024

The inter-annual variability of global ocean air-sea CO2fluxes are non-negligible, modulates the global warming signal, and yet it is poorly represented in Earth System Models (ESMs). ESMs are highly sophisticated and computationally demanding, making it challenging to perform dedicated experiments to investigate the key drivers of the CO2flux variability across spatial and temporal scales. Machine learning methods can objectively and systematically explore large datasets, ensuring physically meaningful results. Here, we show that a kernel ridge regression can reconstruct the present and future CO2flux variability in five ESMs. Surface concentration of dissolved inorganic carbon (DIC) and alkalinity emerge as the critical drivers, but the former is projected to play a lesser role in the future due to decreasing vertical gradient. Our results demonstrate a new approach to efficiently interpret the massive datasets produced by ESMs, and offer guidance into future model development to better constrain the CO2flux.
Recent progress in nanomaterials for bacteria-related tumor therapy
Authors: Zhang Fuping , Wang Shuyu , Yang Shuo , Ma Feihe , Gao Hui
Published: February 2024

Recent progress in nanomaterials for bacteria-related tumor therapy in terms of chemotherapy, immunotherapy and synergistic therapy is summarized in this review in order to provide some insights into this emerging and rapidly growing research area.
Highly-ordered assembled organic fluorescent materials for high-resolution bio-sensing: a review
Authors: Wang Zheng , Chen Zilong , Zhang Zhenhao , Wang Hongzhen , Zhang Haichang
Published: February 2024

Organic fluorescent materials (OFMs) play a crucial role in the development of biosensors, enabling the extraction of biochemical information within cells and organisms, extending to the human body.
Influence of electronic correlation on the valley and topological properties of VSiGeP4 monolayer
Authors: Fan Guangxin , Wu Yanzhao , Tong Junwei , Deng Li , Yin Xiang , Tian Fubo , Zhang Xianmin
Published: February 2024

A topological phase transition occurs when the U value is changed, showing VSiGeP4 could be used for information encoding and storage.
Synthesis of axially chiral diaryl ethers via NHC-catalyzed atroposelective esterification
Authors: Wu Yingtao , Guan Xin , Zhao Huaqiu , Li Mingrui , Liang Tianlong , Sun Jiaqiong , Zheng Guangfan , Zhang Qian
Published: February 2024

We present NHC-catalyzed atroposelective esterification of prochiral dialdehydes, delivering enantioenriched axially chiral diaryl ethers. Matched kinetic resolutions amplify the enantioselectivity by removing minor enantiomers via over-functionalization.
Flexible and rigid spinel ferrite carboneous composite as a future of tunable absorption dominant cmWave shielding materials
Authors: Khade Vaishnavi , Thirumalasetty Avanish Babu , Rathod Asmita Ajay , Chaoukiker Yogesh Kumar , Wuppulluri Madhuri
Published: February 2024

In this article, we compare the EMI shielding performance of rigid and flexible composites of cobalt nickel ferrite.
Making Gd2O3 nanofibers flexible by grain-boundary toughening
Authors: Xu Li , Zhou Wenqian , Huang Liqian , Yu Jianyong , Si Yang , Ding Bin
Published: February 2024

Flexible Gd2O3 nanofibers with fine grains were prepared by sol–gel electrospinning and grain boundary strengthening.
Additive-assisted synthesis of α-Kdo glycosides with peracetylated glycosyl ynenoate as a donor
Authors: Miao He , Lu Siqian , Chen Hongyu , Shang Jintao , Zheng Jibin , Yang You
Published: February 2024

Additive-assisted α-selective Kdo glycosylation using a peracetylated Kdo ynenoate is described for stereoselective synthesis of the protected trisaccharide variant relevant to the lipopolysaccharide of Coxiella burnetii strain Nine Mile.
Chiral lanthanide hexaazamacrocycles for circularly polarized luminescence, high relaxivity and magnetic resonance imaging
Authors: Tang Yuxin , Jian Minghong , Tang Baobing , Zhu Zhenhua , Wang Zhenxin , Liu Yunling
Published: February 2024

Mononuclear chiral lanthanide hexaazamacrocycles afford brilliant luminescence, strong CPL, high relaxivity and efficient MRI.
Cancer Vaccines Designed Based the Nanoparticle and Tumor Cells for the Treatment of Tumors: A Perspective
Authors: Wu Qing-Juan , Lv Wen-Liang
Published: February 2024

Cancer vaccines based on tumor cell components have shown promising results in animal and clinical studies. The vaccine system contains abundant tumor antigen components, which can activate the immune system by antigens. However, their efficacy has been limited by the inability of antigens delivery, which are the core components of vaccines, further fail to be presented and activation of effective cells. Nanotechnology offers a novel platform to enhance the immunogenicity of tumor‐associated antigens and deliver them to antigen‐presenting cells (APCs) more efficiently. In addition, nanotreatment of tumor cells derivate active ingredients could also help improve the effectiveness of cancer vaccines. In this review, we summarize recent advances in the development of cancer vaccines by the combination of nanotechnology and tumor‐based ingredients, including liposomes, polymeric nanoparticles, metallic nanoparticles, virus‐like particles and tumor cells membrane, tumor lysate, and specific tumor antigens. These nanovaccines have been designed to increase antigen uptake, prolong antigen presentation, and modulate immune responses through codelivery of immunostimulatory agents. We also further discuss challenges and opportunities in the clinical translation of these nanovaccines.