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Abstract Doxorubicin (DOX) is a broad-spectrum and highly efficient anticancer agent, but its clinical implication is limited by lethal cardiotoxicity. Growing evidences have shown that alterations in intestinal microbial composition and function, namely dysbiosis, are closely linked to the progression of DOX-induced cardiotoxicity (DIC) through regulating the gut-microbiota-heart (GMH) axis. The role of gut microbiota and its metabolites in DIC, however, is largely unelucidated. Our review will focus on the potential mechanism between gut microbiota dysbiosis and DIC, so as to provide novel insights into the pathophysiology of DIC. Furthermore, we summarize the underlying interventions of microbial-targeted therapeutics in DIC, encompassing dietary interventions, fecal microbiota transplantation (FMT), probiotics, antibiotics, and natural phytochemicals. Given the emergence of microbial investigation in DIC, finally we aim to point out a novel direction for future research and clinical intervention of DIC, which may be helpful for the DIC patients.

Background: Repetitive mild traumatic brain injury (rmTBI) can lead to somatic, emotional, and cognitive symptoms that persist for years after the initial injury. Although the ability of various treatments to promote recovery after rmTBI has been explored, the optimal time window for early intervention after rmTBI is unclear. Previous research has shown that hydrogen-rich water (HRW) can diffuse through the blood-brain - barrier, attenuate local oxidative stress, and reduce neuronal apoptosis in patients with severe traumatic brain injury. However, research on the effect of HRW on rmTBI is scarce. Aims: The objectives of this study were to explore the following changes after rmTBI and HRW treatment: (i) temporal changes in inflammasome activation and oxidative stress-related protein expression through immunoblotting, (ii) temporal changes in neuron/myelin-related metabolite concentrations in vivo through magnetic resonance spectroscopy, (iii) myelin structural changes in late-stage rmTBI via immunofluorescence, and (iv) postinjury anxiety/depression-like behaviors and spatial learning and memory impairment. Results: NLRP-3 expression in the rmTBI group was elevated at 7 and 14 DPI, and inflammasome marker levels returned to normal at 30 DPI. Oxidative stress persisted throughout the first month postinjury. HRW replacement significantly decreased Nrf2 expression in the prefrontal cortex and hippocampal CA2 region at 14 and 30 DPI, respectively. Edema and local gliosis in the hippocampus and restricted diffusion in the thalamus were observed on MR-ADC images. The tCho/tCr ratio in the rmTBI group was elevated, and the tNAA/tCr ratio was decreased at 30 DPI. Compared with the mice in the other groups, the mice in the rmTBI group spent more time exploring the open arms in the elevated plus maze (P < 0.05) and were more active in the maze (longer total distance traveled). In the sucrose preference test, the rmTBI group exhibited anhedonia. In the Morris water maze test, the latency to find the hidden platform in the rmTBI group was longer than that in the sham and HRW groups (P < 0.05). Conclusion: Early intervention with HRW can attenuate inflammasome assembly and reduce oxidative stress after rmTBI. These changes may restore local oligodendrocyte function, promote myelin repair, prevent axonal damage and neuronal apoptosis, and alleviate depression-like behavior and cognitive impairment.

BackgroundIncreasing evidence indicating that coronavirus disease 2019 (COVID-19) increased the incidence and related risks of pericarditis and whether COVID-19 vaccine is related to pericarditis has triggered research and discussion. However, mechanisms behind the link between COVID-19 and pericarditis are still unknown. The objective of this study was to further elucidate the molecular mechanisms of COVID-19 with pericarditis at the gene level using bioinformatics analysis.MethodsGenes associated with COVID-19 and pericarditis were collected from databases using limited screening criteria and intersected to identify the common genes of COVID-19 and pericarditis. Subsequently, gene ontology, pathway enrichment, protein–protein interaction, and immune infiltration analyses were conducted. Finally, TF–gene, gene–miRNA, gene–disease, protein–chemical, and protein–drug interaction networks were constructed based on hub gene identification.ResultsA total of 313 common genes were selected, and enrichment analyses were performed to determine their biological functions and signaling pathways. Eight hub genes (IL-1β, CD8A, IL-10, CD4, IL-6, TLR4, CCL2, and PTPRC) were identified using the protein–protein interaction network, and immune infiltration analysis was then carried out to examine the functional relationship between the eight hub genes and immune cells as well as changes in immune cells in disease. Transcription factors, miRNAs, diseases, chemicals, and drugs with high correlation with hub genes were predicted using bioinformatics analysis.ConclusionsThis study revealed a common gene interaction network between COVID-19 and pericarditis. The screened functional pathways, hub genes, potential compounds, and drugs provided new insights for further research on COVID-19 associated with pericarditis.

Lunar shallow subsurface structure is important in revealing the formation and evolution of the Moon. Therefore, a review of key issues in the lunar shallow subsurface structure will help deepen our understanding of the Moon. From a global perspective, lunar shallow subsurface structure is formed by endogenic and exogenic geological processes such as volcanic activities, tectonic activities, meteorite impacts, and space weathering. Its morphological characteristics and stratigraphic structure record the evolution of these geological processes. Recent lunar exploration missions have returned new samples and high-resolution data that have greatly enriched our knowledge. On the basis of reviewing the research progress of radar detection, crater-based excavation analysis, material inversion, and heat flow measurement, we also discuss the processes that contribute to the formation of the lunar shallow surface structure, such as volcanoes, impacts, tectonics, and space weathering. The main hot issues were sorted out and focused on 3 areas: transformation of lunar shallow subsurface structure by geological processes, environment and material composition of the lunar shallow surface structure, and physical properties of lunar shallow surface structure. Overall, existing research on the lunar subsurface has made significant progress, but it has also brought more new unsolved mysteries. It is necessary to introduce new applied payloads such as synthetic aperture radar (SAR), orbiter subsurface investigation radar (OSIR), or time-domain electromagnetic sounding (TDEM) to provide higher-resolution subsurface data, and develop better interpretation methodologies, to further deepen the understanding of the lunar shallow subsurface structure and indeed reveal the mechanism of lunar geological evolution.

Abstract L−3,4-dihydroxyphenylalanine is an important molecule in the adhesion of mussels, and as an oxidative precursor of natural melanin, it plays an important role in living system. Here, we investigate the effect of the molecular chirality of 3,4-dihydroxyphenylalanine on the properties of the self-assembled films by tyrosinase-induced oxidative polymerization. The kinetics and morphology of pure enantiomers are completely altered upon their co-assembly, allowing the fabrication of layer-to-layer stacked nanostructures and films with improved structural and thermal stability. The different molecular arrangements and self-assembly mechanisms of the L+D-racemic mixtures, whose oxidation products have increased binding energy, resulting in stronger intermolecular forces, which significantly increases the elastic modulus. This study provides a simple pathway for the fabrication of biomimetic polymeric materials with enhanced physicochemical properties by controlling the chirality of monomers.

Abstract Background The intestinal epithelial barrier confers protection against the intestinal invasion by pathogens and exposure to food antigens and toxins. Growing studies have linked the gut microbiota to the intestinal epithelial barrier function. The mining of the gut microbes that facilitate the function of intestinal epithelial barrier is urgently needed. Results Here, we studied a landscape of the gut microbiome of seven pig breeds using metagenomics and 16S rDNA gene amplicon sequencing. The results indicated an obvious difference in the gut microbiome between Congjiang miniature (CM) pigs (a native Chinese breed) and commercial Duroc × [Landrace × Yorkshire] (DLY) pigs. CM finishing pigs had stronger intestinal epithelial barrier function than the DLY finishing pigs. Fecal microbiota transplantation from CM and DLY finishing pigs to germ-free (GF) mice transferred the intestinal epithelial barrier characteristics. By comparing the gut microbiome of the recipient GF mice, we identified and validated Bacteroides fragilis as a microbial species that contributes to the intestinal epithelial barrier. B. fragilis-derived 3-phenylpropionic acid metabolite had an important function on the enhancement of intestinal epithelial barrier. Furthermore, 3-phenylpropionic acid facilitated the intestinal epithelial barrier by activating aryl hydrocarbon receptor (AhR) signaling. Conclusions These findings suggest that manipulation of B. fragilis and 3-phenylpropionic acid is a promising strategy for improving intestinal epithelial barrier. Video Abstract

Abstract Background Gut fungi are increasingly recognized as important contributors to host physiology, although most studies have focused on gut bacteria. Post-translational modifications (PTMs) of proteins play vital roles in cell metabolism. However, the contribution of gut fungi to host protein PTMs remains unclear. Mining gut fungi that mediate host protein PTMs and dissecting their mechanism are urgently needed. Results We studied the gut fungal communities of 56 weaned piglets and 56 finishing pigs from seven pig breeds using internal transcribed spacer (ITS) gene amplicon sequencing and metagenomics. The results showed that Kazachstania slooffiae was the most abundant gut fungal species in the seven breeds of weaned piglets. K. slooffiae decreased intestinal epithelial lysine succinylation levels, and these proteins were especially enriched in the glycolysis pathway. We demonstrated that K. slooffiae promoted intestinal epithelial glycolysis by decreasing lysine succinylation by activating sirtuin 5 (SIRT5). Furthermore, K. slooffiae-derived 5′-methylthioadenosine metabolite promoted the SIRT5 activity. Conclusions These findings provide a landscape of gut fungal communities of pigs and suggest that K. slooffiae plays a crucial role in intestinal glycolysis metabolism through lysine desuccinylation. Our data also suggest a potential protective strategy for pigs with an insufficient intestinal energy supply. Video Abstract

The brain is highly integrated and thus unilateral injury can impact the contralateral hemisphere. However, further research is needed to clarify the changes in the response of the contralateral homotopic area to ipsilateral injury. We hypothesized that severe unilateral brain injury would be accompanied by contralateral synaptic changes that are related to functional recovery. To test this, we divided rats into sham and experimental groups. In the experimental group, we performed right motor cortex resection. These rats were further divided into three subgroups according to post-injury time: 7 days, 14 days, and 30 days post-injury. Rats in each group were evaluated using a beam walking test to quantify the recovery of motor function, and all rats received an injection of adeno-associated virus-containing green fluorescent protein (GFP). Finally, we conducted morphological and histological analyses to identify synaptic changes. Over time, the behavior of the rats that underwent right motor cortex resection recovered. Furthermore, in contrast to the sham group, the experimental groups exhibited an increase in the spine density and expression of synaptic proteins in layer V of the contralateral motor cortex, which was consistent with the GFP-labeled neurons. Moreover, more immature spines were observed 7 days post-injury. Notably, spine morphology matured from 7 to 30 days, and the increase in Synapsin-1 intensity in layer V peaked 14 days after the resection, whereas PSD-95 intensity continued to increase until day 30. Our findings suggested that following motor function recovery from unilateral brain injury, spine morphology and synaptic proteins change dynamically in the contralateral hemisphere.

The vibration-based damage detection (VBDD) has been widely used in structural health monitoring (SHM). However, different damage indicators have different effects on SHM. It is necessary to analyze the sensitivity of structural damage indicators to study the correlation between these indicators and damages. In this paper, the sensitivities of the mode shape, modal strain energy (MSE) and strain mode are numerically studied and experimentally validated. The damage is simulated by the reduction in the cross-sectional area of the rods of a 3-D steel frame. The sensitivity of the three damage indicators are obtained and compared by using the finite element (FE) analyses of the frame; the modal parameters are obtained through the experimental modal analysis, and the sensitivity of the three damage indicators are calculated to validate whether they could identify the structural damage. The results indicate that, generally, the sensitivity of the modal strain is the highest, followed by the MSE, and the sensitivity of the mode shape is the lowest. Nevertheless, the MSE shows high sensitivity in the cases of multiple damages. The sensitivity of the damage indicators varies for different damage locations; the sensitivity decreases from the mid span to the end of the steel frame. The above results provide a theoretical basis for the selection of damage indicators in the damage detection.

Bacillus amyloliquefaciens is a generally recognized as safe (GRAS) microorganism that presents great potential for the production of heterologous proteins. In this study, we performed genomic and comparative transcriptome to investigate the critical modular in B. amyloliquefaciens on the production of heterologous alkaline proteases (AprE). After investigation, it was concluded that the key modules affecting the production of alkaline protease were the sporulation germination module (Module I), extracellular protease synthesis module (Module II), and extracellular polysaccharide synthesis module (Module III) in B. amyloliquefaciens. In Module I, AprE yield for mutant BA ΔsigF was 25.3% greater than that of BA Δupp. Combining Module I synergistically with mutation of extracellular proteases in Module II significantly increased AprE production by 36.1% compared with production by BA Δupp. In Module III, the mutation of genes controlling extracellular polysaccharides reduced the viscosity and the accumulation of sediment, and increased the rate of dissolved oxygen in fermentation. Moreover, AprE production was 39.6% higher than in BA Δupp when Modules I, II and III were engineered in combination. This study provides modular engineering strategies for the modification of B. amyloliquefaciens for the production of alkaline proteases.

Abstract Background We previously found that high-dose methylprednisolone increased the incidence of critical illness-related corticosteroid insufficiency (CIRCI) and mortality in rats with traumatic brain injury (TBI), whereas low-dose hydrocortisone but not methylprednisolone exerted protective effects. However, the receptor-mediated mechanism remains unclear. This study investigated the receptor-mediated mechanism of the opposite effects of different glucocorticoids on the survival of paraventricular nucleus (PVN) cells and the incidence of CIRCI after TBI. Methods Based on controlled cortical impact (CCI) and treatments, male SD rats (n = 300) were randomly divided into the sham, CCI, CCI + GCs (methylprednisolone 1 or 30 mg/kg/day; corticosterone 1 mg/kg/day), CCI + methylprednisolone+RU486 (RU486 50 mg/kg/day), and CCI + corticosterone+spironolactone (spironolactone 50 mg/kg/day) groups. Blood samples were collected 7 days before and after CCI. Brain tissues were collected on postinjury day 7 and processed for histology and western blot analysis. Results We examined the incidence of CIRCI, mortality, apoptosis in the PVN, the receptor-mediated mechanism, and downstream signaling pathways on postinjury day 7. We found that methylprednisolone and corticosterone exerted opposite effects on the survival of PVN cells and the incidence of CIRCI by activating different receptors. High-dose methylprednisolone increased the nuclear glucocorticoid receptor (GR) level and subsequently increased cell loss in the PVN and the incidence of CIRCI. In contrast, low-dose corticosterone but not methylprednisolone played a protective role by upregulating mineralocorticoid receptor (MR) activation. The possible downstream receptor signaling mechanism involved the differential effects of GR and MR on the activity of the Akt/CREB/BDNF pathway. Conclusion The excessive activation of GR by high-dose methylprednisolone exacerbated apoptosis in the PVN and increased CIRCI. In contrast, refilling of MR by corticosterone protects PVN neurons and reduces the incidence of CIRCI by promoting GR/MR rebalancing after TBI.

To precisely and timely control the shaft speed for a marine electric propulsion system under normal sea conditions, a new shaft speed control technique combining the evidential reasoning rule with the traditional PID controller was proposed in this study. First, an intelligent adaptive PID controller based on the evidential reasoning rule was designed for a marine electric propulsion system to obtain the PID parameters KP, KI, and KD. Then, a local iterative optimization strategy for model parameters was proposed. Furthermore, the parameters of the adaptive PID controller model were optimized in real time by using the sequential linear programming algorithm, which enabled the adaptive adjustment of KP, KI, and KD. Finally, the performance of the adaptive PID controller regarding the shaft speed control was compared with that of other controllers. The results showed that the adaptive PID controller designed in this study had better control performance, and the shaft speed control method based on the adaptive PID controller could better control the shaft speed of the marine electric propulsion system.

Bladder cancer (BCa) is one of the most expensive and common malignancies in the urinary system due to its high progression and recurrence rate. Although there are various methods, including cystoscopy, biopsy, and cytology, that have become the standard diagnosis methods for BCa, their intrinsic invasive and inaccurate properties need to be overcome. The novel urine cancer biomarkers are assisted by nanomaterials-based biosensors, such as field-effect transistors (FETs) with high sensitivity and specificity, which may provide solutions to these problems. In addition, nanomaterials can be applied for the advancement of next-generation optical imaging techniques and the contrast agents of conventional techniques; for example, magnetic resonance imaging (MRI) for the diagnosis of BCa. Regarding BCa therapy, nanocarriers, including mucoadhesive nanoparticles and other polymeric nanoparticles, successfully overcome the disadvantages of conventional intravesical instillation and improve the efficacy and safety of intravesical chemotherapy for BCa. Aside from chemotherapy, nanomedicine-based novel therapies, including photodynamic therapy (PDT), photothermal therapy (PTT), chemodynamic therapy (CDT), sonodynamic therapy (SDT), and combination therapy, have afforded us new ways to provide BC therapy and hope, which can be translated into the clinic. In addition, nanomotors and the nanomaterials-based solid tumor disassociation strategy provide new ideas for future research. Here, the advances in BCa diagnosis and therapy mentioned above are reviewed in this paper.

Epoxide hydrolase 1 (EPHX1) has been reported to be related to the development of several tumors. However, the regulation of castration-resistant prostate cancer (CRPC) development by EPHX1 has not been reported. We used proteomic technology and found that the EPHX1 protein was highly expressed in CRPC tissues and the CRPC cell line C4-2. We performed screening and found that EPHX1 is a direct target of miR-491-5p. High miR-491-5p expression significantly reduced the EPHX1 level in C4-2 cells and inhibited C4-2 cell proliferation and migration. Zeolite imidazolate framework-8 (ZIF-8) has good thermal stability, a simple synthesis method, tumor site stability, and specific acid responsiveness. We synthesized ZIF-8 nanodrug vectors to deliver miR-491-5p into C4-2 cells. After loading miR-491-5p into ZIF-8, we modified the ZIF-8 surface with folic acid (FA) as the target group (FA@ZIF-8). Our synthesized nanodrug carrier showed less cytotoxicity to C4-2 cells even at 200 μg/ml. Modified FA could increase the efficiency of nanomaterial entry into C4-2 cells. FA@miR-491-5p@ZIF-8 could stably release miR-491-5p for a long period in both phosphate-buffered saline (pH 7.4) and acetate buffer (pH 4.8), and miR-491-5p was released faster at the beginning of the experiment in acetate buffer (pH 4.8). FA@miR-491-5p@ZIF-8 significantly reduced C4-2 cell proliferation and migration, and FA@miR-491-5p@ZIF-8 had a better effect than miR-491-5p alone. In vivo, FA@miR-491-5p@ZIF-8 significantly inhibited CRPC growth in nude mice. Overall, we verified that miR-491-4p regulated CRPC development by targeting EPHX1. The drug nanocarrier FA@miR-491-5p@ZIF-8 not only significantly reduced C4-2 CRPC cell proliferation and migration but also significantly inhibited CRPC growth. Our research provides a theoretical basis for treatment and treatment strategies for CRPC.

We use multi-source remote sensing data to identify the details of a mascon south-east of the lunar Copernicus crater. Studies of the topography, gravity, geochronology and mineral are combined to prove that the mascon is a buried peak-ring basin with diameters of about 130 km and 260 km. The underground structure is covered by 890 m thick mare basalts, as determined by analyzing the spectral features of the impact crater, Copernicus H. The determination of the crater size–frequency distribution (CSFD) suggests that the impact that created the C-H basin occurred earlier than 3.9 Ga. Then, a Hawaiian-style eruption in the late Imbrian period formed the Sinus Aestuum-I dark mantling deposit (DMD). Soon, mare basalts covered the basin several times from 3.8 Ga. Finally, the ejecta from the Copernicus impact event at about 800 Ma, and the weathering processes caused the disappearance of the C-H basin rim from the lunar surface.

In our recent studies, we reported that mineralocorticoid receptor (MR) had the opposite effects of glucocorticoid receptor (GR) on neural cell survival after traumatic brain injury (TBI). However, whether short-term use of high-dose natural glucocorticoids, which are mixed agonists of both MR and GR, leads to neurotoxic effects by inducing excessive GR activation is unclear, as is the threshold GR activation level and the possible signaling pathways remain unclear. In this study, we examined the dual dose-dependent effects of corticosterone (CORT) on spatial memory, hippocampal cell survival and receptor-mediated downstream signaling pathways after TBI. We found that different doses of CORT exhibited dual effects on hippocampal cell survival and rat spatial memory. Low doses of CORT (0.3 and 3 mg/kg) significantly increased MR activation, upregulated Akt/CREB/Bad phosphorylation and Bcl-2 concentration, reduced the number of apoptotic neural cells, and subsequently improved rat spatial memory. In contrast, a high dose of CORT (30 mg/kg) exerted the opposite effects by overactivating GR, upregulating P53/Bax levels, and inhibiting Erk/CREB activity. The results suggest that the neuroprotective and neurotoxic effects of endogenous GC depend on a threshold level and that a higher dose of GC, even for short-term use, should be avoided after TBI.

Abstract Background Cotton is the most essential textile crop worldwide, and phytohormones are critical for cotton fiber development. One example is the role of auxin in fiber initiation, but we know little molecular basis. MicroRNAs (miRNAs) have a significant function in cotton development; nevertheless their role in fiber initiation remains unclear. Here, exogenous IAA was applied to cotton plant before anthesis. Utilizing small RNA sequencing, the mechanism underlying miRNA-mediated regulation of fiber initiation under exogenous IAA treatment was investigated. Results With exogenous IAA application, the endogenous IAA and GA contents of IAA treated (IT) ovules were higher than control (CK) ovules at the fiber initiation stage, while endogenous ABA content was lower in IT than CK. Using scanning electron microscopy, we found the fiber number and size were significantly promoted in IT at 0 DPA. Fiber quality analysis showed that fiber length, uniformity, strength, elongation, and micronaire of IT were higher than CK, though not statistically significant, while lint percent was significantly higher in IT. We generated six small RNA libraries using − 3, 0, and 3 DPA ovules of IT and CK, and identified 58 known miRNAs and 83 novel miRNAs together with the target genes. The differential expressed miRNAs number between IT and CK at − 3, 0, 3 DPA was 34, 16 and 24, respectively. Gene ontology and KEGG pathway enrichment analyses for the target genes of the miRNAs expressed in a differential manner showed that they were significantly enriched in 30 terms and 8 pathways. QRT-PCR for those identified miRNAs and the target genes related to phytohormones and fiber development was performed, and results suggested a potential role of these miRNAs in fiber initiation. Conclusions The exogenous IAA application affected the relative phytohormone contents in ovule and promoted fiber initiation in cotton. Identification and profiling of miRNAs and their targets at the fiber initiation stage provided insights for miRNAs’ regulation function of fiber initiation. These findings not only shed light on the regulatory network of fiber growth but also offer clues for cotton fiber amelioration strategies in cotton.

Acoustic resonance-based level measurement principle needs to extract a sequence of resonance frequencies (RFs) from the synthesis wave and then calculate level height via this RF sequence. However, in practice, the uncertain disturbances in the measurement environment usually lead to the signal distortion of the collected synthesis wave. In this case, some RF points in the sequence are inevitably missed which causes the nonnegligible calculation error. Hence, based on the Dempster-Shafer evidence theory (DST), this paper presents a recursive evidence fusion method to combine multiple RF sequences in a row. It provides a natural way to supplement the missed RF points and also significantly improve the measurement accuracy even if the observed RF sequences are all intact. That is to say, regardless of the missing case or intact case, the proposed fusion method always has high performance. Finally, the comparative experiments of level detection show the level gauge using this method is robust for the sequence with the missing RF points and can further provide higher measurement accuracy than the single RF sequence-based and digital filtering-based level detection methods.

Increasing in urban traffic brings heavy burden on metro transportations, especially for metro hubs which are crossing metro stations with railways. It calls for special scheduling optimization for such metro hubs by taking consideration of train arrivals. First, a detailed procedure is proposed on how to predict the traffic in such metro hubs under influence of train arrivals, including metros train and metro stations. Moreover, a service-oriented metro scheduling optimization procedure is proposed. Further analysis is then conducted when there is heavy traffic such as special holidays. A practical case on a major metro hub is studies for validation, the Chongqingbei (Chongqing North) metro hub in the city of Chongqing, China. The Chongqingbei metro hub is with four metro lines (Lines 3/4/10/Loop), three metro stations (Longtousi, Chongqingbei North Square, Chongqingbei South Square), and two non-connected railway stations (Chongqingbei North and Chongqingbei South). Passengers on three metro stations over four lines are calculated. Case study results show that: (1) when there is normal traffic, a hybrid schedule is more effective in comparison with regular shifts for Line 3 while Lines 4/10/Loop require no additional shifts, (2) when there is heavy traffic, an optimized metro schedule with a smaller interval (original 6-minute interval is reduced to 4-minute) is more effective for Line 3 whereas hybrid shifts and Line 10 requires hybrid shifts and Line 4 and the Loop Line require no additional shifts.

Evolutionary optimization (EO) has been proven to be highly effective computation means in solving asymmetry problems in engineering practices. In this study, a novel evolutionary optimization approach for the belief rule base (BRB) system is proposed, namely EO-BRB, by constructing an optimization model and employing the Differential Evolutionary (DE) algorithm as its optimization engine due to its ability to locate an optimal solution for problems with nonlinear complexity. In the EO-BRB approach, the most representative referenced values of the attributes which are pre-determined in traditional learning approaches are to be optimized. In the optimization model, the mean squared error (MSE) between the actual and observed data is taken as the objective, while the initial weights of all the rules, the beliefs of the scales in the conclusion part, and the referenced values of the attributes are taken as the restraints. Compared with the traditional learning approaches for the BRB system, the EO-BRB approach (1) does not require transforming the numerical referenced values of the attributes into linguistic terms; (2) does not require identifying any initial solution; (3) does not require any mathematical deduction and/or case-specific information which verifies it as a general approach; and (4) can help downsize the BRB system while producing superior performances. Thus, the proposed EO-BRB approach can make the best use of the nonlinear modeling ability of BRB and the optimization superiority of the EO algorithms. Three asymmetry numerical and practical cases are studied to validate the efficiency of the proposed EO-BRB approach.

Water regulation caused by enzymes, such as carbonic anhydrase (CA), changes the water status, making it difficult to diagnose water deficit using leaf water potential (ψL) or stomatal conductance (gs). Therefore, new methods for timely and accurately determining plant water status should be established. In this study, CA activity, ψL, leaf tensity (Td), photosynthetic characteristics and plant growth of Brassica napus L. seedlings under drought and subsequent rewatering were analysed. Results indicated that Td could reflect the plant water status better than ψL or gs and played an important role in the photosynthesis of B. napus. B. napus exhibited good restorability at the 40 g L−1 polyethylene glycol level. The rewatering strategy for B. napus was excellent at 40 g L−1 (−0.15 MPa) →20 g L−1 (−0.11 MPa). Td could be used for the rapid determination of water requirement information in B. napus during winter drought period.

Physically based multispectral image simulation consists of sensor system modeling, bottom-of-atmosphere (BOA) image generation, and top-of-atmosphere (TOA) image calculation. TOA radiance images are usually generated using a lookup table (LUT) for computational efficiency, which is calculated by means of atmospheric radiative transfer codes with different combination of input variables, including viewing zenith, solar zenith, and relative azimuth angles; visibility; columnar water vapor; and ground elevation. In this paper, a new strategy is proposed for TOA radiance image simulation, where transmitted surface radiance and atmospheric radiance at the TOA are calculated, respectively, to improve accuracy as well as efficiency. The transmitted surface radiance image is obtained from pixel-by-pixel calculation of BOA radiance and path transmittance. In calculating the atmospheric radiance of TOA, two LUTs are built for the emitted and the scattered radiance from each atmospheric layer, respectively. The effects of visibility and columnar water vapor on the atmospheric radiance are characterized by means of an equivalent path transmittance, which is related to the scene geometry as well as the thickness of atmospheric layer. In this way, when a new scene is simulated, except for three variables, i.e., viewing and solar zenith angles and atmospheric layer number, other parameters are set as constants in building the LUTs, enabling more combinations of input variables without adding excessive computational burden. Multispectral images in different bands with moderate spatial resolution are simulated and compared with the moderate-resolution imaging spectroradiometer (MODIS) images to demonstrate the accuracy and the usefulness of the proposed strategy.

Although microglial polarization and neuroinflammation are crucial cellular responses after traumatic brain injury, the fundamental regulatory and functional mechanisms remain insufficiently understood. As potent anti-inflammatory agents, the use of glucocorticoids in traumatic brain injury is still controversial, and their regulatory effects on microglial polarization are not yet known. In the present study, we sought to determine whether exacerbation of traumatic brain injury caused by high-dose dexamethasone is related to its regulatory effects on microglial polarization and its mechanisms of action. In vitro cultured BV2 cells and primary microglia and a controlled cortical impact mouse model were used to investigate the effects of dexamethasone on microglial polarization. Lipopolysaccharide, dexamethasone, RU486 (a glucocorticoid receptor antagonist), and ruxolitinib (a Janus kinase 1 antagonist) were administered. RNA-sequencing data obtained from a C57BL/6 mouse model of traumatic brain injury were used to identify potential targets of dexamethasone. The Morris water maze, quantitative reverse transcription-polymerase chain reaction, western blotting, immunofluorescence and confocal microscopy analysis, and TUNEL, Nissl, and Golgi staining were performed to investigate our hypothesis. High-throughput sequencing results showed that arginase 1, a marker of M2 microglia, was significantly downregulated in the dexamethasone group compared with the traumatic brain injury group at 3 days post–traumatic brain injury. Thus dexamethasone inhibited M1 and M2 microglia, with a more pronounced inhibitory effect on M2 microglia in vitro and in vivo. Glucocorticoid receptor plays an indispensable role in microglial polarization after dexamethasone treatment following traumatic brain injury. Additionally, glucocorticoid receptor activation increased the number of apoptotic cells and neuronal death, and also decreased the density of dendritic spines. A possible downstream receptor signaling mechanism is the GR/JAK1/STAT3 pathway. Overactivation of glucocorticoid receptor by high-dose dexamethasone reduced the expression of M2 microglia, which plays an anti-inflammatory role. In contrast, inhibiting the activation of glucocorticoid receptor reduced the number of apoptotic glia and neurons and decreased the loss of dendritic spines after traumatic brain injury. Dexamethasone may exert its neurotoxic effects by inhibiting M2 microglia through the GR/JAK1/STAT3 signaling pathway.

It is necessary to switch the control strategies for propulsion system frequently according to the changes of sea states in order to ensure the stability and safety of the navigation. Therefore, identifying the current sea state timely and effectively is of great significance to ensure ship safety. To this end, a reasoning model that is based on maximum likelihood evidential reasoning (MAKER) rule is developed to identify the propeller ventilation type, and the result is used as the basis for the sea states identification. Firstly, a data-driven MAKER model is constructed, which fully considers the interdependence between the input features. Secondly, the genetic algorithm (GA) is used to optimize the parameters of the MAKER model in order to improve the evaluation accuracy. Finally, a simulation is built to obtain experimental data to train the MAKER model, and the validity of the model is verified. The results show that the intelligent sea state identification model that is based on the MAKER rule can identify the propeller ventilation type more accurately, and finally realize intelligent identification of sea states.

A fully-polarimetric unitary multiple signal classification (UMUSIC) tomography algorithm is proposed, which can be used for acquiring high-resolution three-dimensional (3D) imagery, in a polarimetric multiple-input multiple-output synthetic aperture radar (MIMO-SAR) with a small number of baselines. In terms of the elevation resolution, UMUSIC provides an improvement over standard MUSIC by utilizing the conjugate of the complex sample data and converting the complex covariance matrix into a real matrix. The combination of UMUSIC and fully-polarimetric data permits a further reduction of the noise of the sample covariance matrix, which is obtained through pixel averaging of multiple two-dimensional (2D) images. Considering the consistency of four polarizations, this algorithm not only makes scattering centers have the same estimated height in four polarizations, but it also improves the estimation accuracy. Simulation results show that this algorithm outperforms the popular distributed compressed sensing (DCS). Image processing of measured data of an aircraft model using a multiple-input multiple-output synthetic aperture radar (MIMO-SAR) with six baselines is presented to validate the proposed algorithm.

Air pollution continues to attract more and more public attention. Space-based infrared sensors provide a measure to monitor air quality in large areas. In this paper, a band selection procedure of space-based infrared sensors is proposed for urban air pollutant detection, in which observation geometry, ground and atmosphere radiant characteristics, and sensor system noise are integrated. The physics-based atmospheric radiative transfer model is reviewed and used to calculate total spectral radiance at the sensor aperture. Spectral filters with different central wavelength and bandwidth are designed to calculate contrasts in various bands, which can be presented as a two-dimensional matrix. Minimal available bandwidth and signal-to-noise ratio threshold are set to characterize the impacts of the sensor system. In this way, the band with higher contrast is assumed to have better detection performance. The proposed procedure is implemented to analyze an optimal band for detecting four types of gaseous pollutants and discriminating aerosol particle pollution to demonstrate usefulness. Simulation results show that narrower bands tend to achieve better performance while the optimal band is related to the available minimal bandwidth and pollutant density. In addition, the bands that are near optimal can achieve similar performance.

In this work, we focus on sparse representation of two-dimensional (2-D) radar signatures for man-made targets. Based on the damped exponential (DE) model, a 2-D augmented state−space approach (ASSA) is proposed to estimate the parameters of scattering centers on complex man-made targets, i.e., the complex amplitudes and the poles in down-range and aspect dimensions. An augmented state−space approach is developed for pole estimation of down-range dimension. Multiple-range search strategy, which applies one-dimensional (1-D) state−space approach (SSA) to the 1-D data for each down-range cell, is used to alleviate the pole-pairing problem occurring in previous algorithms. Effectiveness of the proposed approach is verified by the numerical and measured inverse synthetic aperture radar (ISAR) data.

It is a challenge to distinguish between different cloud types because of the complexity and diversity of cloud coverage, which is a significant clutter source that impacts on target detection and identification from the images of space-based infrared sensors. In this paper, a novel strategy for cloud classification in wide-swath passive sensor images is developed, which is aided by narrow-swath active sensor data. The strategy consists of three steps, that is, the orbit registration, most matching donor pixel selection, and cloud type assignment for each recipient pixel. A new criterion for orbit registration is proposed so as to improve the matching accuracy. The most matching donor pixel is selected via the Euclidean distance and the square sum of the radiance relative differences between the recipient and the potential donor pixels. Each recipient pixel is then assigned a cloud type that corresponds to the most matching donor. The cloud classification of the Moderate Resolution Imaging Spectroradiometer (MODIS) images is performed with the aid of the data from Cloud Profiling Radar (CPR). The results are compared with the CloudSat product 2B-CLDCLASS, as well as those that are obtained using the method of the International Satellite Cloud Climatology Project (ISCCP), which demonstrates the superior classification performance of the proposed strategy.