bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Deposition Techniques and Supramolecular Arrangement in Thin Films for Sensor Applications
Authors: Miyazaki Celina M. , Martin Cibely S. , Ozório Maíza S. , Kavazoi Henry S. , Constantino Carlos J. L. , Aléssio Priscila
Published: October 2023

In recent decades, many research efforts have been dedicated to finding highly sensitive devices for fast and reliable identification and quantification of an expanding range of analytes. As a result, there has been an increased number of publications dedicated to this area and a consequent increase in the number of review papers on the subject. However, unlike most review articles, we chose to explore the impact of supramolecular arrangement (or deeper, when possible, approaching the molecular organization) and assembly variables on sensing performance. This review briefly discusses the methods used to determine the molecular organization of thin films. We also examine various deposition techniques, including Langmuir-Blodgett, Langmuir-Schaefer, Layer-by-Layer assembly, electrodeposition, and spray pyrolysis, describing mainly (but not limited to) the advances in the last five years in developing thin films for sensors, with a particular emphasis on how the supramolecular arrangement can influence the sensing properties of these films.
Preparation and Optimization of Mesoporous SnO2 Quantum Dot Thin Film Gas Sensors for H2S Detection Using XGBoost Parameter Importance Analysis
Authors: Liu Jianqiao , Wang Yujia , Sun Yue , Zhang Kuanguang , Ding Yang , Fu Ce , Wang Junsheng
Published: October 2023

Tin oxide (SnO2) is a traditional gas-sensitive semiconductor with excellent response to various gases. However, its sensor performances are attenuated by the utility factor during gas diffusion in the sensing body. Therefore, the rational design of microstructure of devices is attractive and necessary because it may provide a sensible and controllable microstructure, which facilitates gas diffusion and inhibits the utility factor. Herein, the mesoporous tin oxide (MPTD) quantum dot thin film for H2S gas sensors is prepared by a facile route, which creates a mesoporous microstructure for thin films by the thermal decomposition of NH4Cl. The pore size of the thin films is controlled to be 19.36–40.13 nm. The mesoporous microstructure exhibits enhanced gas-sensing properties amounting to a 30-fold increase in response and 1/3 reduction in recovery time in H2S detection at room temperature (25 °C), with a limit of detection of 0.4 ppm. To determine the importance of sensor parameters such as pore size, film thickness, and grain size, an eXtreme Gradient Boosting (XGBoost) algorithm model was developed to examine the feature importance of each parameter on the gas-sensing performance of the MPTD sensors. The visual illustration of parameter importance is revealed to facilitate the optimization of technical preparation parameters as well as the rational design of semiconductor gas sensors.
Efficacy of Infrared Vein Visualization versus Standard Technique for Peripheral Venous Cannulation in Infant and Toddler Populations: A Randomized Study
Authors: Fehr Graham , Rigali Marisa , Weller Gregory , Grap Shannon M. , Coleman Melissa , Parekh Uma , Chinchilli Vernon M. , Dalal Priti G.
Published: October 2023

Establishing intravenous (IV) access in younger patient populations via the traditional cannulation technique for procedures requiring anesthesia is often challenging. Infrared (IR) vein visualization is a modality that aids venous cannulation; however, few reports of this technique exist in the infant and toddler population. The primary aim of this study was to compare the efficacy of IR vein visualization to the standard cannulation technique for obtaining peripheral IV access in infant and toddler populations. Following Institutional Review Board (IRB) approval and written informed consent, children were randomly assigned to either a standard cannulation technique group or an IR vein visualization device group for venous cannulation. The primary outcome variable was the success rate of IV cannulation, and the secondary variables were the total number of attempts and the time to successful cannulation. No difference was noted between either group for first-attempt success rate (standard versus IR: 61.25% vs. 54.4%; p = 0.4) or time to establish IV cannulation (standard versus IR: median [interquartile range], 40 s [24–120] vs. 53 s [26–106]; p = 0.55). The anesthesiologist’s grading of the anticipated difficulty of IV cannulation was a significant predictor of cannulation success (p = 0.0016). Our study demonstrated no significant benefit in utilizing the IR vein visualization device in terms of the overall success rate, number of attempts, and time to establish successful IV cannulation when compared to the standard technique. However, in difficult IV access situations, this device proved to be a valuable rescue adjunct.
Position-Dependent Effective Mass and Asymmetry Effects on the Electronic and Optical Properties of Quantum Wells with Improved Rosen–Morse Potential
Authors: Kasapoglu Esin , Yücel Melike Behiye , Duque Carlos A.
Published: October 2023

In this study, we investigated, for the first time, the effects of the spatially varying effective mass, asymmetry parameter, and well width on the electronic and optical properties of a quantum well which has an improved Rosen–Morse potential. Calculations were made within the framework of the effective mass and parabolic band approximations. We have used the diagonalization method by choosing a wave function based on the trigonometric orthonormal functions to find eigenvalues and eigenfunctions of the electron confined within the improved Rosen–Morse potential. Our results show that the position dependence mass, asymmetry, and confinement parameters cause significant changes in the electronic and optical properties of the structure we focus on since these effects create a significant increase in electron energies and a blue shift in the absorption spectrum. The increase in energy levels enables the development of optoelectronic devices that can operate at wider wavelengths and absorb higher-energy photons. Through an appropriate choice of parameters, the Rosen–Morse potential offers, among many advantages, the possibility of simulating heterostructures close to surfaces exposed to air or vacuum, thus giving the possibility of substantially enriching the allowed optical transitions given the breaking of the system´s symmetries. Similarly, the one-dimensional Rosen–Morse potential model proposed here can be extended to one- and zero-dimensional structures such as core/shell quantum well wires and quantum dots. This offers potential advancements in fields such as optical communication, imaging technology, and solar cells.
Spectroscopy Characteristics and Color-Influencing Factors of Green Iron-Bearing Elbaite
Authors: Cui Lianyi , Guo Ying , Tang Jun , Yang Yushu
Published: October 2023

The color-influencing factors and spectroscopy of 22 green elbaite samples were investigated using X-Rite SP62 spectrophotometry, ultraviolet–visible (UV–Vis) spectroscopy, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), and infrared spectroscopy. The chromogenic components iron and manganese were found in the green elbaites; however, the bivariate correlation analysis indicated that the Mn content had no impact on the color, whereas the Fe content significantly affected both the lightness and the hue of green elbaites. The primary factors influencing the color of tourmaline were the absorption band at 720 nm caused by the Fe2+ d-d transitions and the 300 to 400 nm wide absorption edge extending to the visible range due to the O2−-Fe3+ charge transfer. Infrared spectroscopy indicated that the color of tourmalines was also influenced by their structure. As the degree of Y and Z octahedral distortion in the tourmaline lattice increased, the lightness of the tourmaline decreased and its color deepened. The hydroxyl region of the infrared spectra of green elbaite showed three distinct peak positions representing two types of hydroxyl vibrations: O1H at the W position and O3H at the V position. The O1H vibrations are attributed to YLiYAlYAl and XNa or X position vacancy, while the O3H vibrations are assigned to ZAlZAlYAl and ZAlZAlYLi. The presence of three peaks in the hydroxyl vibrational region of the IR spectra indicated that these samples were iron-bearing elbaites.
Innovative Imaging Techniques: Nice to Have or Essential to Treat Complex Diseases?
Authors: de Vries Jean-Paul P. M.
Published: October 2023

Nowadays, a substantial number of our patients have multimorbidity, and need treatment for complex diseases [...]
Establishing and Validating a Morphological Prediction Model Based on CTA to Evaluate the Incidence of Type-B Dissection
Authors: Fu Yan , Huang Siyi , Zhao Deyin , Qiu Peng , Hu Jiateng , Liu Xiaobing , Lu Xinwu , Feng Lvfan , Hu Min , Cheng Yong
Published: October 2023

Background: Many patients with Type B aortic dissection (TBAD) may not show noticeable symptoms until they become intervention and help prevent critically ill, which can result in fatal outcomes. Thus, it is crucial to screen people at high risk of TBAD and initiate the necessary preventive and therapeutic measures before irreversible harm occurs. By developing a prediction model for aortic arch morphology, it is possible to accurately identify those at high risk and take prompt action to prevent the adverse consequences of TBAD. This approach can facilitate timely the development of serious illnesses. Method: The predictive model was established in a primary population consisting of 173 patients diagnosed with acute Stanford TBAD, with data collected from January 2017 and December 2018, as well as 534 patients with healthy aortas, with data collected from April 2018 and December 2018. Explicitly, the data were randomly separated into the derivation set and validation set in a 7:3 ratio. Geometric and anatomical features were extracted from a three-dimensional multiplanar reconstruction of the aortic arch. The LASSO regression model was utilized to minimize the data dimension and choose relevant features. Multivariable logistic regression analysis and backward stepwise selection were employed for predictive model generation, combining demographic and clinical features as well as geometric and anatomical features. The predictive model’s performance was evaluated by examining its calibration, discrimination, and clinical benefit. Finally, we also conducted internal verification. Results: After applying LASSO logistic regression and backward stepwise selection, 12 features were entered into the prediction model. Age, aortic arch angle, total thoracic aorta distance, ascending aorta tortuosity, aortic arch tortuosity, distal descending aorta tortuosity, and type III arch were protective factors, while male sex, hypertension, aortic arch height, and aortic arch distance were risk factors. The model exhibited satisfactory discrimination (AUC, 0.917 [95% CI, 0.890–0.945]) and good calibration in the derivation set. Applying the predictive model to the validation set also provided satisfactory discrimination (AUC, 0.909 [95% CI, 0.864–0.953]) and good calibration. The TBAD nomogram for clinical use was established. Conclusions: This study demonstrates that a multivariable logistic regression model can be used to predict TBAD patients.
A Bayesian Inference Based Computational Tool for Parametric and Nonparametric Medical Diagnosis
Authors: Chatzimichail Theodora , Hatjimihail Aristides T.
Published: October 2023

Medical diagnosis is the basis for treatment and management decisions in healthcare. Conventional methods for medical diagnosis commonly use established clinical criteria and fixed numerical thresholds. The limitations of such an approach may result in a failure to capture the intricate relations between diagnostic tests and the varying prevalence of diseases. To explore this further, we have developed a freely available specialized computational tool that employs Bayesian inference to calculate the posterior probability of disease diagnosis. This novel software comprises of three distinct modules, each designed to allow users to define and compare parametric and nonparametric distributions effectively. The tool is equipped to analyze datasets generated from two separate diagnostic tests, each performed on both diseased and nondiseased populations. We demonstrate the utility of this software by analyzing fasting plasma glucose, and glycated hemoglobin A1c data from the National Health and Nutrition Examination Survey. Our results are validated using the oral glucose tolerance test as a reference standard, and we explore both parametric and nonparametric distribution models for the Bayesian diagnosis of diabetes mellitus.
Dynamic Offloading in Flying Fog Computing: Optimizing IoT Network Performance with Mobile Drones
Authors: Min Wei , Khakimov Abdukodir , Ateya Abdelhamied A. , ElAffendi Mohammed , Muthanna Ammar , Abd El-Latif Ahmed A. , Muthanna Mohammed Saleh Ali
Published: October 2023

The rapid growth of Internet of Things (IoT) devices and the increasing need for low-latency and high-throughput applications have led to the introduction of distributed edge computing. Flying fog computing is a promising solution that can be used to assist IoT networks. It leverages drones with computing capabilities (e.g., fog nodes), enabling data processing and storage closer to the network edge. This introduces various benefits to IoT networks compared to deploying traditional static edge computing paradigms, including coverage improvement, enabling dense deployment, and increasing availability and reliability. However, drones’ dynamic and mobile nature poses significant challenges in task offloading decisions to optimize resource utilization and overall network performance. This work presents a novel offloading model based on dynamic programming explicitly tailored for flying fog-based IoT networks. The proposed algorithm aims to intelligently determine the optimal task assignment strategy by considering the mobility patterns of drones, the computational capacity of fog nodes, the communication constraints of the IoT devices, and the latency requirements. Extensive simulations and experiments were conducted to test the proposed approach. Our results revealed significant improvements in latency, availability, and the cost of resources.
Deep Learning–Based Segmentation of Trypanosoma cruzi Nests in Histopathological Images
Authors: Hevia-Montiel Nidiyare , Haro Paulina , Guillermo-Cordero Leonardo , Perez-Gonzalez Jorge
Published: October 2023

The use of artificial intelligence has shown good performance in the medical imaging area, in particular the deep learning methods based on convolutional neural networks for classification, detection, and/or segmentation tasks. The task addressed in this research work is the segmentation of amastigote nests from histological microphotographs in the study of Trypanosoma cruzi infection (Chagas disease) implementing a U-Net convolutional network architecture. For the nests’ segmentation, a U-Net architecture was trained on histological images of an acute-stage murine experimental model performing a 5-fold cross-validation, while the final tests were carried out with data unseen by the U-Net from three image groups of different experimental models. During the training stage, the obtained results showed an average accuracy of 98.19 ± 0.01, while in the case of the final tests, an average accuracy of 99.9 ± 0.1 was obtained for the control group, as well as 98.8 ± 0.9 and 99.1 ± 0.8 for two infected groups; in all cases, high sensitivity and specificity were observed in the results. We can conclude that the use of a U-Net architecture proves to be a relevant tool in supporting the diagnosis and analysis of histological images for the study of Chagas disease.
Deep Learning of Sensor Data in Cybersecurity of Robotic Systems: Overview and Case Study Results
Authors: Szynkiewicz Wojciech , Niewiadomska-Szynkiewicz Ewa , Lis Kamila
Published: October 2023

Recent technological advances have enabled the development of sophisticated robotic and sensor systems monitored and controlled by algorithms based on computational intelligence. The deeply intertwined and cooperating devices connected to the Internet and local networks, usually through wireless communication, are increasingly used in systems deployed among people in public spaces. The challenge is to ensure that physical and digital components work together securely, especially as the impact of cyberattacks is significantly increasing. The paper addresses cybersecurity issues of mobile service robots with distributed control architectures. The focus is on automatically detecting anomalous behaviors possibly caused by cyberattacks on onboard and external sensors measuring the robot and environmental parameters. We provide an overview of the methods and techniques for protecting robotic systems. Particular attention is paid to our technique for anomaly detection in a service robot’s operation based on sensor readings and deep recurrent neural networks, assuming that attacks result in the robot behaving inconsistently. The paper presents the architecture of two artificial neural networks, their parameters, and attributes based on which the potential attacks are identified. The solution was validated on the PAL Robotics TIAGo robot operating in the laboratory and replicating a home environment. The results confirm that the proposed system can effectively support the detection of computer threats affecting the sensors’ measurements and, consequently, the functioning of a service robotic system.
Improving OSAHS Prevention Based on Multidimensional Feature Analysis of Snoring
Authors: Fang Yu , Liu Dongbo , Zhao Sixian , Deng Daishen
Published: October 2023

Obstructive Sleep Apnea–Hypopnea Syndrome (OSAHS), a severe respiratory sleep disorder, presents a significant threat to human health and even endangers life. As snoring is the most noticeable symptom of OSAHS, identifying OSAHS via snoring sound analysis is vital. This study aims to analyze the time-domain and frequency-domain characteristics of snoring sounds to detect OSAHS and its severity. The snoring sounds are extracted and scrutinized from nighttime acoustic signals, with spectral energy ratio features being applied, calculated via the snore detection frequency division method. A variety of time and frequency-domain features are derived from the snoring sounds. A novel Snore Detection Cepstral Coefficient (SDCC) is proposed, based on Mel Frequency Cepstral Coefficients (MFCCs) and snore detection frequency division. Relief-F feature screening is then applied to SDCC and MFCC. Canonical Correlation Analysis (CCA) is utilized on the fusion features obtained as a result, and the results indicate the highest accuracy (97.8%) with Subspace KNN. The optimal classifier with feature combination is used for the snore model of OSASH early warnings all night, effectively recognizing and assessing OSAHS and reflecting the severity of its disease. This result, achieving high accuracy and low computational complexity, shows that the proposed method holds significant promise for developing portable sleep health detection devices.
Variation in the Physiological Condition of Common Coral Trout (Plectropomus leopardus) Unrelated to Coral Cover on the Great Barrier Reef, Australia
Authors: Pratchett Morgan S. , Caballes Ciemon F. , Hobbs Jean-Paul A. , DiBattista Joseph D. , Bergseth Brock , Waldie Peter , Champion Curtis , Mc Cormack Samuel P. , Hoey Andrew S.
Published: October 2023

There are a wide variety of fishes that occur exclusively on coral reefs, though it is unclear to what extent these species (especially larger-bodied fisheries target species) are reliant on the specific reef habitat provided by corals. This study explored variation in the physiological condition of common coral trout (Plecropomus leopardus) on Australia’s Great Barrier Reef, explicitly testing whether fish condition varied with local coral cover in the aftermath of severe mass bleaching and coral loss. Both the physiological condition (specifically, the length–weight relationships, hepatocyte vacuolation, and electrical phase angle) of P. leopardus and the live cover of habitat-forming corals varied greatly among the sites considered in this study, but there was little correspondence between these factors. Fish condition was largely influenced by fish size and varied with latitude. While there was no apparent effect of recent coral bleaching and coral loss on the physiological condition of P. leopardus, this does not mean that these key fisheries species will be unaffected by further changes to the environmental conditions and reef habitat. It is important, therefore, that fisheries managers remain vigilant to apparent effects of climate change and other anthropogenic pressures on fisheries stocks.
Design and Characterization of Citronella Oil-Loaded Micro-Emulgel for the Treatment of Candida Albicans Infection
Authors: Singh Shambhvi , Chauhan Shikha Baghel , Gupta Charu , Singh Indu , Gupta Annie , Sharma Shwetakshi , Kawish S. M. , Rahman Shakilur , Iqbal Muzaffar
Published: October 2023

The purpose of the current study was to prepare and evaluate a citronella oil-loaded microemulsion-based micro-emulgel for the treatment of Candida albicans. The primary objective was to use the skin to transfer hydrophobic medications into the bloodstream. The formulation included cinnamon oil as an antifungal oil and citronella oil as an active pharmaceutical ingredient, respectively. Tween 80 and PEG 200 were used as the surfactant and co-surfactant, respectively, to create phase diagrams. Carbopol 940, one of the frequently used polymers, was investigated for its ability to prepare gel formulations. The optimized (F3) batch contained the highest percentage (87.05 ± 0.03%) of drug content and, according to the statistics provided, had the highest drug release rate of around 87.05% within 4 h. The Korsmeyer–Peppas model with n value of 0.82, which is in the range 0.5–1, had the highest r2 value, indicating that release following non-Fickian/anomalous diffusion provided a better dimension for all of the formulations. The optimized (F3) formulation had stronger antifungal activity in comparison to other formulations. This leads to the conclusion that citronella oil can be made into a micro-emulgel, which may improve its release in aqueous systems while maintaining a high level of drug release at the target site.
Large-Scale Automatic Identification of Industrial Vacant Land
Authors: Sun Yihao , Hu Han , Han Yawen , Wang Ziyan , Zheng Xiaodi
Published: October 2023

Many cities worldwide have large amounts of industrial vacant land (IVL) due to development and transformation, posing a growing problem. However, the large-scale identification of IVL is hindered by obstacles such as high cost, high variability, and closed-source data. Moreover, it is difficult to distinguish industrial vacant land from operational industrial land based solely upon image features. To address these issues, we propose a method for the large-scale automatic identification of IVL. The framework uses deep learning to train remote-sensing images of potential industrial vacant land to generate a semantic segmentation model and further use population density and surface temperature data to filter model predictions. The feasibility of the proposed methodology was validated through a case study in Tangshan City, Hebei Province, China. The study indicates two major conclusions: (1) The proposed IVL identification framework can efficiently generate industrial vacant land mapping. (2) HRNet exhibits the highest accuracy and strongest robustness after training compared with other semantic segmentation backbone networks, ensuring high-quality performance and stability, as evidenced by a model accuracy of 97.84%. Based on the above advantages, the identification framework provides a reference method for various countries and regions to identify industrial vacant land on a large scale, which is of great significance for advancing the research and transformation of industrial vacant land worldwide.
Platelets as Potential Non-Traditional Cardiovascular Risk Factor—Analysis Performed in Healthy Donors
Authors: Szymańska Patrycja , Luzak Bogusława , Siarkiewicz Przemysław , Golański Jacek
Published: October 2023

Abnormal lipid profile, increased glucose level, and elevated body weight are traditional cardiometabolic risk factors; however, the role of platelets in the development of cardiovascular disease (CVD) is increasingly being highlighted. The aim of this study was to select platelet-related parameters (non-genetic molecular and routine laboratory measurements) that may be associated with increased cardiovascular risk among healthy populations. We evaluated the level of platelet indices, platelet-based inflammatory markers, platelet reactivity parameters, and platelet reactive oxygen species (ROS) generation in relation to selected cardiometabolic risk factors. We noted the association between total cholesterol and LDL cholesterol with platelet aggregation and platelet ROS generation. We found the relationship between triglycerides, glucose, and body mass index with the relatively new multi-inflammatory indices (MII-1 and MII-3). Moreover, we noticed that the mean platelet volume-to-lymphocyte ratio in healthy subjects is not a good source of information about platelets and inflammation. We also highlighted that platelet-to-HDL-cholesterol ratio may be a promising prognostic cardiometabolic indicator. The association between platelet-related (especially molecular) and cardiometabolic parameters requires further research. However, the goal of this study was to shed light on the consideration of platelets as a non-traditional cardiovascular risk factor and a crucial element in identifying individuals at high-risk of developing CVD in the future.
Age-Dependent Sex Differences in Perineuronal Nets in an APP Mouse Model of Alzheimer’s Disease Are Brain Region-Specific
Authors: Rahmani Rayane , Rambarack Naiomi , Singh Jaijeet , Constanti Andrew , Ali Afia B.
Published: October 2023

Alzheimer’s disease (AD) is the most common form of dementia, which disproportionately affects women. AD symptoms include progressive memory loss associated with amyloid-β (Aβ) plaques and dismantled synaptic mechanisms. Perineuronal nets (PNNs) are important components of the extracellular matrix with a critical role in synaptic stabilisation and have been shown to be influenced by microglia, which enter an activated state during AD. This study aimed to investigate whether sex differences affected the density of PNNs alongside the labelling of microglia and Aβ plaques density.We performed neurochemistry experiments using acute brain slices from both sexes of the APPNL-F/NL-F mouse model of AD, aged-matched (2–5 and 12–16 months) to wild-type mice, combined with a weighted gene co-expression network analysis (WGCNA). The lateral entorhinal cortex (LEC) and hippocampal CA1, which are vulnerable during early AD pathology, were investigated and compared to the presubiculum (PRS), a region unscathed by AD pathology. The highest density of PNNs was found in the LEC and PRS regions of aged APPNL-F/NL-F mice with a region-specific sex differences. Analysis of the CA1 region using multiplex-fluorescent images from aged APPNL-F/NL-F mice showed regions of dense Aβ plaques near clusters of CD68, indicative of activated microglia and PNNs. This was consistent with the results of WGCNA performed on normalised data on microglial cells isolated from age-matched, late-stage male and female wild-type and APP knock-in mice, which revealed one microglial module that showed differential expression associated with tissue, age, genotype, and sex, which showed enrichment for fc-receptor-mediated phagocytosis. Our data are consistent with the hypothesis that sex-related differences contribute to a disrupted interaction between PNNs and microglia in specific brain regions associated with AD pathogenesis.
Hepatic-Specific FGF21 Knockout Abrogates Ovariectomy-Induced Obesity by Reversing Corticosterone Production
Authors: Xu Jiayu , Shao Xinyu , Zeng Haozhe , Wang Chengxi , Li Jiayi , Peng Xiaoqin , Zhuo Yong , Hua Lun , Meng Fengyan , Han Xingfa
Published: October 2023

Increased glucocorticoid (GC) levels act as a master contributor to central obesity in estrogen-depleted females; however, what factors cause their increased GC production is unclear. Given (1) liver fibroblast growth factor 21 (FGF21) and GCs regulate each other’s production in a feed-forward loop, and (2) circulating FGF21 and GCs are parallelly increased in menopausal women and ovariectomized mice, we thus hypothesized that elevation of hepatic FGF21 secretion causes increased GGs production in estrogen-depleted females. Using the ovariectomized mice as a model for menopausal women, we found that ovariectomy (OVX) increased circulating corticosterone levels, which in turn increased visceral adipose Hsd11b1 expression, thus causing visceral obesity in females. In contrast, liver-specific FGF21 knockout (FGF21 LKO) completely reversed OVX-induced high GCs and high visceral adipose Hsd11b1 expression, thus abrogating OVX-induced obesity in females. Even though FGF21 LKO failed to rescue OVX-induced dyslipidemia, hepatic steatosis, and insulin resistance. What’s worse, FGF21 LKO even further exacerbated whole-body glucose metabolic dysfunction as evidenced by more impaired glucose and pyruvate tolerance and worsened insulin resistance. Mechanically, we found that FGF21 LKO reduced circulating insulin levels, thus causing the dissociation between decreased central obesity and the improvement of obesity-related metabolic syndromes in OVX mice. Collectively, our results suggest that liver FGF21 plays an essential role in mediating OVX-induced central obesity by promoting GC production. However, lack of liver FGF21 signaling reduces insulin production and in turn causes the dissociation between decreased central obesity and the improvement of obesity-related metabolic syndromes, highlighting a detrimental role for hepatic FGF21 signals in mediating the development of central obesity but a beneficial role in preventing metabolic abnormality from further exacerbation in estrogen-depleted females.
Epicardial Adipose Tissue and Atrial Fibrillation Recurrence following Catheter Ablation: A Systematic Review and Meta-Analysis
Authors: Anagnostopoulos Ioannis , Kousta Maria , Kossyvakis Charalampos , Paraskevaidis Nikolaos Taxiarchis , Vrachatis Dimitrios , Deftereos Spyridon , Giannopoulos Georgios
Published: October 2023

(1)Introduction: Catheter ablation has become a cornerstone for the management of patients with atrial fibrillation (AF). Nevertheless, recurrence rates remain high. Epicardial adipose tissue (EAT) has been associated with AF pathogenesis and maintenance. However, the literature has provided equivocal results regarding the relationship between EAT and post-ablation recurrence.(2) Purpose: to investigate the relationship between total and peri-left atrium (peri-LA) EAT with post-ablation AF recurrence. (3) Methods: major electronic databases were searched for articles assessing the relationship between EAT, quantified using computed tomography, and the recurrence of AF following catheter ablation procedures. (4) Results: Twelve studies (2179 patients) assessed total EAT and another twelve (2879 patients) peri-LA EAT. Almost 60% of the included patients had paroxysmal AF and recurrence was documented in 34%. Those who maintained sinus rhythm had a significantly lower volume of peri-LA EAT (SMD: −0.37, 95%; CI: −0.58–0.16, I2: 68%). On the contrary, no significant difference was documented for total EAT (SMD: −0.32, 95%; CI: −0.65–0.01; I2: 92%). No differences were revealed between radiofrequency and cryoenergy pulmonary venous isolation. No publication bias was identified. (5) Conclusions: Only peri-LA EAT seems to be predictive of post-ablation AF recurrence. These findings may reflect different pathophysiological roles of EAT depending on its location. Whether peri-LA EAT can be used as a predictor and target to prevent recurrence is a matter of further research.
Challenges and Strategies for Enhancing eHealth Capacity Building Programs in African Nations
Authors: Asah Flora Nah , Kaasbøll Jens Johan
Published: October 2023

eHealth applications play a crucial role in achieving Universal Health Coverage. (1) Background: To ensure successful integration and use, particularly in developing and low/middle-income countries (LMIC), it is vital to have skilled healthcare personnel. The purpose of this study was to describe challenges that hinder capacity-building initiatives among healthcare personnel in developing and LMIC and suggest interventions to mitigate them. (2) Methods: Adopted a descriptive research design and gathered empirical data through an online survey from 37 organizations. (3) Results: The study found that in developing and LMIC, policymakers and eHealth specialists face numerous obstacles integrating and using eHealth including limited training opportunities. These obstacles include insufficient funds, inadequate infrastructure, poor leadership, and governance, which are specific to each context. The study suggests implementing continuous in-service training, computer-based systems, and academic modules to address these challenges. Additionally, the importance of having solid and appropriate eHealth policies and committed leaders were emphasized. (4) Conclusions: These findings are consistent with previous research and highlight the need for practical interventions to enhance eHealth capacity-building in LMICs. However, it should be noted that the data was collected only from BETTEReHEALTH partners. Therefore, the results only represent their respective organizations and cannot be generalized to the larger population.
Ethnicity, Age, and Gender Differences in Glycated Hemoglobin (HbA1c) Levels among Adults in Northern and Eastern Sudan: A Community-Based Cross-Sectional Study
Authors: Ahmed Sumia F. , Hassan Ahmed A. , Eltayeb Majdolin M. , Omar Saeed M. , Adam Ishag
Published: October 2023

Background: The level of association between glycated hemoglobin (HbA1c) level and ethnicity, age, and gender is not yet settled. This study aimed to investigate the association between ethnicity, age, and gender and HbA1c level among adults who were known not to have diabetes mellitus in northern and eastern Sudan. Methods: A comparative community-based cross-sectional study was conducted. Sociodemographic and clinical characteristics data were collected. HbA1c levels were measured, and multiple linear regression analysis was performed. Results: A total of 898 adults (363 in northern Sudan and 535 in eastern Sudan) were included; 349 (38.9%) were males. The HbA1c level was significantly higher in eastern Sudan, and there was no significant difference in HbA1c levels between genders. In multiple linear regression, for adults with HbA1c <6.5%, ethnicity and BMI were associated with HbA1c, but age and gender were not associated with HbA1c. In northern Sudan, age was positively associated with HbA1c, and there was no association between gender, BMI, and HbA1c in adults with HbA1c <6.5%. In eastern Sudan, BMI was positively associated with HbA1c, and there was no significant association between age and gender and HbA1c level in adults with HbA1c <6.5%. Conclusion: HbA1c levels are influenced by ethnicity and age but not by gender.
A Novel Meta-Analysis-Based Regularized Orthogonal Matching Pursuit Algorithm to Predict Lung Cancer with Selected Biomarkers
Authors: Wang Sai , Wang Bin-Yuan , Li Hai-Fang
Published: October 2023

Biomarker selection for predictive analytics encounters the problem of identifying a minimal-size subset of genes that is maximally predictive of an outcome of interest. For lung cancer gene expression datasets, it is a great challenge to handle the characteristics of small sample size, high dimensionality, high noise as well as the low reproducibility of important biomarkers in different studies. In this paper, our proposed meta-analysis-based regularized orthogonal matching pursuit (MA-ROMP) algorithm not only gains strength by using multiple datasets to identify important genomic biomarkers efficiently, but also keeps the selection flexible among datasets to take into account data heterogeneity through a hierarchical decomposition on regression coefficients. For a case study of lung cancer, we downloaded GSE10072, GSE19188 and GSE19804 from the GEO database with inconsistent experimental conditions, sample preparation methods, different study groups, etc. Compared with state-of-the-art methods, our method shows the highest accuracy, of up to 95.63%, with the best discriminative ability (AUC 0.9756) as well as a more than 15-fold decrease in its training time. The experimental results on both simulated data and several lung cancer gene expression datasets demonstrate that MA-ROMP is a more effective tool for biomarker selection and learning cancer prediction.
Intervention Effects of Physical Activity on Type 2 Diabetic Patients Potentially Infected with COVID-19
Authors: Yu Lihua , Guo Sainyu , Ji Wen , Sun Hailian , Lee Seongno , Zhang Deju
Published: October 2023

The coronavirus disease 2019 (COVID-19) pandemic has clearly had a great influence on the lifestyles of the population, especially on patients with type 2 diabetes mellitus. During the COVID-19 outbreak, many countries/regions implemented social-isolation measures, leading to an increase in negative behaviors and impairing the capability of diabetic patients to resist COVID-19, ultimately causing severe prognoses. Moreover, as the epidemic progressed, multiple studies emphasized the significance of physical exercise in the management of type 2 diabetic patients infected with COVID-19. In this study, we selected research from 1 December 2019 to 9 August 2023 that focused on COVID-19-infected diabetic patients to investigate the impact of type 2 diabetes on the immune functions, inflammation factor levels, lung injuries, and mental disorders of such patients, as well as to assess the risk of novel coronavirus pneumonia in these patients. Additionally, the effects of high-intensity, moderate-intensity, and low-intensity exercises on novel coronavirus pneumonia infection in type 2 diabetic patients and the mechanisms of the effects of such exercise were considered. We concluded that elderly diabetic patients with COVID-19 should perform low-intensity exercises to facilitate their recoveries. This study offers guidance for a proper understanding of the dangers of diabetes and the use of appropriate measures to reduce the risk of novel coronavirus pneumonia infections in type 2 diabetic patients.
Influence of Sulfate-Reducing Bacteria on Corrosion Behavior of EQ70 High-Strength Steel
Authors: Song Yanyan , Shi Hongwei , Nwokolo Izuchukwu K. , Wu Bin , Gao Shitian , Cheng Huize , Wang Jun
Published: October 2023

This work examines corrosion behavior of EQ70 high-strength steel under anaerobic conditions in artificial seawater containing sulfate-reducing bacteria (SRB). Polarization and electrochemical impedance spectra (EIS) tests were conducted. The results reveal that corrosion rate initially decreased at the beginning of immersion. However, as the immersion time progressed, the corrosion rate of the high-strength steel increased, attributed to SRB reproduction. The scanning electron microscopy (SEM) results demonstrate that the corrosion was more severe in artificial seawater containing SRB compared to that of seawater without SRB. The morphologies of confocal laser scanning microscopy (CLSM) demonstrate that, after 15 days of immersion, the average depth of the corrosion pits on the sample in the artificial seawater containing SRB was nearly double that of the sample in the SRB-free seawater.
Preparation of Elastic Macroporous Graphene Aerogel Based on Pickering Emulsion Method and Combination with ETPU for High Performance Piezoresistive Sensors
Authors: Zhao Wei , Chen Hao , Wang Yuqi , Zhuo Qing , Liu Yaopeng , Li Yuanyuan , Dong Hangyu , Li Shidong , Tan Linli , Tan Jianfeng , Liu Zhuo , Li Yingru
Published: October 2023

High-performance pressure sensors provide the necessary conditions for smart shoe applications. In this paper, the elastic Macroporous Graphene Aerogel (MGA) was synthesized via the modified Hummers’ method, and it was further combined with Expanded-Thermoplastic polyurethane (ETPU) particles to assemble MGA-ETPU flexible sensors. The MGA-ETPU has a low apparent density (3.02 mg/cm3), high conductivity (0.024 S/cm) and fast response time (50 ms). The MGA-ETPU has a large linear sensing range (0–10 kPa) and consists of two linear regions: the low-pressure region (0 to 8 kPa) and the high-pressure region (8 to 10 kPa), with sensitivities of 0.08 kPa−1, and 0.246 kPa−1, respectively. Mechanical test results show that the MGA-ETPU sensor showed 19% reduction in maximum stress after 400 loading–unloading compression cycles at 40% strain. Electrical performance tests showed that the resistance of MGA-ETPU sensor decreased by 12.5% when subjected to sudden compression at 82% strain and returned to its original state within 0.05 s. Compared to existing flexible sensors, the MGA-ETPU sensors offer excellent performance and several distinct advantages, including ease of fabrication, high sensitivity, fast response time, and good flexibility. These remarkable features make them ideally suited as flexible pressure sensors for smart shoes.
Clostridioides difficile from Fecally Contaminated Environmental Sources: Resistance and Genetic Relatedness from a Molecular Epidemiological Perspective
Authors: Blau Khald , Berger Fabian K. , Mellmann Alexander , Gallert Claudia
Published: October 2023

Clostridioides difficile is the most important pathogen causing antimicrobial-associated diarrhea and has recently been recognized as a cause of community-associated C. difficile infection (CA-CDI). This study aimed to characterize virulence factors, antimicrobial resistance (AMR), ribotype (RT) distribution and genetic relationship of C. difficile isolates from diverse fecally contaminated environmental sources. C. difficile isolates were recovered from different environmental samples in Northern Germany. Antimicrobial susceptibility testing was determined by E-test or disk diffusion method. Toxin genes (tcdA and tcdB), genes coding for binary toxins (cdtAB) and ribotyping were determined by PCR. Furthermore, 166 isolates were subjected to whole genome sequencing (WGS) for core genome multi-locus sequence typing (cgMLST) and extraction of AMR and virulence-encoding genes. Eighty-nine percent (148/166) of isolates were toxigenic, and 51% (76/148) were positive for cdtAB. Eighteen isolates (11%) were non-toxigenic. Thirty distinct RTs were identified. The most common RTs were RT127, RT126, RT001, RT078, and RT014. MLST identified 32 different sequence types (ST). The dominant STs were ST11, followed by ST2, ST3, and ST109. All isolates were susceptible to vancomycin and metronidazole and displayed a variable rate of resistance to moxifloxacin (14%), clarithromycin (26%) and rifampicin (2%). AMR genes, such as gyrA/B, blaCDD-1/2, aph(3′)-llla-sat-4-ant(6)-la cassette, ermB, tet(M), tet(40), and tetA/B(P), conferring resistance toward fluoroquinolone, beta-lactam, aminoglycoside, macrolide and tetracycline antimicrobials, were found in 166, 137, 29, 32, 21, 72, 17, and 9 isolates, respectively. Eleven “hypervirulent” RT078 strains were detected, and several isolates belonged to RTs (i.e., RT127, RT126, RT023, RT017, RT001, RT014, RT020, and RT106) associated with CA-CDI, indicating possible transmission between humans and environmental sources pointing out to a zoonotic potential.
Microbial Community Colonization Process Unveiled through eDNA-PFU Technology in Mesocosm Ecosystems
Authors: Gu Siyu , Zhang Peng , Luo Shuai , Chen Kai , Jiang Chuanqi , Xiong Jie , Miao Wei
Published: October 2023

Microbial communities are essential components of aquatic ecosystems and are widely employed for the detection, protection, and restoration of water ecosystems. The polyurethane foam unit (PFU) method, an effective and widely used environmental monitoring technique, has been improved with the eDNA-PFU method, offering efficiency, rapidity, and standardization advantages. This research aimed to explore the colonization process of microbial communities within PFUs using eDNA-PFU technology. To achieve this, we conducted ten-day monitoring and sequencing of microbial communities within PFUs in a stable and controlled artificial aquatic ecosystem, comparing them with water environmental samples (eDNA samples). Results showed 1065 genera in eDNA-PFU and 1059 in eDNA, with eDNA-PFU detecting 99.95% of eDNA-identified species. Additionally, the diversity indices of bacteria and eukaryotes in both methods showed similar trends over time in the colonization process; however, relative abundance differed. We further analyzed the colonization dynamics of microbes in eDNA-PFU and identified four clusters with varying colonization speeds. Notably, we found differences in colonization rates between bacteria and eukaryotes. Furthermore, the Molecular Ecological Networks (MEN) showed that the network in eDNA-PFU was more modular, forming a unique microbial community differentiated from the aquatic environment. In conclusion, this study, using eDNA-PFU, comprehensively explored microbial colonization and interrelationships in a controlled mesocosm system, providing foundational data and reference standards for its application in aquatic ecosystem monitoring and beyond.
Review and Perspectives on Bifidobacterium lactis for Infants’ and Children’s Health
Authors: Tremblay Annie , Bronner Stéphane , Binda Sylvie
Published: October 2023

The influence of microbiota dysbiosis in early life is increasingly recognized as a risk factor for the development of several chronic diseases later in life, including an increased risk of asthma, eczema, allergies, obesity, and neurodevelopmental disorders. The question whether the potential lifelong consequences of early life dysbiosis could be mitigated by restoring microbiota composition remains unresolved. However, the current evidence base suggests that protecting the normal development of the microbiome during this critical developmental window could represent a valuable public health strategy to curb the incidence of chronic and lifestyle-related diseases. Probiotic Bifidobacteria are likely candidates for this purpose in newborns and infants considering the natural dominance of this genus on microbiota composition in early life. Moreover, the most frequently reported microbiota composition alteration in association with newborn and infant diseases, including necrotizing enterocolitis and diarrhea, is a reduction in Bifidobacteria levels. Several studies have assessed the effects of B. animalis subsp. lactis strains in newborns and infants, but recent expert opinions recommend analyzing their efficacy at the strain-specific level. Hence, using the B94 strain as an example, this review summarizes the clinical evidence available in infants and children in various indications, discussing the safety and potential modes of actions while providing perspectives on the concept of “non-infant-type” probiotics for infants’ health.