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.