Deep Diversity-Enhanced Feature Representation of Hyperspectral Images

In this paper, we study the problem of efficiently and effectively embedding the high-dimensional spatio-spectral information of hyperspectral (HS) images, guided by feature diversity. Specifically, based on the theoretical formulation that feature diversity is correlated with the rank of the unfolded kernel matrix, we rectify 3D convolution by modifying its topology to enhance the rank upper-bound. This modification yields a rank-enhanced spatial-spectral symmetrical convolution set (ReS 3-ConvSet), which not only learns diverse and powerful feature representations but also saves network parameters. Additionally, we also propose a novel diversity-aware regularization (DA-Reg) term that directly acts on the feature maps to maximize independence among elements. To demonstrate the superiority of the proposed ReS 3-ConvSet and DA-Reg, we apply them to various HS image processing and analysis tasks, including denoising, spatial super-resolution, and classification. Extensive experiments show that the proposed approaches outperform state-of-the-art methods both quantitatively and qualitatively to a significant extent. The code is publicly available at https://github.com/jinnh/ReSSS-ConvSet.

Observation on Efficacy of Selective Malposition Ligation Combined with Hemorrhoid and Fistula I in Complex Mixed Hemorrhoid

Objective

The efficacy of selective malposition ligation combined with hemorrhoid and fistula I prescription and the improvement of complications were assessed to improve surgical efficiency and safety.

Methods

423 patients undergoing complex mixed hemorrhoid surgery at different time points were included as research objects and enrolled into group A (malposition ligation), group B (selective malposition ligation), and group C (selective malposition ligation and hemorrhoid and fistula I), each with 141 cases.

Results

The scores for visual analogue scale (VAS), edema, and hemorrhage of group C 8h, 1 day, 2 days, 3 days, 5 days, and 7 days after surgery were all inferior to those in groups A and B, while that of group B was inferior to that in group A (P < .05). The duration of wound healing of group C (15.33 ± 2.78 days) was shorter than that of groups A (21.78 ± 3.22 days) and B (18.34 ± 3.01 days), and this duration of group B was shorter than that of group A (P < .05). The total effective rate of group C (96.45%) was superior to that of groups B (96.45%) and A (82.27%). The total effective rate of group B was superior to that of group A. The falling-off rate of the rubber ring in groups C and B was inferior to that in group A. The incidence of total complications in group C (9.93%) was inferior to that in groups B (30.50%) and A (30.50%), while that of group B was inferior to that in group A (P < .05).

Conclusion

After selective malposition ligation, the oral intake of hemorrhoid and fistula I could promote the recovery of wounds among patients with complex mixed hemorrhoids and reduce the incidence of postoperative hemorrhage and edema. Hence, it has significant clinical application values.

Hash Encoding and Brightness Correction in 3D Industrial and Environmental Reconstruction of Tidal Flat Neural Radiation

We present an innovative approach to mitigating brightness variations in the unmanned aerial vehicle (UAV)-based 3D reconstruction of tidal flat environments, emphasizing industrial applications. Our work focuses on enhancing the accuracy and efficiency of neural radiance fields (NeRF) for 3D scene synthesis. We introduce a novel luminance correction technique to address challenging illumination conditions, employing a convolutional neural network (CNN) for image enhancement in cases of overexposure and underexposure. Additionally, we propose a hash encoding method to optimize the spatial position encoding efficiency of NeRF. The efficacy of our method is validated using diverse datasets, including a custom tidal flat dataset and the Mip-NeRF 360 dataset, demonstrating superior performance across various lighting scenarios.

Target identification, and optimization of dioxygenated amide derivatives as potent antibacterial agents with FabH inhibitory activity

The enzyme FabH plays a critical role in the initial step of fatty acid biosynthesis, which is vital for the survival of bacteria. As a result, FabH has emerged as an appealing target for the development of novel antibacterial agents. In this study, employing the chemical proteomics method, we validated the previously identified skeleton amide derivatives bearing dioxygenated rings, potentially formed through metabolic processes. Building upon the proteomics findings, we then synthesized and evaluated 32 compounds containing N-heterocyclic amides for their antimicrobial activity for future optimizing the deoxygenated amides. Several compounds demonstrated potent antimicrobial properties with low toxicity, particularly compound 25, which exhibited remarkable potential as an agent with an MIC range of 1.25-3.13 μg/mL against the tested bacterial strains and an IC50 of 2.0 μM against E. coli-derived FabH. Furthermore, we evaluated nine analogues with relatively low MIC values through cytotoxicity and hemolytic activity assessments, Lipinski's rule-of-five criteria, and in silico ADMET predictions to ascertain their druggability potential. Notably, a detailed docking simulation was performed to investigate the binding interactions of compound 25 within the binding pocket of E. coli FabH, which encouragingly revealed strong binding interactions. Based on our findings, compound 25 emerges as the optimal candidate for in vivo therapy aimed at treating infected skin defects. Remarkably, the application of compound 25 demonstrated a significant reduction in the duration of wound infection and notably accelerated the healing process of infected wounds, achieving an impressive 94 % healing rate by day 10.

Zinc Transporters Serve as Prognostic Predictors and their Expression Correlates with Immune Cell Infiltration in Specific Cancer: A Pan-cancer Analysis

The disruption of zinc (Zn) homeostasis has been implicated in cancer development and progression through various signaling pathways. Maintaining intracellular zinc balance is crucial in the context of cancer. Human cells rely on two families of transmembrane transporters, SLC30A/ZNT and SLC39A/ZIP, to coordinate zinc homeostasis. While some ZNTs and ZIPs have been linked to cancer progression, limited information is available regarding the expression patterns of zinc homeostasis-related genes and their potential roles in predicting prognosis and developing therapeutic strategies for specific cancers. In this study, a systematic analysis was conducted to examine the expression of all genes from the SLC30A and SLC39A families at both mRNA and protein levels across different cancers. As a result, three SLC39A genes (SLC39A1, SLC39A4, and SLC39A8) were found to be significantly dysregulated in specific cancers, including cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), liver hepatocellular carcinoma (LIHC), pancreatic adenocarcinoma (PAAD), and kidney renal papillary cell carcinoma (KIRP). Moreover, the dysregulation of these genes was tightly associated with the prognosis of patients with those cancers. Furthermore, we found that the gene SLC39A8 exhibited the lowest mutation frequency in KIRP, whereas mutations in SLC39A4 were found to significantly impact overall survival (OS), disease-free (DF), and progress-free survival (PFS) in cancer patients, particularly in those with PAAD. Additionally, immune infiltration analysis revealed that SLC39A1, SLC39A4, and SLC39A8 may function as immune regulators in cancers. This provides new insights into understanding the complex relationship between zinc homeostasis and cancer progression.

Exploring the heterogeneity of community and function and correspondence of "species-enzymes" among three types of Daqu with different fermentation peak-temperature via high-throughput sequencing and metagenomics

The enzyme activity of Daqu is an important prerequisite for defining it as a Baijiu starter. However, little is known about the functional species related to enzymes in different types of Daqu at the metagenomic level. Therefore, we analyzed the differences in enzymatic properties, microbial composition and metabolic function of three types of Daqu, namely high-, medium- and low-temperature Daqus (HTD, MTD and LTD), by combining chemical feature and multi-dimensional sequencing. The results showed that both liquefaction, saccharification, fermentation and esterification powers were remarkably weaker in HTD compared to MTD and LTD. Totally, 30 bacterial and 5 fungal phyla were identified and significant differences in community structures were also observed among samples, with Brevibacterium/Microascus, Pseudomonas, and Lactobacillus/Saccharomycopsis identified as biomarkers for HTD, MTD and LTD, respectively. Additionally, the importance of deterministic assembly in bacterial communities was proportional to the fermentation peak-temperature, while stochastic assembly dominated in fungal ones. Metagenomics analysis indicated eukaryota (>80 %, mainly Ascomycota) predominated in HTD and MTD while bacteria (54.3 %, mainly Actinobacteriota) were more abundant in LTD. However, the functional profiles and pathways of MTD and LTD were more similar, and the synthesis and metabolism of carbohydrates and amino acids were the crucial biological functions of all samples. Finally, the relationship between species and enzymes in different samples was constructed and the functional species in LTD and MTD were more diverse than HTD, which elucidated the functional species associated with enzyme activity in each type of Daqu. These results will greatly enrich our understanding of the core functional species in three typical Daqu, which provide available information for rational regulation of Daqu quality and the Baijiu fermentation.

Lycium barbarum polysaccharide promotes the immunoprotective effects of a recombinant Lactobacillus plantarum vaccine expressing the Trichinella spiralis cathepsin F-like protease 1 gene

Trichinellosis caused by Trichinella spiralis (T. spiralis) is a zoonotic disease that poses a substantial risk to human health. At present, vaccines used to prevent trichinellosis are effective, but the production of antibody levels and immunogenicity are low. Adjuvants can increase antibody levels and vaccine immunogenicity. As a result, it is critical to develop an effective adjuvant for the T. spiralis vaccine. Recent research has shown that traditional Chinese medicine polysaccharides with low-toxicity and biodegradability can act as adjuvants in vaccines. In this study, BALB/c mice were orally inoculated with a recombinant Lactobacillus plantarum (L. plantarum) vaccine expressing the T. spiralis cathepsin F-like protease 1 gene (rTs-CPF1), which was given three times at 10-day intervals. Lycium barbarum polysaccharide (LBP) was administered orally for 37 days. At 37 days after the first immunization, mice were infected with 350 T. spiralis muscle larvae (ML). Specific IgG and sIgA antibody levels against the T. spiralis CPF1 protein were increased in mice immunized with rTs-CPF1+LBP compared to those immunized with rTs-CPF1 alone. Furthermore, LBP increased IFN-γ and IL-4 expression levels, and the number of intestinal and intramuscular worms was significantly reduced in the rTs-CPF1+LBP group compared to that in the rTs-CPF1 group. In the rTs-CPF1+LBP group, the reduction rates of adult worms and muscle larvae were 47.31 % and 68.88 %, respectively. To summarize, LBP promotes the immunoprotective effects of the T. spiralis vaccine and may be considered as a novel adjuvant in parasitic vaccines.

Manganese Enhances the Osteogenic Effect of Silicon-Hydroxyapatite Nanowires by Targeting T Lymphocyte Polarization

Biomaterials encounter considerable challenges in extensive bone defect regeneration. The amelioration of outcomes may be attainable through the orchestrated modulation of both innate and adaptive immunity. Silicon-hydroxyapatite, for instance, which solely focuses on regulating innate immunity, is inadequate for long-term bone regeneration. Herein, extra manganese (Mn)-doping is utilized for enhancing the osteogenic ability by mediating adaptive immunity. Intriguingly, Mn-doping engenders heightened recruitment of CD4+ T cells to the bone defect site, concurrently manifesting escalated T helper (Th) 2 polarization and an abatement in Th1 cell polarization. This consequential immune milieu yields a collaborative elevation of interleukin 4, secreted by Th2 cells, coupled with attenuated interferon gamma, secreted by Th1 cells. This orchestrated interplay distinctly fosters the osteogenesis of bone marrow stromal cells and effectuates consequential regeneration of the mandibular bone defect. The modulatory mechanism of Th1/Th2 balance lies primarily in the indispensable role of manganese superoxide dismutase (MnSOD) and the phosphorylation of adenosine 5'-monophosphate-activated protein kinase (AMPK). In conclusion, this study highlights the transformative potential of Mn-doping in amplifying the osteogenic efficacy of silicon-hydroxyapatite nanowires by regulating T cell-mediated adaptive immunity via the MnSOD/AMPK pathway, thereby creating an anti-inflammatory milieu favorable for bone regeneration.

Diosbulbin C, a novel active ingredient in Dioscorea bulbifera L. extract, inhibits lung cancer cell proliferation by inducing G0/G1 phase cell cycle arrest

BACKGROUND

Despite the critical progress of non-small cell lung cancer (NSCLC) therapeutic approaches, the clinical outcomes remain considerably poor. The requirement of developing novel therapeutic interventions is still urgent. In this study, we showed for the first time that diosbulbin C, a natural diterpene lactone component extracted from traditional Chinese medicine Dioscorea bulbifera L., possesses high anticancer activity in NSCLC.

METHODS

A549 and NCI-H1299 cells were used. The inhibitory effects of the diosbulbin C on NSCLC cell proliferation were evaluated using cytotoxicity, clone formation, EdU assay, and flow cytometry. Network pharmacology methods were used to explore the targets through which the diosbulbin C inhibited NSCLC cell proliferation. Molecular docking, qRT-PCR, and western blotting were used to validate the molecular targets and regulated molecules of diosbulbin C in NSCLC.

RESULTS

Diosbulbin C treatment in NSCLC cells results in a remarkable reduction in cell proliferation and induces significant G0/G1 phase cell cycle arrest. AKT1, DHFR, and TYMS were identified as the potential targets of diosbulbin C. Diosbulbin C may inhibit NSCLC cell proliferation by downregulating the expression/activation of AKT, DHFR, and TYMS. In addition, diosbulbin C was predicted to exhibit high drug-likeness properties with good water solubility and intestinal absorption, highlighting its potential value in the discovery and development of anti-lung cancer drugs.

CONCLUSIONS

Diosbulbin C induces cell cycle arrest and inhibits the proliferation of NSCLC cells, possibly by downregulating the expression/activation of AKT, DHFR, and TYMS.

Expression of Ferroptosis-Related Proteins Glutathione Peroxidase 4, Nuclear Factor Erythroid 2-Related Factor 2, and Solute Carrier Family 7 Member 11 in Gastric Cancer Patients

BACKGROUND/AIMS

The aim of this study was to investigate the expression of ferroptosis-related targets glutathione peroxidase 4, nuclear factor erythroid 2-related factor 2, and solute carrier family 7 member 11 in gastric cancer and the correlation between their expression and the clinicopathological characteristics and prognosis of gastric cancer patients.

MATERIALS AND METHODS

Forty-two gastric cancer samples and paracancerous samples were included, and all cases were detected with glutathione peroxidase 4, nuclear factor erythroid 2-related factor 2, and solute carrier family 7 member 11 by immunohistochemistry. Six gastric cancer cell lines and 1 normal gastric epithelial cell were stably cultured, and the expression of target genes of different cell lines was detected using western blot and polymerase chain reaction. Public data were downloaded from the database, and analyses were performed by software including Statistical Package for the Social Sciences and Prism.

RESULTS

A high glutathione peroxidase 4 expression level was found in 7 (16.67%) cancer tissues and 0 (0.00%) paracancerous tissues (P = .012). Nuclear factor erythroid 2-related factor 2 was upregulated in 23 (54.76%) cancer tissues and 2 (4.76%) paracancerous tissues (P < .001). Solute carrier family 7 member 11 showed increased expression in 4 (9.52%) cancer tissues and 1 (2.38%) paracancerous tissue (P = .356). No significant association existed between their expression and the clinicopathological characteristics and prognosis of gastric cancer patients. Glutathione peroxidase 4 and nuclear factor erythroid 2-related factor 2 expressions were higher in all 6 gastric cancer cell lines compared to normal gastric epithelial cells.

CONCLUSION

Glutathione peroxidase 4 and nuclear factor erythroid 2-related factor 2 expressions were significantly higher in gastric cancer, which may be potential biomarkers of gastric cancer.

Paeonol impacts ovarian cancer cell proliferation, migration, invasion and apoptosis via modulating the transforming growth factor beta/smad3 signaling pathway

Paeonol (2-hydroxy-4-methoxyphenylacetophenone) is a natural phenolic component isolated from the root bark of peony with multiple pharmacological activities and has been proven to have anti-cancer effects. The objective of this study is to investigate the influence mechanism of paeonol on the proliferatory and apoptotic activities of ovarian cancer (OC) cells by modulating the transforming growth factor beta (TGF-β)/Smad3 pathway. The SKOV3 cells were pretreated with various concentrations of paeonol (0, 25, 50, 100, 200, 400 μg/mL) for 48 hours to determine the optimal experimental concentration of paeonol. Following this, the TGF-β overexpression vector was constructed and transfected into the SKOV3 cells. The assessment of cell proliferation, invasion, and migration was conducted through MTT, colony formation, flow cytometry, transwell, and wound-healing experiments. The detection of TGF-β/Smad3 pathway-related proteins and apoptosis-related proteins (B-cell lymphoma (Bcl-2) Bcl-2-associated X protein (Bax)) was performed using Western blot analysis. Paeonol exhibited a significant inhibitory effect on SKOV3 cell viability when administered at concentrations ranging from 50-400 μg/mL, with an IC50 value of 200 μg/mL. Within the concentration range of 50 to 200 μg/mL, paeonol exhibited a dose-dependent effect on the progression of SKOV3 cells, including a reduction in the anti-apoptotic protein Bcl-2, an increase in the pro-apoptotic protein Bax (P<0.05), inhibition of cell migration and invasion (P<0.05), and promotion of cell apoptosis (P<0.05), particularly at a concentration of 200 μg/mL. These effects were found to be more pronounced. The aforementioned effects of paeonol can be ascribed to its inhibition of the TGFβ/Smad3 pathway, according to a mechanistic viewpoint. It is noteworthy that the inhibitory impact of paeonol on SKOV3 cell progression is counteracted by the elevation of TGF-β levels following overexpression. We conclude that paeonol exerts regulatory effects on the TGF-β/Smad3 pathway, leading to the inhibition of proliferation, migration, and invasion of OC cells, thereby attenuating malignant behavior of cancer cells.

Multisensory stimulation bundles on sleep and neurobehavioral development in the first year after birth in very preterm infants: a randomized crossover controlled study protocol

BACKGROUND

Disrupted sleep is believed to contribute to short- and long-term neurodevelopmental problems in very preterm infants (VPIs). This study presents a protocol for an evaluator-blinded, randomized crossover trial. It aims to assess the sleep efficiency of hospitalized VPIs by providing multisensory stimulation bundles. Furthermore, it aims to observe the intervention impacts on sleep during hospitalization of the VPIs and their sleep and neurodevelopmental outcomes during the first year of post-discharge follow-up.

METHODS

The study will be conducted in the neonatology department of a tertiary pediatric teaching hospital. All the eligible VPIs will undergo two types of care in random order: "standard care" (2 weeks) and "standard care plus multisensory stimulation bundles," each lasting 2 weeks. A generated list of random numbers will be used for case sequence allocation. Sleep outcomes will be evaluated using the Actiwatch-2 Actigraph. Moreover, the amplitude-integrated electroencephalography and the Griffiths Mental Development Scales will be used to measure the neurodevelopmental outcomes during hospitalization and in the first year of follow-up of the VPIs.

DISCUSSION

The intervention protocol of this study differs from that of other traditional interventions by producing precise and consistent supportive stimulations, similar to maternal tactile, auditory, posture, and visual effects for hospitalized VPIs. This protocol could be an effective measure to facilitate sleep and early neurodevelopment of VPIs. The expected outcomes will help confirm the implementation and generalization of the multisensory stimulation bundles' care protocol in neonatology departments. We expect that the study will positively impact hospitalized VPIs, especially in their sleep and early neurodevelopmental outcomes. It will also provide a new perspective regarding parent and infant interaction strategies, particularly for newborn intensive care units that limit visits because of the global spread of COVID-19.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR 2200059099. Registered on 25 April 2022, https://www.chictr.org.cn/showproj.html?proj=166980 ; the Hospital Research Ethics Committee (approval number: SCMCIRB-K2021086-1, Version 01), approved on 21 January 2022.

Research on composite fault diagnosis technology of underwater vehicle actuator with positioning error constraint

When diagnosing the composite fault of the actuator, the characteristics of the motion force of the underwater vehicle are not analyzed, and there are diagnostic errors, resulting in the low accuracy of the diagnosis technology. In order to solve this problem and improve the operation safety of underwater vehicle actuators, this paper proposes a compound fault diagnosis technology for underwater vehicle actuators under positioning error constraints. Analyze the motion force of the underwater robot actuator, control the motion of the underwater robot actuator according to the analysis results, and extract real-time data parameters according to the control results. Under the constraint of positioning error, the composite fault features of the underwater robot actuator are divided, and the diagnosis model is built according to the deep fusion of the features to complete the fault diagnosis. The experimental results show that the technology can diagnose the composite fault data of the actuator, and the positioning error of the horizontal axis and the horizontal axis can be significantly improved, which can improve the diagnosis effect of the composite fault of the actuator and to the improvement of underwater robot running safety of actuators provide certain reference.

A Robust and Integrated Visual Odometry Framework Exploiting the Optical Flow and Feature Point Method

In this paper, we propose a robust and integrated visual odometry framework exploiting the optical flow and feature point method that achieves faster pose estimate and considerable accuracy and robustness during the odometry process. Our method utilizes optical flow tracking to accelerate the feature point matching process. In the odometry, two visual odometry methods are used: global feature point method and local feature point method. When there is good optical flow tracking and enough key points optical flow tracking matching is successful, the local feature point method utilizes prior information from the optical flow to estimate relative pose transformation information. In cases where there is poor optical flow tracking and only a small number of key points successfully match, the feature point method with a filtering mechanism is used for posing estimation. By coupling and correlating the two aforementioned methods, this visual odometry greatly accelerates the computation time for relative pose estimation. It reduces the computation time of relative pose estimation to 40% of that of the ORB_SLAM3 front-end odometry, while ensuring that it is not too different from the ORB_SLAM3 front-end odometry in terms of accuracy and robustness. The effectiveness of this method was validated and analyzed using the EUROC dataset within the ORB_SLAM3 open-source framework. The experimental results serve as supporting evidence for the efficacy of the proposed approach.

Mineralization of Few-Layer Graphene Made It Bioavailable in Chlamydomonas reinhardtii

Numerous studies have emphasized the toxicity of graphene-based nanomaterials to algae, however, the fundamental behavior and processes of graphene in biological hosts, including its transportation, metabolization, and bioavailability, are still not well understood. As photosynthetic organisms, algae are key contributors to carbon fixation and may play an important role in the fate of graphene. This study investigated the biological fate of 14C-labeled few-layer graphene (14C-FLG) in Chlamydomonas reinhardtii (C. reinhardtii). The results showed that 14C-FLG was taken up by C. reinhardtii and then translocated into its chloroplast. Metabolomic analysis revealed that 14C-FLG altered the metabolic profiles (including sugar metabolism, fatty acid, and tricarboxylic acid cycle) of C. reinhardtii, which promoted the photosynthesis of C. reinhardtii and then enhanced their growth. More importantly, the internalized 14C-FLG was metabolized into 14CO2, which was then used to participate in the metabolic processes required for life. Approximately 61.63%, 25.31%, and 13.06% of the total radioactivity (from 14CO2) was detected in carbohydrates, lipids, and proteins of algae, respectively. Overall, these results reveal the role of algae in the fate of graphene and highlight the potential of available graphene in bringing biological effects to algae, which helps to better assess the environmental risks of graphene.

Supramolecular Transistors with Quantum Interference Effect

The charge transport through supramolecular junctions exhibits unique quantum interference (QI) effects, which provide an opportunity for the design of supramolecular transistors. Benefiting from the configuration dependence of QI, configuration control of the supramolecular assemblies to demonstrate the QI features is a key but challenging step. In this work, we fabricated the supramolecular transistors and investigated the charge transport through the conducting channel of the individual π-stacked thiophene/phenylene co-oligomers (TPCOs) using the electrochemically gated scanning tunneling microscope break junction technique. We controlled the configuration of the supramolecular channel and switched the QI features between the anti-resonance and resonance states of the supramolecular channels. We observed the supramolecular transistor with its on/off ratio above 103 (∼1300), a high gating efficiency of ∼165 mV/dec, a low off-state leakage current of ∼30 pA, and the channel length scaled down to <2.0 nm. Density functional theory calculations suggested that the QI features in π-stacked TPCOs vary depending on the supramolecular architecture and can be manipulated efficiently by fine-tuning the supramolecular configurations. This work reveals the potential of the supramolecular channels for molecular electronics and provides a fundamental understanding of intermolecular charge transport.

Treatment of pregnant mice with ABZ had no effect on the immune response of their offspring infected with Trichinella spiralis

Trichinellosis is a food-borne parasitic disease with a worldwide distribution that not only endangers human health but also leads to economic loss. Infection of pregnant animals with Trichinella spiralis (T. spiralis) may lead to abortion and other adverse consequences, so it is necessary to treat the infection during pregnancy. Albendazole (ABZ) is an effective therapeutic drug for adult T. spiralis worms. The safety of this drug during pregnancy, especially whether it has any effect on offspring, should be fully evaluated. A change in the immune response to T. spiralis in the offspring of pregnant mice treated with ABZ may lead to a difference in susceptibility to T. spiralis compared to that of the offspring of normal mice. However, the safety of ABZ treatment in pregnant mice and the effects on the immune response and susceptibility of their offspring to T. spiralis are poorly understood. Therefore, we assessed whether maternal ABZ treatment during pregnancy affects the immune response or susceptibility to T. spiralis in infected offspring. In this study, mice were infected with T. spiralis at 10 days of pregnancy and treated with ABZ at 3 days post infection (dpi), and the specific immune response in the pregnant mice and the survival rate and worm burden of their 6-week-old offspring after T. spiralis infection were examined. The results showed that the antiparasitic immune response in pregnant mice was activated by T. spiralis infection. Treatment of pregnant mice with ABZ increased the percentage of CD4 + T cells. The percentages of Th2 and Treg cells in the PP, MLN and spleen of pregnant mice in the infection group were significantly increased compared with those of normal mice. ABZ treatment during pregnancy promoted the Th2 and Treg immune responses in pregnant mice infected with T. spiralis. The transcriptional levels of the Th2 and Treg cytokines IL-4, IL-5, IL-13, and TGF-β in the small intestine, MLN and spleen of pregnant mice in the treatment group were significantly higher than those of pregnant mice in the T. spiralis infection only group. The results indicated that ABZ treatment did not cause abortion in pregnant mice or affect the survival rate of their offspring. Furthermore, treatment of pregnant mice with ABZ had no significant effect on the above immune responses in their T. spiralis-infected offspring compared to those of T. spiralis-infected offspring of mice in the normal group. The results also indicated that treatment of pregnant mice infected with T. spiralis with ABZ shifted the immune response to a Th2- and Treg-skewed immune response and that this drug had no effects on the offspring survival rate, immune response or worm burden after T. spiralis infection. This study further indicated that ABZ administration to treat T. spiralis infection in pregnant mice is safe for the select immune response and susceptibility of their offspring.

Investigation of Diagnostic and Prognostic Value of CLEC4M of Non-Small Cell Lung Carcinoma Associated with Immune Microenvironment

Purpose

C-type lectin domain family 4 member M (CLEC4M) has been found to be involved in the occurrence and development of cancer, but its role in NSCLC remains to be fully explored. Our work aims to evaluate the diagnostic and prognostic value of CLEC4M in NSCLC and to investigate the underlying mechanisms of CLEC4M in the immune microenvironment of NSCLC.

Methods

Integrating publicly accessible data and clinical tissue samples to verify the expression of CLEC4M in NSCLC. The diagnostic value of CLEC4M was determined by receiver operating characteristic (ROC) curve. Kaplan-Meier survival analysis, nomogram plot, univariate and multivariate Cox regression models were performed to evaluate the prognostic impact of CLEC4M on NSCLC patients. The correlation between CLEC4M and tumor immune infiltration was estimated using TIMER and UALCAN databases. Functional assessments including GO, KEGG pathway and GSEA analyses were implemented to illustrate the potential mechanisms of CLEC4M in NSCLC.

Results

CLEC4M was significantly downregulated in NSCLC tissue, as confirmed by immunohistochemistry of clinical tissues. The high AUC value of ROC curves demonstrated the diagnostic accuracy of CLEC4M in NSCLC. Additionally, low CLEC4M expression was associated with poor survival in NSCLC patients. Furthermore, CLEC4M was found to be significantly associated with tumor immune infiltration, and CLEC4M may be involved in immune activation and proliferation inhibition through the functional assessment, suggesting that CLEC4M may be a therapeutic target for NSCLC patients.

Conclusion

Our findings reveal CLEC4M is significantly downregulated in NSCLC tissues, and illustrate the diagnostic and prognostic value of CLEC4M in NSCLC, as well as its potential serve as an immune-related therapeutic target.

Interaction of Graphitic Carbon Nitride with Cell Membranes: Probing Phospholipid Extraction and Lipid Bilayer Destruction

Understanding how nanomaterials interact with cell membranes has important implications for ecotoxicology and human health. Here, we investigated the interactions between graphitic carbon nitride (g-C₃N₄, CN) and red blood cells, a plausible contact target for nanoparticles when they enter the bloodstream. Through a hemolysis assay, the cytotoxicity of CN derived from different precursors was quantitatively assessed, which is highly related to the surface area of CN. Reactive oxygen species (ROS) generation and lipid peroxidation detection confirmed that CN causes rapid cell membrane rupture by a physical interaction mechanism rather than ROS-related chemical oxidation. Dye leakage assay and theoretical simulation indicated that the less-layered CN is prone to folding inward to wrap and extract lipid molecules from cell membranes. The electron-rich inherent pores of CN play a dominant role in capturing the headgroups of phospholipids, whereas the hydrophobic interaction is critical for the anchoring of lipid tails. Our further experimental evidence demonstrated that the destructive extraction of phospholipids from cell membranes by CN occurs primarily in the outer leaflet, and phosphatidylcholine is the most easily extracted lipid. Moreover, the formation of protein corona on CN was found to decrease the nonspecific interactions but increase steric repulsion, thus mitigating CN cytotoxicity. Overall, our data provide a molecular basis for CN's cytotoxicity.

Single-Stage Underwater Target Detection Based on Feature Anchor Frame Double Optimization Network

OBJECTIVE

The shallow underwater environment is complex, with problems of color shift, uneven illumination, blurring, and distortion in the imaging process. These scenes are very unfavorable for the reasoning of the detection network. Additionally, typical object identification algorithms struggle to maintain high resilience in underwater environments due to picture domain offset, making underwater object detection problematic.

METHODS

This paper proposes a single-stage detection method with the double enhancement of anchor boxes and features. The feature context relevance is improved by proposing a composite-connected backbone network. The receptive field enhancement module is introduced to enhance the multi-scale detection capability. Finally, a prediction refinement strategy is proposed, which refines the anchor frame and features through two regressions, solves the problem of feature anchor frame misalignment, and improves the detection performance of the single-stage underwater algorithm.

RESULTS

We achieved an effect of 80.2 mAP on the Labeled Fish in the Wild dataset, which saves some computational resources and time while still improving accuracy. On the original basis, UWNet can achieve 2.1 AP accuracy improvement due to the powerful feature extraction function and the critical role of multi-scale functional modules. At an input resolution of 300 × 300, UWNet can provide an accuracy of 32.4 AP. When choosing the number of prediction layers, the accuracy of the four and six prediction layer structures is compared. The experiments show that on the Labeled Fish in the Wild dataset, the six prediction layers are better than the four.

CONCLUSION

The single-stage underwater detection model UWNet proposed in this research has a double anchor frame and feature optimization. By adding three functional modules, the underwater detection of the single-stage detector is enhanced to address the issue that it is simple to miss detection while detecting small underwater targets.

Deep Posterior Distribution-Based Embedding for Hyperspectral Image Super-Resolution

In this paper, we investigate the problem of hyperspectral (HS) image spatial super-resolution via deep learning. Particularly, we focus on how to embed the high-dimensional spatial-spectral information of HS images efficiently and effectively. Specifically, in contrast to existing methods adopting empirically-designed network modules, we formulate HS embedding as an approximation of the posterior distribution of a set of carefully-defined HS embedding events, including layer-wise spatial-spectral feature extraction and network-level feature aggregation. Then, we incorporate the proposed feature embedding scheme into a source-consistent super-resolution framework that is physically-interpretable, producing PDE-Net, in which high-resolution (HR) HS images are iteratively refined from the residuals between input low-resolution (LR) HS images and pseudo-LR-HS images degenerated from reconstructed HR-HS images via probability-inspired HS embedding. Extensive experiments over three common benchmark datasets demonstrate that PDE-Net achieves superior performance over state-of-the-art methods. Besides, the probabilistic characteristic of this kind of networks can provide the epistemic uncertainty of the network outputs, which may bring additional benefits when used for other HS image-based applications. The code will be publicly available at https://github.com/jinnh/PDE-Net.

Mutation detection dual correlation filter with an object-awareness module for real-time target tracking

Discriminative correlation filter (DCF) based methods have recently been widely used for visual tracking tasks. The adaptive spatiotemporal-regulation based tracker (AutoTrack) can only partially solve some limitations of the DCF framework including filter degradation and the boundary effect, but its application scenarios need to be broadened, and performance improvements are also required. To further surmount these difficulties, this paper provides an object-awareness-module based mutation detection dual correlation filter (MDDCF-OAM). The main innovation points of this work are: (1) an object-mask based context enhancer is proposed to formulate a more robust appearance model; (2) a dual filter training-learning structure is adopted to allow the dual filters to restrict each other and suppress the filter degradation effect; (3) a Gaussian label map is updated with the refined joint response map to detect and attenuate the response mutation effects. Exhaustive experiments have been conducted to test the efficiency of the suggested MDDCF-OAM on four benchmarks, namely, OTB2015, UAV123, TC128, and VOT2019. The results indicate that: (1) the introduced MDDCF-OAM surpasses nine state-of-the-art trackers; (2) the MDDCF-OAM has a real-time speed of 32 frames per second, which is sufficient for target tracking tasks in numerous scenarios, especially unmanned aerial vehicles and camera tracking.

The Role and Therapeutic Potential of Macropinocytosis in Cancer

Macropinocytosis, a unique endocytosis pathway characterized by nonspecific internalization, has a vital role in the uptake of extracellular substances and antigen presentation. It is known to have dual effects on cancer cells, depending on cancer type and certain microenvironmental conditions. It helps cancer cells survive in nutrient-deficient environments, enhances resistance to anticancer drugs, and promotes invasion and metastasis. Conversely, overexpression of the RAS gene alongside drug treatment can lead to methuosis, a novel mode of cell death. The survival and proliferation of cancer cells is closely related to macropinocytosis in the tumor microenvironment (TME), but identifying how these cells interface with the TME is crucial for creating drugs that can limit cancer progression and metastasis. Substantial progress has been made in recent years on designing anticancer therapies that utilize the effects of macropinocytosis. Both the induction and inhibition of macropinocytosis are useful strategies for combating cancer cells. This article systematically reviews the general mechanisms of macropinocytosis, its specific functions in tumor cells, its occurrence in nontumor cells in the TME, and its application in tumor therapies. The aim is to elucidate the role and therapeutic potential of macropinocytosis in cancer treatment.

Uptake Route Altered the Bioavailability of Graphene in Misgurnus anguillicaudatus: Comparing Waterborne and Sediment Exposures

Numerous studies on the bioavailability of graphene-based nanomaterials relate to the water-only exposure route. However, the sediment exposure route should be the most important pathway for benthic organisms to ingest graphene, while to date little work on the bioavailability of graphene in benthic organisms has been explored. In this study, with the help of carbon-14-labeled few-layer graphene (¹⁴C-FLG), we quantificationally compared the bioaccumulation, biodistribution, and elimination kinetics of ¹⁴C-FLG in loaches via waterborne and sediment exposures. After 72 h of exposure, the accumulated ¹⁴C-FLG in loaches exposed via waterborne was 14.28 μg/g (dry mass), which was 3.18 times higher than that (4.49 μg/g) exposed via sediment. The biodistribution results showed that, compared to waterborne exposure, sediment exposure remarkably facilitated the transport of ¹⁴C-FLG from the gut into the liver, which made it difficult to be excreted. Although ¹⁴C-FLG did not cause significant hepatotoxicity, the disruption of intestinal microbiota homeostasis, immune response, and several key metabolic pathways in the gut were observed, which may be due to the majority of ¹⁴C-FLG being accumulated in the gut. Overall, this study reveals the different bioavailabilities of graphene in loaches via waterborne and sediment exposures, which is helpful in predicting its bioaccumulation capability and trophic transfer ability.

Super-resolution reconstruction of biometric features recognition based on manifold learning and deep residual network

BACKGROUND AND OBJECTIVE

In daily life, face information has the characteristics of uniqueness and universality. However, in a real-world scene, the image information of the face acquired by the acquisition device often contains noises such as blurring and sharpening. As such, super-resolution reconstruction of face features recognition based on manifold learning is proposed in this paper.

METHODS

We reconstruct low-resolution facial expression images, introduce a simplified residual block network and manifold learning, and propose joint supervision through a new hybrid loss function, which not only retains the color and characteristics of the image, but also retains the high-frequency information. The ResNet50 network uses the weight feature of information entropy to optimize the information of the pooling layer, and the esNet50 network uses the improved PSO algorithm to optimize the initial weight of the error back-propagation phase.

RESULTS

In the case of inputting extremely low resolution (6 × 6) facial expression images, the accuracy rate is increased by 9.091%. The accuracy of the high-resolution facial expressions after reconstruction with a size of 12×12 is 96.970%. The accuracy rate for happy expressions is 100%, the accuracy rate for anger, disgust, sadness, and surprise recognition is 97%, the accuracy rate for contempt is 94%, and the accuracy rate for fear is 88%.

CONCLUSIONS

The experimental results verify the feasibility and superiority of the system, and effectively improve the accuracy of low-resolution facial expressions.

Anticancer Activity of Erianin: Cancer-Specific Target Prediction Based on Network Pharmacology

Erianin is a major bisbenzyl compound extracted from Dendrobium chrysotoxum Lindl., an important traditional Chinese herb. In recent years, a growing body of evidence has proved the potential therapeutic effects of erianin on various cancers, including hepatoma, melanoma, non-small-cell lung carcinoma, myelogenous leukemia, breast cancer, and osteosarcoma. Especially, the pharmacological activities of erianin, such as antioxidant and anticancer activity, have been frequently demonstrated by plenty of studies. In this study, we firstly conducted a systematic review on reported anticancer activity of erianin. All updated valuable information regarding the underlying action mechanisms of erianin in specific cancer was recorded and summarized in this paper. Most importantly, based on the molecular structure of erianin, its potential molecular targets were analyzed and predicted by means of the SwissTargetPrediction online server (http://www.swisstargetprediction.ch). In the meantime, the potential therapeutic targets of 10 types of cancers in which erianin has been proved to have anticancer effects were also predicted via the Online Mendelian Inheritance in Man (OMIM) database (http://www.ncbi.nlm.nih.gov/omim). The overlapping targets may serve as valuable target candidates through which erianin exerts its anticancer activity. The clinical value of those targets was subsequently evaluated by analyzing their prognostic role in specific cancer using Kaplan-Meier plotter (http://Kmplot.com/analysis/) and Gene Expression Profiling Interactive Analysis (GEPIA) (http://gepia.cancer-pku.cn/). To better assess and verify the binding ability of erianin with its potential targets, molecular flexible docking was performed using Discovery Studio (DS). The valuable targets obtained from the above analysis and verification were further mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway using the Database for Annotation, Visualization and Integrated Discovery (DAVID) (http://david.abcc.ncifcrf.gov/) to explore the possible signaling pathways disturbed/regulated by erianin. Furthermore, the in silico prediction of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of erianin was also performed and provided in this paper. Overall, in this study, we aimed at 1) collecting all experiment-based important information regarding the anticancer effect and pharmacological mechanism of erianin, 2) providing the predicted therapeutic targets and signaling pathways that erianin might act on in cancers, and 3) especially providing in silico ADMET properties of erianin.

Facial expression recognition based on deep learning

BACKGROUND AND OBJECTIVE

Facial expression recognition technology will play an increasingly important role in our daily life. Autonomous driving, virtual reality and all kinds of robots integrated into our life depend on the development of facial expression recognition technology. Many tasks in the field of computer vision are based on deep learning technology and convolutional neural network. The paper proposes an occluded expression recognition model based on the generated countermeasure network. The model is divided into two modules, namely, occluded face image restoration and face recognition.

METHODS

Firstly, this paper summarizes the research status of deep facial expression recognition methods in recent ten years and the development of related facial expression database. Then, the current facial expression recognition methods based on deep learning are divided into two categories: Static facial expression recognition and dynamic facial expression recognition. The two methodswill be introduced and summarized respectively. Aiming at the advanced deep expression recognition algorithms in the field, the performance of these algorithms on common expression databases is compared, and the strengths and weaknesses of these algorithms are analyzed in detail.

DISCUSSION AND RESULTS

As the task of facial expression recognition is gradually transferred from the controlled laboratory environment to the challenging real-world environment, with the rapid development of deep learning technology, deep neural network can learn discriminative features, and is gradually applied to automatic facial expression recognition task. The current deep facial expression recognition system is committed to solve the following two problems: (1) Overfitting due to lack of sufficient training data; (2) In the real world environment, other variables that have nothing to do with expression bring interference problems.

CONCLUSION

From the perspective of algorithm, combining other expression models, such as facial action unit model and pleasure arousal dimension model, as well as other multimodal models, such as audio mode, 3D face depth information and human physiological information, can make expression recognition more practical.

Data-driven trajectory tracking control for autonomous underwater vehicle based on iterative extended state observer

In this study, we explore the precise trajectory tracking control problem of autonomous underwater vehicle (AUV) under the disturbance of the underwater environment. First, a model-free adaptive control (MFAC) is designed based on data-driven ideology and a full-form dynamic linearization (FFDL) method is utilized to online estimate time-varying parameter pseudo gradient (PG) to establish an equivalent data model of AUV motion. Second, the iterative extended state observer (IESO) scheme is designed to combine with FFDL-MFAC. Because the proposed novel controller is able to learn from repeated iterations, the proposed novel controller can estimate and compensate the model approximation error produced by external environmental unknown disturbance. Third, three-dimensional motion is decoupled into horizontal and vertical and a multi closed-loop control structure is designed that exhibits faster convergence rate and reduces sensitivity to parameter jumps than single closed-loop system. Finally, two simulation scenarios are designed featuring non external disturbance and Gaussian noise of signal-to-noise ratio of 90 dB. The simulation results reveal the superiority of FFDL. Furthermore, we adpot the technical parameters data of T-SEA I AUV to conduct numerical simulation, aunderwater trajectory as the tracking scenario and set waves to 0.5 m and current to 0.2 m/s to simulate Lv.2 ocean conditions of "International Ocean State Standard". The simulation results demonstrate the effectiveness and robustness of the proposed tracking control algorithm.

[Analysis of the performance of a multi-view fusion and active contour constraint based deep learning algorithm for ossicles segmentation on 10 μm otology CT]

Objective: To explore the performance of a deep learning algorithm that combined multi-view fusion with active contour constrained for ossicles segmentation on the 10 μm otology CT images. Methods: The 10 μm otology CT image data from 79 cases (56 cases were from volunteers and 23 cases were from specimens) were retrospectively collected in the Radiology Department of Beijing Friendship Hospital from October 2019 to December 2020. An annotation of malleus, incus, and stapes were conducted. Then the datasets were established and were divided into training set (n=55), validation set (n=8), and test set (n=16). Using the rapid localization of the region of interest combined with the precise segmentation algorithm, the malleus, incus and stapes were segmented and fused from three perspectives of coronal, sagittal and cross-sectional views. Besides, an active contour loss was designed simultaneously for the segmentation of stapes. Dice similarity coefficient (DSC) was used as the objective evaluation metric for the evaluation of the segmentation results. The inter group DSC of the proposed method was compared with that of the basic method and other methods. Results: The average DSC values of the multi-view fusion segmentation algorithm for malleus, incus and stapes reached up to 94.2%±2.7%, 94.6%±2.6% and 76.0%±5.5%, respectively. After adopting the constraint of active contour loss method, the average DSC of stapes was improved (76.4%±5.4% vs 76.0%±5.5%). The visualization results also demonstrated that the segmentation results of the stapes were more complete. Conclusions: Multi-view fusion algorithm based on 10 μm otology CT images can realize accurate segmentation of malleus and incus. Combined with the constraint of active contour loss method, the segmentation accuracy of stapes can be further improved.

Single-Molecule Electrochemical Transistors

Single-molecule electrochemical transistors are a type of novel molecular devices in which the tunneling current through the single-molecule junction is modulated by the electrochemical gate, and is considered a promising candidate to be employed in molecular integrated circuits for building the future "molecular computers." Benefiting from the particular interfacial electrical double layer, the current modulation process can be realized through direct orbital gating as well as electrochemical electron transfer driven by electrode potential, thus significantly enriching the functions of the transistor devices. This review focuses on the transfer characteristics and the performance of several typical types of single-molecule electrochemical transistors and the prospects for the fabrication toward integrated devices.

Robust face recognition based on multi-task convolutional neural network

PURPOSE

Due to the lack of prior knowledge of face images, large illumination changes, and complex backgrounds, the accuracy of face recognition is low. To address this issue, we propose a face detection and recognition algorithm based on multi-task convolutional neural network (MTCNN).

METHODS

In our paper, MTCNN mainly uses three cascaded networks, and adopts the idea of candidate box plus classifier to perform fast and efficient face recognition. The model is trained on a database of 50 faces we have collected, and Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measurement (SSIM), and receiver operating characteristic (ROC) curve are used to analyse MTCNN, Region-CNN (R-CNN) and Faster R-CNN.

RESULTS

The average PSNR of this technique is 1.24 dB higher than that of R-CNN and 0.94 dB higher than that of Faster R-CNN. The average SSIM value of MTCNN is 10.3% higher than R-CNN and 8.7% higher than Faster R-CNN. The Area Under Curve (AUC) of MTCNN is 97.56%, the AUC of R-CNN is 91.24%, and the AUC of Faster R-CNN is 92.01%. MTCNN has the best comprehensive performance in face recognition. For the face images with defective features, MTCNN still has the best effect.

CONCLUSIONS

This algorithm can effectively improve face recognition to a certain extent. The accuracy rate and the reduction of the false detection rate of face detection can not only be better used in key places, ensure the safety of property and security of the people, improve safety, but also better reduce the waste of human resources and improve efficiency.

Crown ether-based anion exchange membranes with highly efficient dual ion conducting pathways

Anion exchange membranes (AEMs) are a crucial constituent for alkaline fuel cells. As the core component of fuel cells, the low performance AEMs restrict the development and application of the fuel cells. Herein, the trade-off between the OH^- conductivity and dimensional stability was solved by constructing AEMs with adequate OH^- conductivity and satisfactory alkali resistance using Tröger's base (TB) poly (crown ether)s (PCEs) as the main chain, the embedded quaternary ammonium (QA) and Na⁺-functionalized crown ether units as the cationic group. Crown ether is an electron donator, and can capture Na⁺ to form Na⁺-functionalized crown ether units to conveniently transfer OH^- and significantly promote the alkaline stability of the AEMs. The influence of the Na⁺-functionalized crown ether units on the performance of AEMs was studied in detail. The PCEs based AEMs show an obvious hydrophobic-hydrophilic microphase separation. These features make them ideal platforms for the OH^- conduction applications. As expected, the as-prepared PCEs-QA-100% (100% is the degree of cross-linking) AEM with an ionic exchange capacity (IEC) of 2.07 meq g^-1 has a high OH^- conductivity of 159 mS cm^-1 at 80 °C. Furthermore, the membrane electrode assemblies fabricated using the PCEs-QA-100% AEM possess a maximum power density of 291 mW cm^-2 under the current density of 500 mA cm^-2.

Effect of heat input on interfacial characterization of the butter joint of hot-rolling CP-Ti/Q235 bimetallic sheets by Laser + CMT

Composite structures made of 2 mm-thick titanium and 10 mm-thick carbon steel are widely used in infrastructures such as long-distance gas transportation. However, cracking, which is caused by intermetallic compounds (ICs), is a dominate failure mode in welds of this structure. Thus, a common way to improve the in-service life of is reduce the number of ICs. In this paper, we employ a novel hybrid welding method to fabricate composite structures of TA₂ titanium and Q235 carbon steel. Specifically, Ti and carbon steel is welded by laser and double Cold Metal Transfer (CMT) welding, respectively. The microstructure near the interface of Ti and steel is then examined using SEM, EBSD, EDS, with emphasis on the ICs in terms of chemical elements and morphologies. Results show that FeTi and Fe₂Ti are the main ICs near the interface, and responsible for the failure of the welds. The effect of welding heat input on the formation of ICs is investigated as well. Results show that ICs are smaller when the heat input is low. Under low heat input circumstance, the tensile strength of the weld can reach up to 420 MPa.

First report of Diaporthe eres causing root rot of Coptis chinensis Franchet

Chongqing coptis (Coptis chinensis Franchet) industry produces more than 60% of the Chinese coptis crop, and has been exported to many countries and regions. Since 2008, root rot has become a serious and widespread disease on coptis plants in Shizhu county with an average incidence of 40%, and yield losses up to 67%. Symptomatic coptis plants showed stunted growth, with the fibrous roots and main roots having brown or black, rotten, necrotic lesions. To our knowledge, Fusarium solani, F. carminascens, F. oxysporum and F. tricinctum have been previously reported as pathogens of coptis root rot (Luo et al. 2014; Cheng et al. 2020; Wu et al. 2020), but non Fusarium pathogens has not been reported yet. In order to identify new pathogens, 33 diseased roots were collected from Shizhu (30°18'N, 108°30'E) in October 2019. Small samples (0.5 cm in length) were cut from the border between diseased and healthy tissue, and then put on PDA after surface sterilization. Cultures were incubated at 25°C in dark until fungal colonies were observed. After subculturing for 3 times, 3 out of 21 isolates yielded a similar type of fungal colony. White, aerial, fluffy mycelium were formed and reached 8.3 cm diameter within 7 days, and dark pigmentation developed in the centre. Colonies turned to gray with age, and abundant dark brown pycnidia and black stromata were formed at maturity. Alpha conidia were aseptate, hyaline, fusiform to ellipsoidal, often biguttulate, measuring (6.0-8.5)×(2.0-3.0) μm. Beta conidia were aseptate, hyaline, linear to hooked, measuring (18-30)×(1.0-1.5) μm (Figure S1). For further identification, a multigene phylogenetic analysis was carried out. The internal transcribed spacer (ITS), translation elongation factor 1ɑ (tef1-ɑ), histone H3 (his3), calmodulin (cal), and β-tubulin (tub2) gene regions were amplified with ITS1/ITS4, EF1-728F/EF1-986R, CYLH3F/H3-1b, CAL228F/CAL737R, T1/Bt2b (White et al. 1990; Glass and Donaldson 1995; Carbone and Kohn 1999; Crous et al. 2004). GenBank accession numbers of isolate H13 were MT463391 for the ITS region, MT975573 for tef1-ɑ, MT975574 for his3, MT975575 for cal, and MT975576 for tub2. BLAST results showed the ITS, tef1-ɑ, his3, cal and tub2 sequences revealed 99.82% (553/554 base pairs), 100% (347/347 base pairs), 100% (474/474 base pairs), 99.39% (486/489 base pairs), and 99.14% (803/810 base pairs) homology respectively with those of Diaporthe eres (MN816416.1, KU557616.1, KC343564.1, KU557595.1, and KY569366.1). Thus, H13 were identified as D. eres based on its morphological and molecular characteristics. Pathogenicity of D. eres in coptis was investigated using the H13 isolate (1 of the 3 isolates). The roots of 10 healthy 2-year-old coptis plants were individually inoculated with 5 ml of a 106 conidia/mL conidial suspension and sterilized water was used to mock inoculate. Thirty days after inoculation, most of the inoculated coptis roots showed dark brown and rotten root, similar to those observed in the field, whereas mock inoculated roots showed healthy. D. eres was recovered from symptomatic roots and identified based on morphology. To our knowledge, this is the first report of D. eres causing root rot of coptis not only in China but anywhere in the world.

Hyperspectral Image Super-Resolution via Deep Progressive Zero-Centric Residual Learning

This paper explores the problem of hyperspectral image (HSI) super-resolution that merges a low resolution HSI (LR-HSI) and a high resolution multispectral image (HR-MSI). The cross-modality distribution of the spatial and spectral information makes the problem challenging. Inspired by the classic wavelet decomposition-based image fusion, we propose a novel lightweight deep neural network-based framework, namely progressive zero-centric residual network (PZRes-Net), to address this problem efficiently and effectively. Specifically, PZRes-Net learns a high resolution and zero-centric residual image, which contains high-frequency spatial details of the scene across all spectral bands, from both inputs in a progressive fashion along the spectral dimension. And the resulting residual image is then superimposed onto the up-sampled LR-HSI in a mean-value invariant manner, leading to a coarse HR-HSI, which is further refined by exploring the coherence across all spectral bands simultaneously. To learn the residual image efficiently and effectively, we employ spectral-spatial separable convolution with dense connections. In addition, we propose zero-mean normalization implemented on the feature maps of each layer to realize the zero-mean characteristic of the residual image. Extensive experiments over both real and synthetic benchmark datasets demonstrate that our PZRes-Net outperforms state-of-the-art methods to a significant extent in terms of both 4 quantitative metrics and visual quality, e.g., our PZRes-Net improves the PSNR more than 3dB, while saving 2.3× parameters and consuming 15× less FLOPs. The code is publicly available at https://github.com/zbzhzhy/PZRes-Net.

Power efficient LED placement algorithm for indoor visible light communication

This paper proposes a novel power-efficient light-emitting diode (LED) placement algorithm for indoor visible light communication (VLC). In the considered model, the LEDs can be designedly placed for high power efficiency while satisfying the indoor communication and illumination requirements. This design problem is formulated as a power minimization problem under both communication and illumination level constraints. Due to the interactions among LEDs and the illumination uniformity constraint, the formulated problem is complex and non-convex. To solve the problem, we first transform the complex uniformity constraint into a series of linear constraints. Then an iterative algorithm is proposed to decouple the interactions among LEDs and transforms the original problem into a series of convex sub-problems. Then, we use Lagrange dual method to solve the sub-problem and obtain a convergent solution of the original problem. Simulation results show that the proposed LED placement algorithm can harvest 14% power consumption gain when compared with the baseline scheme with centrally placed LEDs.

First Report of Root Rot Caused by Fusarium avenaceum on Coptis chinensis Franchet in Chongqing, China

Coptis chinensis Franchet, is a perennial herb used as a traditional Chinese medicine. Annual production of Coptis is about 3000 tons in Shizhu, Chongqing. In recent years, root rot has become a serious and widespread disease on Coptis in Shizhu with an average incidence of 40%, and yield losses up to 67%. Infected plants were easy to pull from the soil, and most of the fibrous roots and main roots were brown or black compared to healthy roots that were yellow. Severely infected plants were wilted and necrotic. In October 2019, 33 diseased roots were collected from Shizhu (30°18'N, 108°30'E), and small samples (0.5 cm in length) were cut from the border between diseased and healthy tissue, successively sterilized with 75% ethanol and 2% sodium hypochlorite, rinsed 3 times with sterilized water, dried on sterilized filter paper, and transferred onto PDA, and incubated at 25°C for 7 days in dark. Eighteen distinct fungal isolates (H1-H18) were isolated and Koch's postulates were conducted to verify the pathogenicity of individual isolates. The rhizosphere soil of healthy 2-year-old Coptis plants was inoculated by pouring 5 mL of conidial suspension (106 conidia/mL) scraped from a culture of each isolate on PDA. Sterilized water was used to mock inoculate. For each isolate, 6 plants were inoculated. After 20 days, the roots of all plants inoculated with H15 or H18 were dark brown and rotten, while mock inoculated plants were healthy. The isolates H15 and H18 were re-isolated from symptomatic plants. Isolate H15 formed abundant white mycelium on PDA and produced rose pigment in the agar. Conidia were long and slender, straight to slightly curved, with 1-3 septate. The apical cells were tapering and bent, and the foot cells were distinctly notched. Conidiogenous cells were monophialides and polyphialides. No chlamydospores were observed (Figure S1). Isolate H18 formed white sparse mycelium on PDA and produced no pigment in the agar. Conidia were relatively wide, straight and stout, with 3-5 septate. The apical cells were blunt and rounded, and the foot cells were barely notched. Conidiogenous cells were long monophialides. Chlamydospores were formed intercalary in the hyphae (Figure S2). For further identification, the internal transcribed spacer (ITS), β-tubulin, translation elongation factor 1ɑ (EF1ɑ) and RNA polymerase second largest subunit (RPB2) gene regions were amplified with ITS1/ITS4, Bt2a/Bt2b, EF1/EF2 and 5f2/7cr (White et al. 1990; Glass and Donaldson, 1995; O'Donnell et al. 2010). GenBank accession numbers of H15 and H18 were MT463390 and MT463389 for the ITS region, MT465656 and MT465654 for β-tubulin, MT653321 and MT465651 for EF1ɑ, and MT653323 and MT653322 for RPB2. BLAST results showed the ITS, β-tubulin, EF1ɑ, and RPB2 sequences revealed 100% (533/533 base pairs), 100% (265/265 base pairs), 98% (622/632 base pairs), and 99% (936/947 base pairs) homology respectively with those of Fusarium avenaceum (MN186746.1, MH791368.1, KU238140.1, and MK185027.1), and 100% (537/537 base pairs), 100% (227/227 base pairs), 100% (688/688 base pairs), and 99.03% (918/927 base pairs) with F. solani in GenBank (MH857319.1, MN692929.1, KP674211.1, and MH300549.1), respectively. Thus, H15 and H18 were identified as F. avenaceum and F. solani based on its morphological and molecular characteristics. To our knowledge, F. solani has been previously reported as a pathogen on Coptis (Luo et al. 2014), and this is the first report of root rot on Coptis caused by F. avenaceum in the world. Identification of the pathogens is important for effective disease management and control.

[Clinical characteristics and death risk factors of severe COVID-19]

Objective: To analyze the clinical features and death-related risk factors of COVID-19. Methods: We enrolled 891 COVID-19 patients admitted to the Affiliated Hospital of Jianghan University from December 2019 to February 2020, including 427 men and 464 women. Of the 891 cases, 582 were severe or critical, including 423(73%)severe and 159 (27%) critical cases. We compared the demographics, laboratory findings, clinical characteristics, treatments and prognosis data of the 582 severe patients. Univariate and multivariate logistic regression analysis was conducted to explore the risk factors associated with death in COVID-19 patients. Results: The 582 severe patients included 293 males and 289 females, with a median age of 64(range 24 to 106). Sixty-three patients died, including 45 males and 18 females, with a median age of 71(range 37 to 90). The average onset time of the 582 patients was 8 days, of whom 461 (79%) had fever, 358 (62%) dry cough, 274 (47%) fatigue. There were 206 cases with shortness of breath (35%), 155 cases with expectoration (27%), 83 cases with muscle pain or joint pain (14%), 71 cases with diarrhea (12%), and 29 cases with headache (4%). Underlying diseases were present in 267 (46%) patients, most commonly hypertension (194, 33%), followed by diabetes (69, 12%), coronary atherosclerotic heart disease (37, 6%), tumor (18, 3%), and chronic obstructive pulmonary disease (5, 1%). Chest CT showed bilateral lung involvement in 505 patients (87%). Upon admission, the median lymphocyte count of the 582 patients was 0.8(IQR, 0.6-1.1)×10(9)/L, the median D-dimer was 0.5 (IQR, 0.4- 0.8) mg/L, the median N-terminal brain natriuretic peptide precursor (NT-proBNP) was 433 (IQR, 141- 806) pg/L, and the median creatinine was 70.3 (IQR, 56.9-87.9) μmol/L. The death group had a median lymphocyte count of 0.5 (0.4-0.8)×10(9)/L, D-dimer 1.1 (0.7-10.0)mg/L, N-terminal brain natriuretic peptide precursor 1479(893-5 087) pg/ml, and creatinine 89.9(67.1-125.3) μmol/L. Multivariate logistic analysis showed that increased D-dimer (OR: 1.095, 95% CI: 1.045-1.148, P<0.001), increased NT-proBNP (OR: 4.759, 95% CI: 2.437-9.291, P<0.001), and decreased lymphocyte count (OR: 0.180, 95% CI: 0.059-0.550, P=0.003) were the risk factors of death in COVID-19 patients. Conclusions: The average onset time of severe COVID-19 was 8 days, and the most common symptoms were fever, dry cough and fatigue. Comorbidities such as hypertension were common and mostly accompanied by impaired organ functions on admission. Higher D-dimer, higher NT-proBNP, and lower lymphocyte count were the independent risk factors of death in COVID-19 patients.

Isolation and characterization of plant growth-promoting rhizobacteria and their effects on the growth of Medicago sativa L. under salinity conditions

Plant growth-promoting rhizobacteria are a group of free-living bacteria that colonize plant rhizosphere and benefit plant root growth, thereby increasing host plant to cope with salinity induced stress. The aim of this study was to (1) isolate and characterize auxin-producing bacteria showing a high plant growth-promoting (PGP) potential, and (2) evaluate the PGP effects on the growth of Medicago sativa L under salinity stress (130 mM NaCl). Of thirteen isolates, Bacillus megaterium NRCB001 (NRCB001), B. subtilis subsp. subtilis NRCB002 (NRCB002) and B. subtilis NRCB003 (NRCB003) had the ability to produce auxin, which ranged from 47.53 to 154.38 μg ml^-1. The three auxin-producing bacterial strains were shown multiple PGP traits, such as producing siderophore and NH₃, showing ACC deaminase activity, solubilize phosphate and potassium. Furthermore, NRCB001, NRCB002, and NRCB003 could survive in LB medium containing 1750 mM NaCl. The three auxin-producing with salinity tolerance strains were selected for further analyses. In greenhouse experiments, when inoculated with NRCB001, NRCB002 and NRCB003, dry weight of alfalfa significantly (P < 0.05) increased by 24.1%, 23.1% and 38.5% respectively, compared with those of non-inoculated control seedlings under normal growth condition. When inoculated with NRCB002 and NRCB003, dry weight of alfalfa significantly (P < 0.05) increased by 96.9 and 71.6% respectively, compared with those of non-inoculated control seedlings under 130 mM NaCl condition. Our results indicated that NRCB002 and NRCB003 having PGP traits are promising candidate strains to develop biofertilizers, especially used under salinity stress conditions.

Meriolin1 induces cell cycle arrest, apoptosis, autophagy and targeting the Akt/MAPKs pathways in human neuroblastoma SH-SY5Y cells

OBJECTIVES

Meriolins, a kind of chemical hybrid between meridianins and variolins, have lately been determined as kinase inhibitors and reportedly have antitumour activity. However, there is currently no in-depth study for the action mechanism. This study aimed to elucidate the potentially antitumour action mechanism of Meriolin1 on human neuroblastoma (SH-SY5Y) cells.

METHODS

Firstly, cell viability was detected by MTT assay. Secondly, cell cycle, cell apoptosis, cell autophagy, reactive oxygen species and mitochondrial membrane potential (ΔΨm) were measured by flow cytometry. Then, cell cycle-associated proteins, Bcl-2 family proteins, Akt/MAPK proteins and autophagy-associated proteins expressions were evaluated by Western blot. Bcl-2 and Bax mRNA expressions were also evaluated by qRT-PCR. Furthermore, cell adhesion assay and Hoechst 33258 fluorescent staining were carried out to detect the effect of Meriolin1 on cell adhesion and morphology. Finally, to gain further insight into mechanism of action of Meriolin1 to CDK protein, the molecular docking study was performed by using the CDOCKER module of DS software.

KEY FINDINGS

Meriolin1 could exert the antitumour activity on SH-SY5Y cells by inducing cell cycle arrest, cell autophagy, the mitochondrion-dependent cell apoptosis and targeting the Akt/MAPKs signalling pathway.

CONCLUSIONS

Meriolin1 might be a promising therapeutic candidate for neuroblastoma.

A novel double-variant RHAG allele leads to Rhmod phenotype

AIMS/OBJECTIVES

We aimed to analyse the molecular backgrounds and red blood cell (RBC) antigen expression of a male blood donor with Rh_mod phenotype and his family members.

BACKGROUND

Rh deficiency phenotypes are rarely found worldwide and are characterised by the lack of Rh antigen expression on RBCs. During routine screening, we found a blood donor who seemingly lacked Rh antigens. Therefore, we recruited the donor and his family for further investigation.

METHODS

RBC serotyping and antibody screening/identification were performed for each sample. A routine blood examination was also conducted. RHD, RHCE and RHAG were sequenced at the genomic DNA or RNA level. Eleven antigens or proteins associated with Rh complex were tested using flow cytometry analysis.

RESULTS

The proband and one of his brothers showed extremely weak D antigen and Rh expression levels but did not manifest anaemia. Most of the expressed RBC antigens of the two Rh-deficient individuals were similar to the previously reported cases but with some exceptions. Molecular analyses demonstrated homozygous expression of a novel RHAG allele, namely, c.[572G>A;707A>C], both in the proband and one of his brothers.

CONCLUSIONS

To our knowledge, we identified the second double-variant RHAG allele and the first one related to Rh_mod phenotype. The novel allele was also confirmed to be heritable by family analyses.

Reducing postsurgical exudate in breast cancer patients by using San Huang decoction to ameliorate inflammatory status: a prospective clinical trial

Background

Reducing inflammatory factors in wound exudate is a promising treatment approach for healing wounds in postsurgical breast cancer patients. Traditional Chinese Medicine (tcm) treatments have been shown to be beneficial and safe for optimal regulation of oxidative stress during the postoperative period. In the present clinical trial, we evaluated the effectiveness of a promising Chinese herbal formula, San Huang decoction [shd (Radix astragali, Radix et rhizoma rhei, and Rhizoma curcuma longa, 3:1:1; supplemental Table 1)], on wound inflammatory response after mastectomy.

Methods

The study randomized 30 patients with breast cancer who fulfilled the inclusion and exclusion criteria to either a treatment (n = 15) or a control group (n = 15). Patients in the treatment group received liquid shd, taken twice daily with or without food. Treatment was given for 1 day before surgery and for 7 days postoperatively. Participants in the control group received a placebo on the same schedule as the treatment group. Outcomes measured in every subject included clinical tcm and wound inflammation symptom scores, daily and total amounts of drainage fluid, and levels of inflammatory factors in the exudate [tumour necrosis factor α (tnf-α), interleukins 6 (il-6), 8 (il-8), and 2R (il-2R), human C-reactive protein (crp)] at 2 hours and on days 1, 3, and 7 postoperatively.

Results

The total amount of drainage fluid over 7 days was significantly lower in the treatment group (572.20 ± 93.95 mL) than in the control group (700.40 ± 107.38 mL). The tcm symptom score was also lower in treatment group (day 7: 1.87 ± 0.83 vs. 4.80 ± 3.61, p = 0.049), as was the inflammatory symptom score (day 7: 0.67 ± 0.72 vs. 3.67 ± 2.50, p = 0.001). Levels of tnf-α, il-6, il-8, il-2R, and crp in drainage fluid were significantly lower with shd treatment.

Conclusions

Perioperative treatment with shd effectively lessened postoperative exudate and ameliorated inflammatory symptoms in patients who underwent surgery for breast cancer.