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Ligusticum chuanxiong Hort. is considered an important medicinal herb with extremely high economic value and medicinal value due to its various effects, including anti-oxidation, sedative action, hepatoprotection, and invigorating blood circulation. However, L. chuanxiong cultivation is hampered by various plant diseases, especially the root rot caused by Fusarium solani, hindering the sustainable development of the L. chuanxiong industry. The occurrence of soil-borne diseases is closely linked to imbalances in the microbial community structure. Here, we studied the yields, rhizosphere microbiota, and soil physiochemical characteristics of healthy and diseased L. chuanxiong plants affected by root rot with high-throughput sequencing and microbial network analysis, aiming to explore the relationships between soil environmental factors, microbiomes, and plant health of L. chuanxiong. According to the results, L. chuanxiong root rot significantly decreased the yields, altered microbial community diversity and composition, enriched more pathogenic fungi, recruited some beneficial bacteria, and reduced microbial interaction network stability. The Mantel test showed that soil organic matter and pH were the major environmental factors modulating plant microbiome assembly. The root rot severity was significantly affected by soil physiochemical properties, including organic matter, cation exchange capacity, available nitrogen, phosphorus, potassium, and pH. Furthermore, two differential microbes that have great potential in the biocontrol of L. chuanxiong root rot were dug out in the obtained results, which were the genera Trichoderma and Bacillus. This study provided a theoretical basis for further studies revealing the microecological mechanism of L. chuanxiong root rot and the ecological prevention and control of L. chuanxiong root rot from a microbial ecology perspective.

The productivity and quality of agricultural crops worldwide are adversely affected by disease outbreaks and inadequate nutrient availability. Of particular concern is the potential increase in mycotoxin prevalence due to crop diseases, which poses a threat to food security. Microorganisms with multiple functions have been favored in sustainable agriculture to address such challenges. Aspergillus flavus is a prevalent aflatoxin B1 (AFB1)-producing fungus in China. Therefore, we wanted to obtain an anti-aflatoxigenic bacterium with potent mycotoxin detoxification ability and other beneficial properties. In the present study, we have isolated an anti-aflatoxigenic strain, BC11-1, of Burkholderia contaminans, from a forest rhizosphere soil sample obtained in Luzhou, Sichuan Province, China. We found that it possesses several beneficial properties, as follows: (1) a broad spectrum of antifungal activity but compatibility with Trichoderma species, which are themselves used as biocontrol agents, making it possible to use in a biocontrol mixture or individually with other biocontrol agents in an integrated management approach; (2) an exhibited mycotoxin detoxification capacity with a degradation ratio of 90% for aflatoxin B1 and 78% for zearalenone, suggesting its potential for remedial application; and (3) a high ability to solubilize phosphorus and produce cytokinin production, highlighting its potential as a biofertilizer. Overall, the diverse properties of BC11-1 render it a beneficial bacterium with excellent potential for use in plant disease protection and mycotoxin prevention and as a biofertilizer. Lastly, a pan-genomic analysis suggests that BC11-1 may possess other undiscovered biological properties, prompting further exploration of the properties of this unique strain of B. contaminans. These findings highlight the potential of using the anti-aflatoxigenic strain BC11-1 to enhance disease protection and improve soil fertility, thus contributing to food security. Given its multiple beneficial properties, BC11-1 represents a valuable microbial resource as a biocontrol agent and biofertilizer.

Abstract Background Limited research has focused on the correlation between an external compression and the regeneration of ruptured Achilles tendons. The aim of this study was to evaluate the influence of a constricted paratenon with external compression on the regeneration process of separated rabbit common calcanean tendon stumps. Methods A transection, establishing a 4 mm gap, was created in the right common calcanean tendon of 24 young adult male New Zealand white rabbits. The animals were assigned to two groups: In the control group, only received cast immobilization. In the constricted paratenon (CP) group, the rabbits had a local 3-dimensional printed clasp applied to mimic external compression and same cast immobilization as the control group. Morphologic, histologic and immunohistochemistry examinations were performed at 2 and 4 weeks postoperative. Results Separated tendon stumps were connected by novel granulated tendon fibrils in the control group. However, the regenerated tendon fibrils appeared insufficient in the CP group, the tendon length and the adhesion grade of the CP group was significantly larger than that of the control group at 4 weeks (P

Abstract Background For patients with sepsis receiving non-invasive ventilation (NIV), early rehabilitation is crucial. The Sitting Baduanjin (SBE) is an efficient early rehabilitation exercise suitable for bed patients. There is no consensus about the effect of SBE on the early rehabilitation of septic patients with NIV. This study focused on how the SBE affected the early rehabilitation of sepsis patients with NIV. Methods 96 sepsis patients with NIV were randomly assigned to either an Baduanjin group that received the SBE based on the routine rehabilitation exercise (n = 48) or a control group (n = 48) that received routine rehabilitation exercise. The primary outcome was the Medical Research Council(MRC)score, and the Barthel Index score, the duration of NIV, length of ICU stay, length of total stay, hospitalization expense as secondary outcomes. Results A total of 245 sepsis patients were screened, with 96 randomly assigned. The study was completed by 90 patients out of the 96 participants.Results revealed that the MRC score increased in both groups, but the improvement of muscle strength in Baduanjin group was more obvious, with statistical significance (p

To assess the clinical applicability of a semi-quantitative luciferase immunosorbent assay (LISA) for detecting antibodies against Treponema pallidum antigens TP0171 (TP15), TP0435 (TP17), and TP0574 (TP47) in diagnosing and monitoring syphilis. LISA for detection of anti-TP15, TP17, and TP47 antibodies were developed and evaluated for syphilis diagnosis using 261 serum samples (161 syphilis, 100 non-syphilis). Ninety serial serum samples from 6 syphilis rabbit models (3 treated, 3 untreated) and 110 paired serum samples from 55 syphilis patients were used to assess treatment effects by utilizing TRUST as a reference. Compared to TPPA, LISA-TP15, LISA-TP17, and LISA-TP47 showed a sensitivity of 91.9%, 96.9%, and 98.8%, specificity of 99%, 99%, and 98%, and AUC of 0.971, 0.992, and 0.995, respectively, in diagnosing syphilis. Strong correlations (rs = 0.89–0.93) with TPPA were observed. In serial serum samples from rabbit models, significant differences in the relative light unit (RLU) were observed between the treatment and control group for LISA-TP17 (days 31–51) and LISA-TP47 (day 41). In paired serum samples from syphilis patients, TRUST titres and the RLU of LISA-TP15, LISA-TP17, and LISA-TP47 decreased post-treatment (P

Background: Exercise is recommended as the first-line management for knee osteoarthritis (KOA); however, it is difficult to determine which specific exercises are more effective. This study aimed to explore the potential mechanism and effectiveness of a leg-swinging exercise practiced in China, called ‘KOA pendulum therapy’ (KOAPT). Intraarticular hydrostatic and dynamic pressure (IHDP) are suggested to partially explain the signs and symptoms of KOA. As such this paper set out to explore this mechanism in vivo in minipigs and in human volunteers alongside a feasibility clinical trial. The objective of this study is 1) to analyze the effect of KOAPT on local mechanical and circulation environment of the knee in experimental animals and healthy volunteers; and 2) to test if it is feasible to run a large sample, randomized/single blind clinical trial. Methods: IHDP of the knee was measured in ten minipigs and ten volunteers (five healthy and five KOA patients). The effect of leg swinging on synovial blood flow and synovial fluid content depletion in minipigs were also measured. Fifty KOA patients were randomly divided into two groups for a feasibility clinical trial. One group performed KOAPT (targeting 1000 swings/leg/day), and the other performed walking exercise (targeting 4000 steps/day) for 12 weeks with 12 weeks of follow-up. Results: The results showed dynamic intra-articular pressure changes in the knee joint, increases in local blood flow, and depletion of synovial fluid contents during pendulum leg swinging in minipigs. The intra-articular pressure in healthy human knee joints was −11.32 ± 0.21 (cmH2O), whereas in KOA patients, it was −3.52 ± 0.34 (cmH2O). Measures were completed by 100% of participants in all groups with 95–98% adherence to training in both groups in the feasibility clinical trial. There were significant decreases in the Oxford knee score in both KOAPT and walking groups after intervention (p

Abstract Background Increasing evidence indicates that four and a half LIM domains 2 (FHL2) plays a crucial role in the progression of various cancers. However, the biological functions and molecular mechanism of FHL2 in lung adenocarcinoma (LUAD) remain unclear. Methods We evaluated the prognostic value of FHL2 in LUAD using public datasets and further confirmed its prognostic value with our clinical data. The biological functions of FHL2 in LUAD were evaluated by in vitro and in vivo experiments. Pathway analysis and rescue experiments were subsequently performed to explore the molecular mechanism by which FHL2 promoted the progression of LUAD. Results FHL2 was upregulated in LUAD tissues compared to adjacent normal lung tissues, and FHL2 overexpression was correlated with unfavorable outcomes in patients with LUAD. FHL2 knockdown significantly suppressed the proliferation, migration and invasion of LUAD cells, while FHL2 overexpression had the opposite effect. Mechanistically, FHL2 upregulated the PI3K/AKT/mTOR pathway and subsequently inhibited autophagy in LUAD cells. The effects FHL2 on the proliferation, migration and invasion of LUAD cells are dependent on the inhibition of autophagy, as of induction autophagy attenuated the aggressive phenotype induced by FHL2 overexpression. Conclusions FHL2 promotes the progression of LUAD by activating the PI3K/AKT/mTOR pathway and subsequently inhibiting autophagy, which can be exploited as a potential therapeutic target for LUAD.

Knee osteoarthritis (KOA) is one of the most common degenerative joint diseases in the elderly worldwide. The primary lesion in patients with KOA is the degeneration of articular cartilage. This study aimed to observe the biological effects of cyclic negative pressure on C28/I2 chondrocytes and to elucidate the underlying molecular mechanisms. We designed a bi-directional intelligent micro-pressure control device for cyclic negative pressure intervention on C28/I2 chondrocytes. Chondrocyte vitality and proliferation were assessed using Cell Counting Kit-8 (CCK-8) and 5-ethynyl-2'-deoxyuridine (EdU) assays. The extracellular matrix was analyzed using real-time fluorescence quantitative polymerase chain reaction (PCR) and western blot, while the molecular mechanism of the chondrocyte response to cyclic negative pressure was explored through mRNA sequencing. Experimental data demonstrated that cyclic negative pressure promoted chondrocyte proliferation and upregulated the expression of chondrocyte-specific protein, namely the collagen type II alpha 1 chain (COL2A1) protein, and the transcription factor SRY-box transcription factor 9 (SOX9). Additionally, RNA sequencing analysis revealed that the gene levels of insulin-like growth factor 2 (IGF-II) and early growth response 1 (EGR-1) were significantly elevated in the cyclic negative pressure group. This study demonstrates that cyclic negative pressure stimulates the proliferation of C28/I2 chondrocytes by promoting the expression of EGR-1 and IGF-II. This new discovery may provide novel insights into cartilage health and KOA prevention.

Abstract Recent findings have shown that fatty acid metabolism is profoundly involved in ferroptosis. However, the role of cholesterol in this process remains incompletely understood. In this work, we show that modulating cholesterol levels changes vulnerability of cells to ferroptosis. Cholesterol alters metabolic flux of the mevalonate pathway by promoting Squalene Epoxidase (SQLE) degradation, a rate limiting step in cholesterol biosynthesis, thereby increasing both CoQ10 and squalene levels. Importantly, whereas inactivation of Farnesyl-Diphosphate Farnesyltransferase 1 (FDFT1), the branch point of cholesterol biosynthesis pathway, exhibits minimal effect on ferroptosis, simultaneous inhibition of both CoQ10 and squalene biosynthesis completely abrogates the effect of cholesterol. Mouse models of ischemia-reperfusion and doxorubicin induced hepatoxicity confirm the protective role of cholesterol in ferroptosis. Our study elucidates a potential role of ferroptosis in diseases related to dysregulation of cholesterol metabolism and suggests a possible therapeutic target that involves ferroptotic cell death.

Purposes Speech emotion recognition allows computers to understand the emotional information contained in human speech, and is an important part of intelligent human-computer interaction. Feature extraction and fusion are key parts in speech emotion recognition systems, and have an important impact on recognition results. Aiming at the problem of insufficient emotional information contained in traditional acoustic features, a deep feature extraction method based on multi-task learning for optimization of acoustic features is proposed in this paper. Methods The proposed acoustic depth feature can better characterize itself and has more emotional information. Then, on the basis of the complementarity between acoustic features and spectrogram features, spectrogram features through convolutional neural network are extracted. Then, the multi-kernel principal component analysis method is used to perform feature fusion and dimension reduction on these two features, and the obtained fusion features can effectively improve the system recognition performance. Findings Experiments are carried out on the EMODB and the CASIA speech databases. When the DNN classifier is used, the multi-kernel fusion feature of the acoustic depth feature and the spectrogram feature achieve the highest recognition rates of 92.71% and 88.25%, respectively. Compared with direct feature splicing, this method increased the recognition rate by 2.43% and 2.83%, respectively.

Purposes Deep compressed sensing is the use of deep learning to solve the problems existing in traditional compressed sensing, such as the adaptability of observation matrix to traditional signal compression and the dependency on dictionary by reconstruction algorithm. Methods In this paper, the deep belief network (DBN) is used to adaptively compress the signal without destroying the randomness of observation matrix. At the same time, the stacked auto encoder (SAE) is used to train the reconstruction network end-to-end to get rid of the dependence of the reconstruction algorithm on sparse dictionary. According to the discrimination of the sparse representation of signal, a compressed sensing recognition model based on DBN and SAE is proposed (CS-DBN-SAE). Findings The results of four classification experiments on DEAP emotional EEG database show that the recognition rate of CS-DBN-SAE model is 83.29%, which is oven 4.3% higher than that of traditional compressed sensing recognition model.

Abstract Aim To explore the effectiveness of motivation‐guided ‘plan, do, check and action’ cycle nursing for self‐management ability and outcomes of patients with gestational diabetes mellitus (GDM). Design A pre‐ and post‐ comparison quasi experimental study. Methods Totally 108 pregnant women with GDM diagnosed and delivered in our hospital from January 2020 to April 2021 were included in this study. They were divided into study group (54 cases) and control group (54 cases). Results The score of self‐management ability were significantly higher than those of control group (t‐test, all p

Background: Scrophulariae Radix (SR) is a commonly used medicinal plant. Alzheimer's disease (AD) is a neurodegenerative disease for which there is no effective treatment. This study aims to initially clarify the potential mechanism of SR in the treatment of AD based on network pharmacology and molecular docking techniques. Methods: The principal components and corresponding protein targets of SR were conducted by HPLC analysis and searched on TCMSP. AD targets were searched on DrugBank, Chemogenomics, TTD, OMIM and GeneCards databases. The compound-target network was constructed by Cytoscape3.8.2. The intersection of compound target and disease target was obtained and the coincidence target was imported into STRING database to construct a PPI network. We further performed GO and KEGG enrichment analysis on the targets. Meanwhile, molecular docking study and cell experiments were approved for the core target and the active compound. Results: Through multidatabase retrieval and integration, it was found that 17 components of SR could exert anti-AD effects against 40 targets. KEGG enrichment analysis indicated that Alzheimer's disease (hsa05010) was one of the most significant AD enrichment signalling pathways. Combined with the gene expression profile information in the AlzData database, 15 targets were found to be associated with tau or beta-amyloid protein (Aβ). GO analysis indicated that the primary molecular functions of SR in the treatment of AD were neurotransmitter receptor activity (GO:0007268), postsynaptic neurotransmitter receptor activity (GO:0070997), and acetylcholine receptor activity (GO:0050435). Moreover, we explored the anti-AD effects of SR extract and ursolic acid (UA) using SH-SY5Y cells. Treatment of SH-SY5Y cells with 20 μM UA significantly reduced the oxidative damage to these neuronal cells. Conclusion: This study reveals the active ingredients and potential molecular mechanism of SR in the treatment of AD, and provides a theoretical basis for further basic research and clinical application.

Objective To compare the non-synonymous single nucleotide polymorphisms of the carrier protein of branched-chain amino acid transport system Ⅱ (TP0265) of Treponema pallidum (Tp) in Guangdong clinical strain (GD1) with the standard strain of Nichols in the United States and Treponema spp. Methods GD1 was serially subcultured in rabbit testis for obtaining Tp bacterial suspension. GD1 DNA was extracted and the concentration of GD1 genome was quantitatively detected by TP0574 qPCR. GD1 DNA was detected by TP0548 PCR and genotyping system. PCR detection by TP0265 Multiple sequence alignment analysis was performed between GD1 TP0265 and nsSNPs of American Nichols standard strain and Treponema globe. Results The sequencing results of TP0548 were confirmed to be f subtype by BioEdit multiple sequence alignment. Compared with the American Nichols strain, it was found that GD1 had a G175A mutation at the TP0265 base, resulting in the mutation of proline (P) at position 230 of the TP0265 protein to leucine (L). Compared with different Treponema species in the global Treponema genus, except for Nichols, Dal-1 and Nichols Houston in the United States, the TP0265 mutation was found. Conclusion There is a TP0265 nsSNPs mutation in GD1, which involves a wide range of Treponema species worldwide.

IntroductionIn the medical field, electronic medical records contain a large amount of textual information, and the unstructured nature of this information makes data extraction and analysis challenging. Therefore, automatic extraction of entity information from electronic medical records has become a significant issue in the healthcare domain.MethodsTo address this problem, this paper proposes a deep learning-based entity information extraction model called Entity-BERT. The model aims to leverage the powerful feature extraction capabilities of deep learning and the pre-training language representation learning of BERT(Bidirectional Encoder Representations from Transformers), enabling it to automatically learn and recognize various entity types in medical electronic records, including medical terminologies, disease names, drug information, and more, providing more effective support for medical research and clinical practices. The Entity-BERT model utilizes a multi-layer neural network and cross-attention mechanism to process and fuse information at different levels and types, resembling the hierarchical and distributed processing of the human brain. Additionally, the model employs pre-trained language and sequence models to process and learn textual data, sharing similarities with the language processing and semantic understanding of the human brain. Furthermore, the Entity-BERT model can capture contextual information and long-term dependencies, combining the cross-attention mechanism to handle the complex and diverse language expressions in electronic medical records, resembling the information processing method of the human brain in many aspects. Additionally, exploring how to utilize competitive learning, adaptive regulation, and synaptic plasticity to optimize the model's prediction results, automatically adjust its parameters, and achieve adaptive learning and dynamic adjustments from the perspective of neuroscience and brain-like cognition is of interest.Results and discussionExperimental results demonstrate that the Entity-BERT model achieves outstanding performance in entity recognition tasks within electronic medical records, surpassing other existing entity recognition models. This research not only provides more efficient and accurate natural language processing technology for the medical and health field but also introduces new ideas and directions for the design and optimization of deep learning models.

Summary: Background: The ability to accurately identify the absolute risk of neurosyphilis diagnosis for patients with syphilis would allow preventative and therapeutic interventions to be delivered to patients at high-risk, sparing patients at low-risk from unnecessary care. We aimed to develop, validate, and evaluate the clinical utility of simplified clinical diagnostic models for neurosyphilis diagnosis in HIV-negative patients with syphilis. Methods: We searched PubMed, China National Knowledge Infrastructure and UpToDate for publications about neurosyphilis diagnostic guidelines in English or Chinese from database inception until March 15, 2023. We developed and validated machine learning models with a uniform set of predictors based on six authoritative diagnostic guidelines across four continents to predict neurosyphilis using routinely collected data from real-world clinical practice in China and the United States (through the Dermatology Hospital of Southern Medical University in Guangzhou [659 recruited between August 2012 and March 2022, treated as Development cohort], the Beijing Youan Hospital of Capital Medical University in Beijng [480 recruited between December 2013 and April 2021, treated as External cohort 1], the Zhongshan Hospital of Xiamen University in Xiamen [493 recruited between November 2005 and November 2021, treated as External cohort 2] from China, and University of Washington School of Medicine in Seattle [16 recruited between September 2002 and April 2014, treated as External cohort 3] from United States). We included all these patients with syphilis into our analysis, and no patients were further excluded. We trained eXtreme gradient boosting (XGBoost) models to predict the diagnostic outcome of neurosyphilis according to each diagnostic guideline in two scenarios, respectively. Model performance was measured through both internal and external validation in terms of discrimination and calibration, and clinical utility was evaluated using decision curve analysis. Findings: The final simplified clinical diagnostic models included neurological symptoms, cerebrospinal fluid (CSF) protein, CSF white blood cell, and CSF venereal disease research laboratory test/rapid plasma reagin. The models showed good calibration with rescaled Brier score of 0.99 (95% CI 0.98–1.00) and excellent discrimination (the minimum value of area under the receiver operating characteristic curve, 0.84; 95% CI 0.81–0.88) when externally validated. Decision curve analysis demonstrated that the models were useful across a range of neurosyphilis probability thresholds between 0.33 and 0.66 compared to the alternatives of managing all patients with syphilis as if they do or do not have neurosyphilis. Interpretation: The simplified clinical diagnostic models comprised of readily available data show good performance, are generalisable across clinical settings, and have clinical utility over a broad range of probability thresholds. The models with a uniform set of predictors can simplify the sophisticated clinical diagnosis of neurosyphilis, and guide decisions on delivery of neurosyphilis health-care, ultimately, support accurate diagnosis and necessary treatment. Funding: The Natural Science Foundation of China General Program, Health Appropriate Technology Promotion Project of Guangdong Medical Research Foundation, Department of Science and technology of Guangdong Province Xinjiang Rural Science and Technology（Special Commissioner）Project, Southern Medical University Clinical Research Nursery Garden Project, Beijing Municipal Administration of Hospitals Incubating Program.

To solve the problem that Dempster-Shafer (D-S) evidence theory gives combines results contrary to with facts when dealing with conflict evidence, a novel method of conflict evidence combination was proposed. First, the Spearman correlation coefficient is improved and the support between evidences is calculated, and original evidence is amended for the first time. Then, combined with the advantages of the interval distance based on fixed integrals, the uncertainty of evidence is analyzed, a new discount coefficient is determined, and original evidence body is secondarily revised. Finally, the fusion results are obtained by using the Dempster combination rule. The calculation and example analysis demonstrates that the proposed method can effectively fuse the evidence of conflict, and has a higher basic probability distribution than the classical improved algorithm. The proposed method was used for carbon/carbon composite sedimentation data, and a carbon/carbon composite sedimentation mass prediction model based on improved D-S evidence theory was established. Compared with several classical classifiers and the existing prediction model based on D-S evidence theory, this model is increased in accuraey by 5%~13%, which proves its validity.

IntroductionAlthough many studies have demonstrated the existing neurological symptoms in COVID-19 patients, the mechanisms are not clear until now. This study aimed to figure out the critical molecular and immune infiltration situations in the brain of elderly COVID-19 patients.MethodsGSE188847 was used for the differential analysis, WGCNA, and immune infiltration analysis. We also performed GO, KEGG, GSEA, and GSVA for the enrich analysis.Results266 DEGs, obtained from the brain samples of COVID-19 and non-COVID-19 patients whose ages were over 70 years old, were identified. GO and KEGG analysis revealed the enrichment in synapse and neuroactive ligand-receptor interaction in COVID-19 patients. Further analysis found that asthma and immune system signal pathways were significant changes based on GSEA and GSVA. Immune infiltration analysis demonstrated the imbalance of CD8+ T cells, neutrophils, and HLA. The MEpurple module genes were the most significantly different relative to COVID-19. Finally, RPS29, S100A10, and TIMP1 were the critical genes attributed to the progress of brain damage.ConclusionRPS29, S100A10, and TIMP1 were the critical genes in the brain pathology of COVID-19 in elderly patients. Our research has revealed a new mechanism and a potential therapeutic target.

EEG emotion recognition based on Granger causality (GC) brain networks mainly focus on the EEG signal from the same-frequency bands, however, there are still some causality relationships between EEG signals in the cross-frequency bands. Considering the functional asymmetric of the left and right hemispheres to emotional response, this paper proposes an EEG emotion recognition scheme based on cross-frequency GC feature extraction and fusion in the left and right hemispheres. Firstly, we calculate the GC relationship of EEG signals according to the frequencies and hemispheres, and mainly focus on the causality of the cross-frequency EEG signals in left and right hemispheres. Then, to remove the redundant connections of the GC brain network, an adaptive two-stage decorrelation feature extraction scheme is proposed under the condition of maintaining the best emotion recognition performance. Finally, a multi-GC feature fusion scheme is designed to balance the recognition accuracy and feature number of each GC feature, which comprehensively considers the influence of the recognition accuracy and computational complexity. Experimental results on the DEAP emotion dataset show that the proposed scheme can achieve an average accuracy of 84.91% for four classifications, which improved the classification accuracy by up to 8.43% compared with that of the traditional same-frequency band GC features.

In the quality analysis of polysilicon ingot batching, a two-stage genetic algorithm (NRS-SVM-GA) combining the NRS-SVM model with genetic algorithm (GA) was proposed to solve the problem of neighborhood radius and SVM parameter values in the processing of continuous data of polysilicon ingot batting with rough set-support vector machine (NRS-SVM) model. The first stage of the algorithm, by searching for a new neighborhood radius, a better reduction set is obtained. In the second stage the attribute reduction results from the first stage are adopted to, by searching the new parameters of SVM, train the classification model with higher accuracy. According to the purpose of each stage, the corresponding fitness function and termination conditions are put forward. The distinctive features of this method is to implement the NRS-SVM automatic feature extraction and classification prediction, and run the two stages independently to avoid the time consumption for the evaluation of reduction by classifiec. The experimental results of polysilicon ingot batching data set show that this method has shorter running time, stable output, less features, and higher classification accuracy than the standard genetic algorithm.

Abstract Background Recent evidences had shown that loss in phosphatase and tensin homolog deleted on chromosome 10 (PTEN) was associated with immunotherapy resistance, which may be attributed to the non-T-cell-inflamed tumor microenvironment. The impact of PTEN loss on tumor microenvironment, especially regarding T cell infiltration across tumor types is not well understood. Methods Utilizing The Cancer Genome Atlas (TCGA) and publicly available dataset of immunotherapy, we explored the correlation of PTEN expressing level or genomic loss with tumor immune microenvironment and response to immunotherapy. We further investigated the involvement of PI3K-AKT-mTOR pathway activation, which is known to be the subsequent effect of PTEN loss, in the immune microenvironment modulation. Results We reveal that PTEN mRNA expression is significantly positively correlated with CD4/CD8A gene expression and T cells infiltration especially T helpers cells, central memory T cell and effector memory T cells in multiples tumor types. Genomic loss of PTEN is associated with reduced CD8+ T cells, type 1 T helper cells, and increased type 2 T helper cells, immunosuppressed genes (e.g. VEGFA) expression. Furthermore, T cell exclusive phenotype is also observed in tumor with PI3K pathway activation or genomic gain in PIK3CA or PIK3CB. PTEN loss and PI3K pathway activation correlate with immunosuppressive microenvironment, especially in terms of T cell exclusion. PTEN loss predict poor therapeutic response and worse survival outcome in patients receiving immunotherapy. Conclusion These data brings insight into the role of PTEN loss in T cell exclusion and immunotherapy resistance, and inspires further research on immune modulating strategy to augment immunotherapy.

Acinetobacter baumannii, a strictly aerobic, non-lactose fermented Gram-negative bacteria, is one of the important pathogens of nosocomial infection. Major facilitator superfamily (MFS) transporter membrane proteins are a class of proteins that widely exists in microbial genomes and have been revealed to be related to biofilm formation in a variety of microorganisms. However, as one of the MFS transporter membrane proteins, little is known about the role of BIT33_RS14560 in A. baumannii. To explore the effects of BIT33_RS14560 on biofilm formation of A. baumannii, the biofilm formation abilities of 62 isolates were firstly investigated and compared with their transcript levels of BIT33_RS14560. Then, this specific gene was over-expressed in a standard A. baumannii strain (ATCC 19606) and two isolates of extensively drug-resistant A. baumannii (XDR-Ab). Bacterial virulence was observed using a Galleria mellonella infection model. High-throughput transcriptome sequencing (RNA seq) was performed on ATCC 19606 over-expressed strain and its corresponding empty plasmid control strain. Spearman’s correlation analysis indicated a significant negative correlation (R = −0.569, p = 0.000) between the △CT levels of BIT33_RS1456 and biofilm grading of A. baumannii isolates. The amount of A. baumannii biofilm was relatively high within 12–48 h. Regardless of standard or clinical strains; the biofilm biomass in the BIT33_RS14560 overexpression group was significantly higher than that in the control group ( p

Abstract How the genomic landscape of a tumor shapes the formation of tertiary lymphoid structure (TLS) and how might TLS alter the clinical outcome or response to immunotherapy had not been systematically explored. Utilizing the genomic and transcriptome data of solid tumors on TCGA, we quantified TLS based on a previous identified 12-chemokine signature and evaluated its correlation with mutation/neoantigen burden, functional mutation of oncogenes and the presence of viral infection. Clinical data was integrated to decide the prognostic significance of TLS for different cancers after surgical treatment. Publicly available data (clinical and transcriptome data) of immunotherapy clinical trials involving melanoma and lung cancer were also collected to evaluate TLS’s association with therapeutic outcome. Mutation burden and predicted neoantigen counts were positively correlated with TLS scoring in multiple cancer types. Mutation in tumor suppressor genes (KEAP1, PBRM1) and genes involved in extrinsic apoptosis (CASP8), antigen-presentation (HLA-A, HLA-B), immune regulation (SMAD4) or DNA repair (BRCA1, BRCA2, TP53BP1) correlated with TLS alteration in multiple tumor types, indicating the interaction between mutation landscape and TLS formation. Epstein-Barr virus (EBV) infection in gastric cancer and human papillomavirus (HPV) infection in Head and Neck squamous cell carcinoma were associated with increased TLS scoring. High TLS scoring predicted favorable prognosis in certain cancer after surgical treatment and improved response to immunotherapy in lung cancer and melanoma. Our findings unraveled the genomic properties associated with TLS formation in different solid tumors and highlighted the prognostic and predictive significance of TLS in surgical treatment and immunotherapy.

Abstract Background Previous evidence suggests that plasma phospholipid fatty acids (PPFAs) and HOMA insulin resistance (HOMA-IR) are independently related to leukocyte telomere length (LTL). However, there is limited evidence of regarding the effect of their interaction on relative LTL (RLTL). Therefore, here, we aimed to determine the effect of the interaction between PPFAs and HOMA-IR on RLTL. Methods We conducted a cross-sectional study, involving a total of 1246 subjects aged 25–74 years. PPFAs and RLTL were measured, and HOMA-IR was calculated. The effect of the interaction between PPFAs and HOMA-IR on RLTL was assessed by univariate analysis, adjusting for potential confounders. Results In age-adjusted analyses, multivariate linear regression revealed a significant association of the levels of elaidic acid, HOMA-IR, monounsaturated fatty acids (MUFA) and omega-6 (n-6) polyunsaturated fatty acid (PUFA) with RLTL. After adjustment of age and gender, race, smoking, drinking, tea, and exercise, elaidic acid, and omega-3 (n-3) PUFA were negatively associated with RLTL, and HOMA-IR and n-6 PUFA were positively associated with RLTL. These associations were not significantly altered upon further adjustment for anthropometric and biochemical indicators. Meanwhile, the effect of the interaction of elaidic acid and HOMA-IR on RLTL was significant, and remained unchanged even after adjusting for the aforementioned potential confounders. Interestingly, individuals who had the lowest HOMA-IR and the highest elaidic acid levels presented the shortest RLTL. Conclusions Our findings indicated that shorter RLTL was associated with lower HOMA-IR and higher elaidic acid level. These findings might open a new avenue for exploring the potential role of the interaction between elaidic acid and HOMA-IR in maintaining RLTL.

The service network design problem is one of the key problems in the field of railroad intermodal transportation of hazardous materials (hazmat). It lies in determining the frequency of the trains and the allocation of both hazardous and ordinary shipments to these trains, as well as the railroad connecting plan of all shipments based on the established train formation plan. Based on a unified method, we build a multiobjective mixed-integer linear-programming model that comprehensively considers both hazardous and ordinary materials, the compatibility of goods and services, the capacity of the transfer station, and the delivery time limit of each shipment. An augmented ε-constraint algorithm is customized to solve the model. Computational results of a practical example in China show that an increase of 8.4 million yuan in the total cost could reduce nearly 24541 the total risk. Moreover, the algorithms comparison and sensitivity analysis indicate that the augmented ε-constraint algorithm is a more suitable approach to handle the model because of its advantage in the uniqueness of distinct nondominated solutions. Finally, the sensitivity analysis shows that the total cost and risk could simultaneously be reduced if the delivery time limit is relaxed or if the transfer time is shortened.

Abstract Lipid metabolism is essential for stemness maintenance, self‐renewal, and differentiation of stem cells, however, the regulatory function of cholesterol metabolism in erythroid differentiation is poorly studied. In the present study, a critical role for cholesterol homeostasis in terminal erythropoiesis is uncovered. The master transcriptional factor GATA1 binds to Sterol‐regulatory element binding protein 2 (SREBP2) to downregulate cholesterol biosynthesis, leading to a gradual reduction in intracellular cholesterol levels. It is further shown that reduced cholesterol functions to block erythroid proliferation via the cholesterol/mTORC1/ribosome biogenesis axis, which coordinates cell cycle exit in the late stages of erythroid differentiation. The interaction of GATA1 and SREBP2 also provides a feedback loop for regulating globin expression through the transcriptional control of NFE2 by SREBP2. Importantly, it is shown that disrupting intracellular cholesterol hemostasis resulted in defect of terminal erythroid differentiation in vivo. These findings demonstrate that fine‐tuning of cholesterol homeostasis emerges as a key mechanism for regulating erythropoiesis.

Concrete pile foundations are the main load-carrying and aseismic structures for many large-scale building structures. Their structural quality will have a great impact on the safety of building structures. However, the imaging results still cannot easily meet practical demands in current ultrasonic Computerized Tomography (CT) imaging tests of concrete structures. In view of the current difficulties, a combinatorial optimization tomographic imaging method is proposed. First, a quadric broadening objective function with a clear physical meaning is established according to the characteristics of ultrasonic propagation in concrete. Then, a new CT imaging method of concrete pile foundation is formed by combining fast adaptive optimization search ability of Genetic Algorithm (GA) with the global search control ability of Simulated Annealing Algorithm (SAA). The numerical simulation experiments have shown that the usage of the correct priori information and the excellent characteristic of the Simulated Annealing Genetic Algorithm (SAGA) in searching for the global minimum value of the function have produced accurate and effective results with stable numerical values. Finally, the imaging method is verified by experiment, where results show that SAGA requires fewer iterations, has faster computation speed and gives more accurate imaging results compared with the single GA.

In the background of artificial intelligence, the realization of smooth communication between people and machines has become the goal pursued by people. Mel spectrograms is a common method used in speech emotion recognition, focusing on the low-frequency part of speech. In contrast, the inverse Mel (IMel) spectrogram, which focuses on the high-frequency part, is proposed to comprehensively analyze emotions. Because the convolutional neural network-stacked sparse autoencoder (CNN-SSAE) can extract deep optimized features, the Mel-IMel dual-channel complementary structure is proposed. In the first channel, a CNN is used to extract the low-frequency information of the Mel spectrogram. The other channel extracts the high-frequency information of the IMel spectrogram. This information is transmitted into an SSAE to reduce the number of dimensions, and obtain the optimized information. Experimental results show that the highest recognition rates achieved on the EMO-DB, SAVEE, and RAVDESS datasets were 94.79%, 88.96%, and 83.18%, respectively. The conclusions are that the recognition rate of the two spectrograms was higher than that of each of the single spectrograms, which proves that the two spectrograms are complementary. The SSAE followed the CNN to get the optimized information, and the recognition rate was further improved, which proves the effectiveness of the CNN-SSAE network.

MicroRNAs (miRNAs) are important molecules that mediate virus-host interactions, mainly by regulating gene expression via gene silencing. Here, we demonstrated that HIV-1 infection upregulated miR-210-5p in HIV-1-inoculated cell lines and in the serum of HIV-1-infected individuals. Luciferase reporter assays and western blotting confirmed that a target protein of miR-210-5p, TGIF2, is regulated by HIV-1 infection. Furthermore, HIV-1 Vpr protein induced miR-210-5p expression. The use of a miR-210-5p inhibitor and TGIF2 overexpression showed that Vpr upregulated miR-210-5p and thereby downregulated TGIF2, which might be one of the mechanisms used by Vpr to induce G2 arrest. Moreover, we identified a transcription factor, NF-κB p50, which upregulated miR-210-5p in response to Vpr protein. In conclusion, we identified a mechanism whereby miR-210-5p, which is induced upon HIV-1 infection, targets TGIF2. This pathway was initiated by Vpr protein activating NF-κB p50, which promoted G2 arrest. These alterations orchestrated by miRNA provide new evidence on how HIV-1 interacts with its host during infection and increase our understanding of the mechanism by which Vpr regulates the cell cycle.

Glass fiber-reinforced plastics (GFRP) is widely used in many industrial fields. When acoustic emission (AE) technology is applied for dynamic monitoring, the interfering signals often affect the damage evaluation results, which significantly influences industrial production safety. In this work, an effective intelligent recognition method for AE signals from the GFRP damage is proposed. Firstly, the wavelet packet analysis method is used to study the characteristic difference in frequency domain between the interfering and AE signals, which can be characterized by feature vector. Then, the model of back-propagation neural network (BPNN) is constructed. The number of nodes in the input layer is determined according to the feature vector, and the feature vectors from different types of signals are input into the BPNN for training. Finally, the wavelet packet feature vectors of the signals collected from the experiment are input into the trained BPNN for intelligent recognition. The accuracy rate of the proposed method reaches to 97.5%, which implies that the proposed method can be used for dynamic and accurate monitoring of GFRP structures.

Abstract Growing experience with engineered chimeric antigen receptor (CAR)‐T cells has revealed some of the challenges associated with developing patient‐specific therapy. The promising clinical results obtained with CAR‐T therapy nevertheless demonstrate the urgency of advancements to promote and expand its uses. There is indeed a need to devise novel methods to generate potent CARs, and to confer them and track their anti‐tumor efficacy in CAR‐T therapy. A potentially effective approach to improve the efficacy of CAR‐T cell therapy would be to exploit the benefits of nanotechnology. This report highlights the current limitations of CAR‐T immunotherapy and pinpoints potential opportunities and tremendous advantages of using nanotechnology to 1) introduce CAR transgene cassettes into primary T cells, 2) stimulate T cell expansion and persistence, 3) improve T cell trafficking, 4) stimulate the intrinsic T cell activity, 5) reprogram the immunosuppressive cellular and vascular microenvironments, and 6) monitor the therapeutic efficacy of CAR‐T cell therapy. Therefore, genetic and functional modifications promoted by nanotechnology enable the generation of robust CAR‐T cell therapy and offer precision treatments against cancer.

This study evaluates the protective effect of corilagin against Parkinsonismin Japanese encephalitis virus (JEV) induced Parkinson’s disease. The JaGAr-01 strain of virus was used to induce JE. The virus was injected into the rats (13 days age) at the midpoint between the two ears. Adult rats, 12 week after the inoculation of virus, were used for the further study. Corilagin (20 mg/kg) and levodopa with dopa decarboxylase inhibitor (LEV, 10 mg/kg) were administered intraperitoneally for the duration of one week. Bradykinesia and the levels of dopamine in the brain were estimated at the end of protocol. There was a significant decrease inthe motor function in the corilagin, LEV and LEV + corilagin treated groupscompared to the negative control group. However treatment with corilagin, LEV and LEV + corilagin significantly increases the level of dopamine in the brain compared to the negative control group. This study concludes that corilagin ameliorates the Parkinsonismin JEV induced Parkinsonism. Moreover it shows a synergistic effect when treated with LEV. Data presented in the investigation supports that corilagin can be used clinically.

Abstract  Blast, caused by the ascomycete fungus Magnaporthe oryzae, is one of the most devastating diseases of rice worldwide. The Chinese native cultivar (cv.) Q15 expresses the broad-spectrum resistance to most of the isolates collected from China. To effectively utilize the resistance, three rounds of linkage analysis were performed in an F2 population derived from a cross of Q15 and a susceptible cv. Tsuyuake, which segregated into 3:1 (resistant/susceptible) ratio. The first round of linkage analysis employing simple sequence repeat (SSR) markers was carried out in the F2 population through bulked-segregant assay. A total of 180 SSR markers selected from each chromosome equally were surveyed. The results revealed that only two polymorphic markers, RM247 and RM463, located on chromosome 12, were linked to the resistance (R) gene. To further define the chromosomal location of the R gene locus, the second round of linkage analysis was performed using additional five SSR markers, which located in the region anchored by markers RM247 and RM463. The locus was further mapped to a 0.27 cM region bounded by markers RM27933 and RM27940 in the pericentromeric region towards the short arm. For fine mapping of the R locus, seven new markers were developed in the smaller region for the third round of linkage analysis, based on the reference sequences. The R locus was further mapped to a 0.18 cM region flanked by marker clusters 39M11 and 39M22, which is closest to, but away from the Pita/Pita 2 locus by 0.09 cM. To physically map the locus, all the linked markers were landed on the respective bacterial artificial chromosome clones of the reference cv. Nipponbare. Sequence information of these clones was used to construct a physical map of the locus, in silico, by bioinformatics analysis. The locus was physically defined to an interval of ≈37 kb. To further characterize the R gene, five R genes mapped near the locus, as well as 10 main R genes those might be exploited in the resistance breeding programs, were selected for differential tests with 475 Chinese isolates. The R gene carrier Q15 conveys resistances distinct from those conditioned by the carriers of the 15 R genes. Together, this valuable R gene was, therefore, designated as Pi39(t). The sequence information of the R gene locus could be used for further marker-based selection and cloning. [ABSTRACT FROM AUTHOR]

Novel biomarkers are of particular interest for predicting cancer prognosis. This study aimed to explore the associations between enhancer of zeste homolog 2 (EZH2) and patient survival in various cancers.Relevant literature was retrieved from PubMed and Web of Science databases. Pooled hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (CIs) were calculated.Forty-nine studies (8,050 patients) were included. High EZH2 expression was significantly associated with shorter overall (hazard ratio [HR] 1.74, 95% CI: 1.46-2.07), disease-free (HR 1.59, 95% CI: 1.27-1.99), metastasis-free (HR 2.19, 95% CI: 1.38-3.47), progression-free (HR 2.53, 95% CI: 1.52-4.21), cancer-specific (HR 3.13, 95% CI: 1.70-5.74), and disease-specific (HR 2.29, 95% CI: 1.56-3.35) survival, but not recurrence-free survival (HR 1.38, 95% CI: 0.93-2.06). Moreover, EZH2 expression significantly correlated with distant metastasis (OR 3.25, 95% CI: 1.07-9.87) in esophageal carcinoma; differentiation (OR 3.00, 95% CI: 1.37-6.55) in non-small cell lung cancer; TNM stage (OR 3.18, 95% CI: 2.49-4.08) in renal cell carcinoma; and histological grade (OR 4.50, 95% CI: 3.33-6.09), estrogen receptor status (OR 0.15, 95% CI: 0.11-0.20) and progesterone receptor status (OR 0.30, 95% CI: 0.23-0.39) in breast cancer.Our results suggested that EZH2 might be an independent prognostic factor for multiple survival measures in different cancers.

BACKGROUND: Detection of Acinetobacter baumannii has been relying primarily on bacterial culture that often fails to return useful results in time. Although DNA-based assays are more sensitive than bacterial culture in detecting the pathogen, the molecular results are often inconsistent and challenged by doubts on false positives, such as those due to system- and environment-derived contaminations. In addition, these molecular tools require expensive laboratory instruments. Therefore, establishing molecular tools for field use require simpler molecular platforms. The loop-mediated isothermal amplification method is relatively simple and can be improved for better use in a routine clinical bacteriology laboratory. A simple and portable device capable of performing both the amplification and detection (by fluorescence) of LAMP in the same platform has been developed in recent years. This method is referred to as real-time loop-mediated isothermal amplification. In this study, we attempted to utilize this method for rapid detection of A. baumannii. METHODOLOGY AND SIGNIFICANT FINDINGS: Species-specific primers were designed to test the utility of this method. Clinical samples of A. baumannii were used to determine the sensitivity and specificity of this system compared to bacterial culture and a polymerase chain reaction method. All positive samples isolated from sputum were confirmed to be the species of Acinetobacter by 16S rRNA gene sequencing. The RealAmp method was found to be simpler and allowed real-time detection of DNA amplification, and could distinguish A. baumannii from Acinetobacter calcoaceticus and Acinetobacter genomic species 3. DNA was extracted by simple boiling method. Compared to bacterial culture, the sensitivity and specificity of RealAmp in detecting A. baumannii was 98.9% and 75.0%, respectively. CONCLUSION: The RealAmp assay only requires a single unit, and the assay positivity can be verified by visual inspection. Therefore, this assay has great potential of field use as a molecular tool for detection of A. baumannii.