YiQi GuBen formula alleviates airway inflammation and airway remodeling in OVA-induced asthma mice through TLR4/NF-κB signaling pathway.

BACKGROUND: We aim to investigate the effect of YiQi GuBen formula (YQGB) on airway inflammation and airway remodeling in the ovalbumin (OVA)-induced asthma model to further explore the potential mechanisms of YQGB in treating allergic asthma. METHODS: Mice were divided into five groups randomly (n = 10): the control group, OVA group, OVA + Dex (0.1 mg/kg) group, OVA + low-dose (1.1 g/kg) YQGB group, and OVA + high-dose (2.2 g/kg) YQGB group. Inflammatory cell count and IgE were detected in bronchoalveolar lavage fluid (BALF). Lung tissue histopathology was observed by using H&E, PAS, Masson, and immunohistochemistry staining. qRT-PCR and western blot were applied to analyze key genes and proteins associated with TLR4 and NF-κB signaling pathways. RESULTS: In OVA-induced asthma mice, YQGB decreased eosinophils and IgE in BALF. YQGB alleviated the OVA-induced inflammatory infiltration and declined IL-4, IL-5, IL-13, Eotaxin, ECP, GM-CSF, LTC4, and LTD4. YQGB attenuated the OVA-induced goblet cell metaplasia and mucus hypersecretion. YQGB mitigated the OVA-induced subepithelial fibrosis and lowered TGF-ß1, E-Cadherin, Vimentin, and Fibronectin. YQGB ameliorated the OVA-induced airway smooth muscle thickening and lessened α-SMA and PDGF levels. YQGB reduced the expression of TLR4, MyD88, TRAF6, IκBα, and p65 mRNAs, and IκBα and p-p65 protein levels were also reduced. CONCLUSION: YQGB exhibits the anti-asthma effect by reducing airway inflammation and airway remodeling through suppressing TLR4/NF-κB signaling pathway, and is worth promoting clinically.

Design of Digital Twin Cutting Experiment System for Shearer.

This study presents an advanced simulated shearer machine cutting experiment system enhanced with digital twin technology. Central to this system is a simulated shearer drum, designed based on similarity theory to accurately mirror the operational dynamics of actual mining cutters. The setup incorporates a modified machining center equipped with sophisticated sensors that monitor various parameters such as cutting states, forces, torque, vibration, temperature, and sound. These sensors are crucial for precisely simulating the shearer cutting actions. The integration of digital twin technology is pivotal, featuring a real-time data management layer, a dynamic simulation mechanism model layer, and an application service layer that facilitates virtual experiments and algorithm refinement. This multifaceted approach allows for in-depth analysis of simulated coal cutting, utilizing sensor data to comprehensively evaluate the shearer's performance. The study also includes tests on simulated coal samples. The system effectively conducts experiments and captures cutting condition signals via the sensors. Through time domain analysis of these signals, gathered while cutting materials of varying strengths, it is determined that the cutting force signal characteristics are particularly distinct. By isolating the cutting force signal as a key feature, the system can effectively distinguish between different cutting modes. This capability provides a robust experimental basis for coal rock identification research, offering significant insights into the nuances of shearer operation.

Study on detonation characteristics of pulverized coal and evolution law of detonation residue.

This study explores the detonation characteristics and compositional changes of pulverized coal, focusing on its use in Rotary Detonation Wave (RDW) technologies. While pulverized coal has shown high fuel efficiency in RDW settings, transitioning from theory to practical detonation engineering presents substantial scientific and technical hurdles. A key issue is the reprocessing of detonation byproducts for in-situ coal mine gob filling, a topic that has received little attention. Utilizing advanced methods like X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR), this paper investigates the micro-morphology, composition, and aromatic structures of gas-solid products pre and post-detonation at the Tashan Coal Mine's 2305 working face. Results indicate that coal dust from the underground mining face has enhanced detonation characteristics, with the addition of coal powder fuel extending the gas detonation limits. This benefits economic aspects by reducing reliance on gas fuel and lowering detonation fuel costs. The highest recorded detonation wave velocity was 2450 m/s, 14.8% greater than that of coal dust from external sources, suggesting more effective energy release and pressure gain. Furthermore, the study links detonation combustion intensity to coal's aromatic properties, noting a post-detonation aromaticity index (I) of 0.4941. This indicates an improvement in the aromatic structure under high-temperature conditions, vital for coal's reactivity and energy efficiency in RDW applications. This research not only deepens the understanding of coal dust combustion mechanisms but also advances clean coal utilization and deep coal fluidization mining, addressing significant RDW technological challenges.

YiQi GuBen capsule alleviates OVA-induced asthma through improving mitochondrial dysfunction.

Objective: This study aims to explore the effect of YiQi GuBen capsule on improving mitochondrial dysfunction in an animal model of asthma.Methods: The mice (n = 8) were divided into four groups including control (NC), ovalbumin (OVA), dexamethasone (OVA + DEX), and YiQi GuBen (OVA + YQGB) groups. Firstly, we established an OVA-induced mouse asthma model except for the NC group, which then were treated with dexamethasone and YiQi GuBen capsule. Subsequently, HE staining and Masson staining were used for pathological analysis of mice lung tissues. Next, we used transmission electron microscopy (TEM) to observe the effect of the Yiqi Guben capsule on the ultrastructure of mitochondria. Flow cytometry was used to analyze the ROS level, membrane potential, and the number of mitochondria in lung tissue. Moreover, we analyzed the copy number of mitochondrial DNA (mtDNA) and the expression levels of activator peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) and mitochondrial transcription factor A (TFAM).Results: The results of the pathological analysis showed that after treatment with the YiQi GuBen capsule, the lung tissue damage was significantly reduced. In addition, we observed that the ultrastructural damage of mitochondria was improved. Flow cytometry proved that after treatment with the YiQi GuBen capsule, the level of ROS in the mitochondria was effectively reduced, while the mitochondrial membrane potential decreased and the number increased significantly. Moreover, we found that the copy number of mtDNA was significantly increased and the expression levels of PGC-1α and TFAM were significantly upgraded.Conclusion: This study suggests YiQi GuBen capsule can effectively improve mitochondrial dysfunction in the OVA-induced mouse model.

Design of a Multiparametric Perfusion Bioreactor System for Evaluating Sub-Normothermic Preservation of Rat Abdominal Wall Vascularized Composite Allografts.

Static cold storage (SCS), the current clinical gold standard for organ preservation, provides surgeons with a limited window of time between procurement and transplantation. In vascularized composite allotransplantation (VCA), this time limitation prevents many viable allografts from being designated to the best-matched recipients. Machine perfusion (MP) systems hold significant promise for extending and improving organ preservation. Most of the prior MP systems for VCA have been built and tested for large animal models. However, small animal models are beneficial for high-throughput biomolecular investigations. This study describes the design and development of a multiparametric bioreactor with a circuit customized to perfuse rat abdominal wall VCAs. To demonstrate its concept and functionality, this bioreactor system was employed in a small-scale demonstrative study in which biomolecular metrics pertaining to graft viability were evaluated non-invasively and in real time. We additionally report a low incidence of cell death from ischemic necrosis as well as minimal interstitial edema in machine perfused grafts. After up to 12 h of continuous perfusion, grafts were shown to survive transplantation and reperfusion, successfully integrating with recipient tissues and vasculature. Our multiparametric bioreactor system for rat abdominal wall VCA provides an advanced framework to test novel techniques to enhance normothermic and sub-normothermic VCA preservations in small animal models.

Mechanistic insights into targeting caspase-3 activation and alveolar macrophage pyroptosis by Ephedra and bitter almond compounds for treating pediatric pneumonia via network pharmacology and bioinformatics.

This study investigates the molecular mechanism of Ma Huang-Ku Xing Ren, a traditional Chinese medicine formula, in treating pediatric pneumonia. The focus is on the regulation of caspase-3 activation and reduction of alveolar macrophage necrosis through network pharmacology and bioinformatics analyses of Ephedra and bitter almond components. Active compounds and targets from ephedrine and bitter almond were obtained using TCMSP, TCMID, and GeneCards databases, identifying pediatric pneumonia-related genes. A protein-protein interaction (PPI) network was constructed, and core targets were screened. GO and KEGG pathway enrichment analyses identified relevant genes and pathways. An acute pneumonia mouse model was created using the lipopolysaccharide (LPS) inhalation method, with caspase-3 overexpression induced by a lentivirus. The mice were treated with Ephedra and bitter almond through gastric lavage. Lung tissue damage, inflammatory markers (IL-18 and IL-1ß), and cell death-related gene activation were assessed through H&E staining, ELISA, western blot, flow cytometry, and immunofluorescence. The study identified 128 active compounds and 121 gene targets from Ephedra and bitter almond. The PPI network revealed 13 core proteins, and pathway analysis indicated involvement in inflammation, apoptosis, and cell necrosis, particularly the caspase-3 pathway. In vivo results showed that Ephedra and bitter almond treatment significantly mitigated LPS-induced lung injury in mice, reducing lung injury scores and inflammatory marker levels. It also decreased caspase-3 activity and cell death in alveolar macrophages. In conclusion, the active ingredients of Ma Huang-Ku Xing Ren, particularly targeting caspase-3, may effectively treat pediatric pneumonia by reducing apoptosis in alveolar macrophages, as demonstrated by both network pharmacology, bioinformatics analyses, and experimental data.

Learning to Guide Particle Search for Dynamic Multiobjective Optimization.

Dynamic multiobjective optimization problems (DMOPs) are characterized by multiple objectives that change over time in varying environments. More specifically, environmental changes can be described as various dynamics. However, it is difficult for existing dynamic multiobjective algorithms (DMOAs) to handle DMOPs due to their inability to learn in different environments to guide the search. Besides, solving DMOPs is typically an online task, requiring low computational cost of a DMOA. To address the above challenges, we propose a particle search guidance network (PSGN), capable of directing individuals' search actions, including learning target selection and acceleration coefficient control. PSGN can learn the actions that should be taken in each environment through rewarding or punishing the network by reinforcement learning. Thus, PSGN is capable of tackling DMOPs of various dynamics. Additionally, we efficiently adjust PSGN hidden nodes and update the output weights in an incremental learning way, enabling PSGN to direct particle search at a low computational cost. We compare the proposed PSGN with seven state-of-the-art algorithms, and the excellent performance of PSGN verifies that it can handle DMOPs of various dynamics in a computationally very efficient way.

Effects of tail nerve electrical stimulation on the activation and plasticity of the lumbar locomotor circuits and the prevention of skeletal muscle atrophy after spinal cord transection in rats.

INTRODUCTION: Severe spinal cord injury results in the loss of neurons in the relatively intact spinal cord below the injury area and skeletal muscle atrophy in the paralyzed limbs. These pathological processes are significant obstacles for motor function reconstruction. OBJECTIVE: We performed tail nerve electrical stimulation (TNES) to activate the motor neural circuits below the injury site of the spinal cord to elucidate the regulatory mechanisms of the excitatory afferent neurons in promoting the reconstruction of locomotor function. METHODS: Eight days after T10 spinal cord transection in rats, TNES was performed for 7 weeks. Behavioral scores were assessed weekly. Electrophysiological tests and double retrograde tracings were performed at week 8. RESULTS: After 7 weeks of TNES treatment, there was restoration in innervation, the number of stem cells, and mitochondrial metabolism in the rats' hindlimb muscles. Double retrograde tracings of the tail nerve and sciatic nerve further confirmed the presence of synaptic connections between the tail nerve and central pattern generator (CPG) neurons in the lumbar spinal cord, as well as motor neurons innervating the hindlimb muscles. CONCLUSION: The mechanisms of TNES induced by the stimulation of primary afferent nerve fibers involves efficient activation of the motor neural circuits in the lumbosacral segment, alterations of synaptic plasticity, and the improvement of muscle and nerve regeneration, which provides the structural and functional foundation for the future use of cutting-edge biological treatment strategies to restore voluntary movement of paralyzed hindlimbs.

Association between parental occupational exposure and the risk of asthma in offspring: A meta-analysis and systematic review.

BACKGROUND: Previous epidemiological studies have shown inconsistent results regarding the relation between the risk of asthma in offspring and parental occupational exposure. Therefore, we conducted a comprehensive and systematic collection of currently available epidemiological data to quantify the correlation between the 2. METHODS: Related studies published before March 2023 were identified through searches of the Cochrane Library, Embase, PubMed, and Web of Science databases. The quality of included studies was assessed using the Newcastle-Ottawa Scale, while pooled odds ratios (ORs) with 95% confidence intervals (CIs) were computed using fixed-effect or random-effects models. RESULTS: This systematic review included 10 cohort studies, with a total of 89,571 parent-child pairs included in the quantitative analysis. The results exhibited a substantial association between parental occupational exposure to allergens (OR = 1.11; 95% CI: 1.00, 1.23; P = .051) and irritants (OR = 1.19; 95% CI: 1.07, 1.32; P = .001) and an increased risk of asthma in offspring. This association was also observed in the analysis of wheezing (OR = 1.22; 95% CI: 1.11, 1.35; P < .001 and OR = 1.19; 95% CI: 1.08, 1.32; P = .001). Subgroup analysis demonstrated that maternal occupational exposure to allergens (OR = 1.07; 95% CI: 1.02, 1.12; P = .008) and irritants (OR = 1.13; 95% CI: 1.05, 1.21; P = .001) significantly increased the risk of childhood asthma. Furthermore, parental postnatal occupational exposure to allergens (OR = 1.26; 95% CI: 1.10, 1.46; P = .001) and irritants (OR = 1.26; 95% CI: 1.06, 1.49; P = .009) had a more pronounced impact on childhood asthma. Higher levels of exposure (OR = 1.26; 95% CI: 1.10, 1.46; P = .001 and OR = 1.30; 95% CI: 1.16, 1.47; P < .001) were recognized as significant risk factors for childhood asthma. CONCLUSION: Parental occupational exposure to allergens and irritants increases the risk of asthma and wheezing in offspring, with maternal exposure, postnatal exposure, and high-dose exposure being the primary risk factors for childhood asthma.

Design and Experimental Results of a Three-Dimensional Force Sensor for Shearer Cutting Pick Force Monitoring.

The main focus of this work is the design and development of a three-dimensional force sensor for the cutting pick of a coal mining shearer's simulated drum. This sensor is capable of simultaneously measuring the magnitude of force along three directions of the cutting pick during the cutting sample process. The three-dimensional force sensor is built based on the strain theory of material mechanics, and reasonable structural design is implemented to improve its sensitivity and reduce inter-axis coupling errors. The strain distribution of the sensor is analyzed using finite element analysis software, and the distribution of the strain gauges is determined based on the analysis results. In addition, a calibration test system is designed for the sensor, and the sensitivity, linearity, and inter-axis coupling errors of the sensor are calibrated and tested using loading experiments in three mutually perpendicular directions. Modal simulation analysis and actual cutting pick testing of the coal mining machine's simulated drum are conducted to study the dynamic characteristics and functionality of the sensor in practical applications. The experimental results depict sensitivities of 0.748 mV/V, 2.367 mV/V, and 2.83 mV/V for the newly developed sensor, respectively. Furthermore, the cross-sensitivity error was lower than 5.02%. These findings validate that the sensor's structure satisfies the measurement requirements for pick-cutting forces.

Online Sparse Representation Clustering for Evolving Data Streams.

Data stream clustering can be performed to discover the patterns underlying continuously arriving sequences of data. A number of data stream clustering algorithms for finding clusters in arbitrary shapes and handling outliers, such as density-based clustering algorithms, have been proposed. However, these algorithms are often limited in their ability to construct and merge microclusters by measuring the Euclidean distances between high-dimensional data objects, e.g., transferring valuable knowledge from historical landmark windows to the current landmark window, and exploiting evolving subspace structures adaptively. We propose an online sparse representation clustering (OSRC) method to learn an affinity matrix for evaluating the relationships among high-dimensional data objects in evolving data streams. We first introduce a low-dimensional projection (LDP) into sparse representation to adaptively reduce the potential negative influence associated with the noise and redundancy contained in high-dimensional data. Then, we take advantage of the l2,1 -norm optimization technique to choose the appropriate number of representative data objects and form a specific dictionary for sparse representation. The specific dictionary is integrated into sparse representation to adaptively exploit the evolving subspace structures of the high-dimensional data objects. Moreover, the data object representatives from the current landmark window can transfer valuable knowledge to the next landmark window. The experimental results based on a synthetic dataset and six benchmark datasets validate the effectiveness of the proposed method compared to that of state-of-the-art methods for data stream clustering.

Telomerase reverse transcriptase restores pancreatic microcirculation profiles and attenuates endothelial dysfunction by inhibiting mitochondrial superoxide production: A potential target for acute pancreatitis therapy.

BACKGROUND: Acute pancreatitis (AP) is a potentially lethal disease related to prominent microcirculation dysfunction. Pancreatic microvascular endothelial dysfunction enhances oxidative stress with tissue damage. Increased superoxide production disrupts endothelial junction integrity and increases endothelial permeability. Endothelial mitochondrial ROS (mtROS) represent a major intracellular source of superoxide anions. The non-canonical function of telomerase reverse transcriptase (TERT) involves the maintenance of cellular redox homeostasis in somatic tissues. METHODS: We investigated whether TERT restores microcirculation dysfunction and attenuates the endothelium injury by inhibiting superoxide production during AP progression. We established TERT transgenic and TERT knock-down mice and used cerulein (CER) and lipopolysaccharide (LPS) injections to induce AP models. In addition, we exposed HUVECs to LPS following TERT overexpression or silencing to explore the role of TERT in endothelial dysfunction. We also performed flow cytometry and confocal microscopy assays by using HUVECs. And a mtROS inhibitor, MitoTempo, was used to scavenge mitochondria superoxide and alkyl. RESULTS: TERT transgenic mice were found to have restored pancreatic microcirculation profiles and microvascular endothelial morphology compared with wild-type mice under cerulein injection. In contrast, TERT silencing displayed the opposite effect in response to cerulein. Subsequently, we showed that TERT overexpression attenuates mtROS production and mitochondrial dysfunction during LPS-stimulated endothelial dysfunction. Furthermore, we found that TERT overexpression maintains the balance between mitochondrial contents and ATP level during endothelial dysfunction. In addition, the protective trend of MitoTempo is impeded after TERT silencing. CONCLUSION: TERT restores pancreatic microcirculation dysfunction and attenuates microvascular endothelium lesions by inhibiting the increase of superoxide production and mitochondrial dysfunction.

The therapeutic mechanism of transcranial iTBS on nerve regeneration and functional recovery in rats with complete spinal cord transection.

Background: After spinal cord transection injury, the inflammatory microenvironment formed at the injury site, and the cascade of effects generated by secondary injury, results in limited regeneration of injured axons and the apoptosis of neurons in the sensorimotor cortex (SMC). It is crucial to reverse these adverse processes for the recovery of voluntary movement. The mechanism of transcranial intermittent theta-burst stimulation (iTBS) as a new non-invasive neural regulation paradigm in promoting axonal regeneration and motor function repair was explored by means of a severe spinal cord transection. Methods: Rats underwent spinal cord transection and 2 mm resection of spinal cord at T10 level. Four groups were studied: Normal (no lesion), Control (lesion with no treatment), sham iTBS (lesion and no functional treatment) and experimental, exposed to transcranial iTBS, 72 h after spinal lesion. Each rat received treatment once a day for 5 days a week; behavioral tests were administered one a week. Inflammation, neuronal apoptosis, neuroprotective effects, regeneration and synaptic plasticity after spinal cord injury (SCI) were determined by immunofluorescence staining, western blotting and mRNA sequencing. For each rat, anterograde tracings were acquired from the SMC or the long descending propriospinal neurons and tested for cortical motor evoked potentials (CMEPs). Regeneration of the corticospinal tract (CST) and 5-hydroxytryptamine (5-HT) nerve fibers were analyzed 10 weeks after SCI. Results: When compared to the Control group, the iTBS group showed a reduced inflammatory response and reduced levels of neuronal apoptosis in the SMC when tested 2 weeks after treatment. Four weeks after SCI, the neuroimmune microenvironment at the injury site had improved in the iTBS group, and neuroprotective effects were evident, including the promotion of axonal regeneration and synaptic plasticity. After 8 weeks of iTBS treatment, there was a significant increase in CST regeneration in the region rostral to the site of injury. Furthermore, there was a significant increase in the number of 5-HT nerve fibers at the center of the injury site and the long descending propriospinal tract (LDPT) fibers in the region caudal to the site of injury. Moreover, CMEPs and hindlimb motor function were significantly improved. Conclusion: Neuronal activation and neural tracing further verified that iTBS had the potential to provide neuroprotective effects during the early stages of SCI and induce regeneration effects related to the descending motor pathways (CST, 5-HT and LDPT). Furthermore, our results revealed key relationships between neural pathway activation, neuroimmune regulation, neuroprotection and axonal regeneration, as well as the interaction network of key genes.

Angiotensin-(1-7) ameliorates intestinal barrier dysfunction by activating the Keap1/Nrf2/HO-1 signaling pathway in acute pancreatitis.

BACKGROUND: Intestinal barrier dysfunction is a serious complication associated with acute pancreatitis (AP). Angiotensin (Ang)-(1-7) plays a protective role in the intestinal barrier, but the underlying mechanism remains clear. This study investigated the impact of Ang-(1-7) on AP-induced intestinal dysfunction and its involvement in the Keap1/Nrf2/HO-1 pathway. METHODS AND RESULTS: We studied caerulein- and lipopolysaccharide (LPS)-induced AP in mice and an epithelial cell line (IEC-6) from the small intestinal crypt of rats. Ang-(1-7) was administered orally or via the tail vein. IEC-6 cells were divided into five groups: control; LPS; LPS + Ang-(1-7); LPS + Ang-(1-7) + ML385 (an Nrf2 inhibitor); and LPS + ML385. Pancreatic and intestinal histopathology scores were analyzed using the Schmidt and Chiu scores. The expression of intestinal barrier-associated proteins and Keap1/Nrf2/HO-1 pathway constituents was assessed by RT-PCR and western blotting. The peroxide and antioxidant activities in the IEC-6 cells were measured. Compared to those in AP mice, Ang-(1-7) diminished the intestinal levels of proinflammatory factors (interleukin-1ß and tumor necrosis factor α) and serum levels of intestine permeability (D-lactate). Ang-(1-7) increased the expression of barrier-associated proteins (aquaporin-1, claudin-1, and occludin) compared to those in the AP and LPS group. Moreover, Ang-(1-7) promoted the Keap/Nrf2/HO-1 pathway, which resulted in significantly reduced malondialdehyde and increased superoxide dismutase levels.. However, ML385 abolished the effects of Ang-(1-7) on barrier-associated proteins and reversed the Keap1/Nrf2/HO-1 pathway. CONCLUSIONS: Ang-(1-7) reduces AP-induced intestinal inflammation and oxidative injuries by activating the Keap1/Nrf2/HO-1 pathway.

Multisurrogate-Assisted Multitasking Particle Swarm Optimization for Expensive Multimodal Problems.

Many real-world applications can be formulated as expensive multimodal optimization problems (EMMOPs). When surrogate-assisted evolutionary algorithms (SAEAs) are employed to tackle these problems, they not only face the problem of selecting surrogate models but also need to tackle the problem of discovering and updating multiple modalities. Different optimization problems and different stages of evolutionary algorithms (EAs) generally require different types of surrogate models. To address this issue, in this article, we present a multisurrogate-assisted multitasking particle swarm optimization algorithm to seek multiple optimal solutions of EMMOPs at a low computational cost. The proposed algorithm first transforms an EMMOP into a multitasking optimization problem by integrating various surrogate models, and designs a multitasking niche particle swarm algorithm to solve it. Following that, a surrogate model management strategy based on the skill factor and clustering is developed to effectively balance the number of real function evaluations and the prediction accuracy of candidate optimal solutions. In addition, an adaptive local search strategy based on the trust region is proposed to enhance the capability of swarm in exploiting potential optimal modalities. We compare the proposed algorithm with five state-of-the-art SAEAs and seven multimodal EAs on 19 benchmark functions and the building energy conservation problem and experimental results show that the proposed algorithm can obtain multiple highly competitive optimal solutions.

Q-Learning-Based Hyperheuristic Evolutionary Algorithm for Dynamic Task Allocation of Crowdsensing.

Task allocation is a crucial issue of mobile crowdsensing. The existing crowdsensing systems normally select the optimal participants giving no consideration to the sudden departure of mobile users, which significantly affects the sensing quality of tasks with a long sensing period. Furthermore, the ability of a mobile user to collect high-precision data is commonly treated as the same for different types of tasks, causing the unqualified data for some tasks provided by a competitive user. To address the issue, a dynamic task allocation model of crowdsensing is constructed by considering mobile user availability and tasks changing over time. Moreover, a novel indicator for comprehensively evaluating the sensing ability of mobile users collecting high-quality data for different types of tasks at the target area is proposed. A new Q -learning-based hyperheuristic evolutionary algorithm is suggested to deal with the problem in a self-learning way. Specifically, a memory-based initialization strategy is developed to seed a promising population by reusing participants who are capable of completing a particular task with high quality in the historical optima. In addition, taking both sensing ability and cost of a mobile user into account, a novel comprehensive strength-based neighborhood search is introduced as a low-level heuristic (LLH) to select a substitute for a costly participant. Finally, based on a new definition of the state, a Q -learning-based high-level strategy is designed to find a suitable LLH for each state. Empirical results of 30 static and 20 dynamic experiments expose that this hyperheuristic achieves superior performance compared to other state-of-the-art algorithms.

Microbiome Characteristics in Early Threatened Miscarriage Study (MCETMS): a study protocol for a prospective cohort investigation in China.

INTRODUCTION: Studies have suggested that the vaginal microbiome and gut microbiome are involved in pregnancy-related diseases, but little exploration of the link with early miscarriage or threatened miscarriage (TM) has been done. Whether the characteristics of the vaginal microbiome and gut microbiome in early pregnancy are related to TM and early pregnancy outcomes remains unclear. METHODS AND ANALYSIS: The Microbiome Characteristics in Early Threatened Miscarriage Study (MCETMS) is a prospective investigation that will recruit 326 pregnant women with early TM. Pregnant women will be enrolled at 4-8 weeks of gestation, and their vaginal secretions, faecal samples, clinical data and sociodemographic characteristics will be collected prospectively. Pregnant women with TM will be followed up to 12 weeks of gestation to determine the early pregnancy outcomes (ongoing pregnancy or pregnancy loss). DNA will be extracted from the collected samples and will be analysed by 16S rRNA gene sequencing. ETHICS AND DISSEMINATION: The MCETMS study protocol has been approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Traditional Chinese Medical University (ZYYECK[2020]051). Dissemination of study findings will occur through peer-reviewed journals, conferences and presentations. TRIAL REGISTRATION NUMBER: ChiCTR2000041172.

Diagnosis of endometrium hyperplasia and screening of endometrial intraepithelial neoplasia in histopathological images using a global-to-local multi-scale convolutional neural network.

BACKGROUND AND OBJECTIVE: Endometrial hyperplasia (EH), a uterine pathology characterized by an increased gland-to-stroma ratio compared to normal endometrium (NE), may precede the development of endometrial cancer (EC). Particularly, atypical EH also known as endometrial intraepithelial neoplasia (EIN), has been proven to be a precursor of EC. Thus, diagnosing different EH (EIN, hyperplasia without atypia (HwA) and NE) and screening EIN from non-EIN are crucial for the health of female reproductive system. Computer-aided-diagnosis (CAD) was used to diagnose endometrial histological images based on machine learning and deep learning. However, these studies perform single-scale image analysis and thus can only characterize partial endometrial features. Empirically, both global (cytological changes relative to background) and local features (gland-to-stromal ratio and lesion dimension) are helpful in identifying endometrial lesions. METHODS: We proposed a global-to-local multi-scale convolutional neural network (G2LNet) to diagnose different EH and to screen EIN in endometrial histological images stained by hematoxylin and eosin (H&E). The G2LNet first used a supervised model in the global part to extract contextual features of endometrial lesions, and simultaneously deployed multi-instance learning in the local part to obtain textural features from multiple image patches. The contextual and textural features were used together to diagnose different endometrial lesions after fusion by a convolutional block attention module. In addition, we visualized the salient regions on both the global image and local images to investigate the interpretability of the model in endometrial diagnosis. RESULTS: In the five-fold cross validation on 7812 H&E images from 467 endometrial specimens, G2LNet achieved an accuracy of 97.01% for EH diagnosis and an area-under-the-curve (AUC) of 0.9902 for EIN screening, significantly higher than state-of-the-arts. In external validation on 1631 H&E images from 135 specimens, G2LNet achieved an accuracy of 95.34% for EH diagnosis, which was comparable to that of a mid-level pathologist (95.71%). Specifically, G2LNet had advantages in diagnosing EIN, while humans performed better in identifying NE and HwA. CONCLUSIONS: The developed G2LNet that integrated both the global (contextual) and local (textural) features may help pathologists diagnose endometrial lesions in clinical practices, especially to improve the accuracy and efficiency of screening for precancerous lesions.

Dynamic Ensemble Selection for Imbalanced Data Streams With Concept Drift.

Ensemble learning, as a popular method to tackle concept drift in data stream, forms a combination of base classifiers according to their global performances. However, concept drift generally occurs in local data space, causing significantly different performances of a base classifier at different locations. Thus, employing global performance as a criterion to select base classifier is inappropriate. Moreover, data stream is often accompanied by class imbalance problem, which affects the classification accuracy of ensemble learning on minority instances. To drawback these problems, a dynamic ensemble selection for imbalanced data streams with concept drift (DES-ICD) is proposed. For data arrived in chunk-by-chunk, a novel synthetic minority oversampling technique with adaptive nearest neighbors (AnnSMOTE) is developed to generate new minority instances that conform to the new concept. Following that, DES-ICD creates a base classifier on newly arrived data chunk balanced by AnnSMOTE and merges it with historical base classifiers to form a candidate classifier pool. For each query instance, the optimal combination is constructed in terms of the performance of candidate classifiers in its neighborhood. Experimental results for nine synthetic and five real-world datasets show that the proposed method outperforms seven comparative methods on classification accuracy and tracks new concepts in an imbalanced data stream more preciously.

Gluconate-Lactobionate-Dextran Perfusion Solutions Attenuate Ischemic Injury and Improve Function in a Murine Cardiac Transplant Model.

Static cold storage is the cheapest and easiest method and current gold standard to store and preserve donor organs. This study aimed to compare the preservative capacity of gluconate-lactobionate-dextran (Unisol) solutions to histidine-tryptophan-ketoglutarate (HTK) solution. Murine syngeneic heterotopic heart transplantations (Balb/c-Balb/c) were carried out after 18 h of static cold storage. Cardiac grafts were either flushed and stored with Unisol-based solutions with high-(UHK) and low-potassium (ULK) ± glutathione, or HTK. Cardiac grafts were assessed for rebeating and functionality, histomorphologic alterations, and cytokine expression. Unisol-based solutions demonstrated a faster rebeating time (UHK 56 s, UHK + Glut 44 s, ULK 45 s, ULK + Glut 47 s) compared to HTK (119.5 s) along with a better contractility early after reperfusion and at the endpoint on POD 3. Ischemic injury led to a significantly increased leukocyte recruitment, with similar degrees of tissue damage and inflammatory infiltrate in all groups, yet the number of apoptotic cells tended to be lower in ULK compared to HTK. In UHK- and ULK-treated animals, a trend toward decreased expression of proinflammatory markers was seen when compared to HTK. Unisol-based solutions showed an improved preservative capacity compared with the gold standard HTK early after cardiac transplantation. Supplemented glutathione did not further improve tissue-protective properties.