Nodule-CLIP: Lung nodule classification based on multi-modal contrastive learning.

The latest developments in deep learning have demonstrated the importance of CT medical imaging for the classification of pulmonary nodules. However, challenges remain in fully leveraging the relevant medical annotations of pulmonary nodules and distinguishing between the benign and malignant labels of adjacent nodules. Therefore, this paper proposes the Nodule-CLIP model, which deeply mines the potential relationship between CT images, complex attributes of lung nodules, and benign and malignant attributes of lung nodules through a comparative learning method, and optimizes the model in the image feature extraction network by using its similarities and differences to improve its ability to distinguish similar lung nodules. Firstly, we segment the 3D lung nodule information by U-Net to reduce the interference caused by the background of lung nodules and focus on the lung nodule images. Secondly, the image features, class features, and complex attribute features are aligned by contrastive learning and loss function in Nodule-CLIP to achieve lung nodule image optimization and improve classification ability. A series of testing and ablation experiments were conducted on the public dataset LIDC-IDRI, and the final benign and malignant classification rate was 90.6%, and the recall rate was 92.81%. The experimental results show the advantages of this method in terms of lung nodule classification as well as interpretability.

A gene signature linked to fibroblast differentiation for prognostic prediction of mesothelioma.

BACKGROUND: Malignant mesothelioma is a type of infrequent tumor that is substantially related to asbestos exposure and has a terrible prognosis. We tried to produce a fibroblast differentiation-related gene set for creating a novel classification and prognostic prediction model of MESO. METHOD: Three databases, including NCBI-GEO, TCGA, and MET-500, separately provide single-cell RNA sequencing data, bulk RNA sequencing profiles of MESO, and RNA sequencing information on bone metastatic tumors. Dimensionality reduction and clustering analysis were leveraged to acquire fibroblast subtypes in the MESO microenvironment. The fibroblast differentiation-related genes (FDGs), which were associated with survival and subsequently utilized to generate the MESO categorization and prognostic prediction model, were selected in combination with pseudotime analysis and survival information from the TCGA database. Then, regulatory network was constructed for each MESO subtype, and candidate inhibitors were predicted. Clinical specimens were collected for further validation. RESULT: A total of six fibroblast subtypes, three differentiation states, and 39 FDGs were identified. Based on the expression level of FDGs, three MESO subtypes were distinguished in the fibroblast differentiation-based classification (FDBC). In the multivariate prognostic prediction model, the risk score that was dependent on the expression level of several important FDGs, was verified to be an independently effective prognostic factor and worked well in internal cohorts. Finally, we predicted 24 potential drugs for the treatment of MESO. Moreover, immunohistochemical staining and statistical analysis provided further validation. CONCLUSION: Fibroblast differentiation-related genes (FDGs), especially those in low-differentiation states, might participate in the proliferation and invasion of MESO. Hopefully, the raised clinical subtyping of MESO would provide references for clinical practitioners.

Machine learning versus multivariate logistic regression for predicting severe COVID-19 in hospitalized children with Omicron variant infection.

With the emergence of the Omicron variant, the number of pediatric Coronavirus Disease 2019 (COVID-19) cases requiring hospitalization and developing severe or critical illness has significantly increased. Machine learning and multivariate logistic regression analysis were used to predict risk factors and develop prognostic models for severe COVID-19 in hospitalized children with the Omicron variant in this study. Of the 544 hospitalized children including 243 and 301 in the mild and severe groups, respectively. Fever (92.3%) was the most common symptom, followed by cough (79.4%), convulsions (36.8%), and vomiting (23.2%). The multivariate logistic regression analysis showed that age (1-3 years old, odds ratio (OR): 3.193, 95% confidence interval (CI): 1.778-5.733], comorbidity (OR: 1.993, 95% CI:1.154-3.443), cough (OR: 0.409, 95% CI:0.236-0.709), and baseline neutrophil-to-lymphocyte ratio (OR: 1.108, 95% CI: 1.023-1.200), lactate dehydrogenase (OR: 1.993, 95% CI: 1.154-3.443), blood urea nitrogen (OR: 1.002, 95% CI: 1.000-1.003) and total bilirubin (OR: 1.178, 95% CI: 1.005-3.381) were independent risk factors for severe COVID-19. The area under the curve (AUC) of the prediction models constructed by multivariate logistic regression analysis and machine learning (RandomForest + TomekLinks) were 0.7770 and 0.8590, respectively. The top 10 most important variables of random forest variables were selected to build a prediction model, with an AUC of 0.8210. Compared with multivariate logistic regression, machine learning models could more accurately predict severe COVID-19 in children with Omicron variant infection.

Large Microsphere Structure of a Co/C Composite Derived from Co-MOF with Excellent Wideband Electromagnetic Microwave Absorption Performance.

In the field of electromagnetic wave (EMW) absorption, carbon matrix materials based on metal-organic frameworks (MOFs) have drawn more interest as a result of their outstanding advantages, such as porous structure, lightweight, controlled morphology, etc. However, how to broaden the effective absorption bandwidth [EAB; reflection loss (RL) ≤ -10 dB] is still a challenge. In this paper, large microsphere structures of a Co/C composite composed of small particle clusters were successfully prepared by the solvothermal method and annealing treatment. At a filling ratio of 40 wt %, the Co/C composite shows attractive microwave absorption (MA) performance after being annealed at 600 °C in an atmosphere of argon. With an EAB of 6.32 GHz (9.92-16.24 GHz) and a thickness of just 2.57 mm, the minimum RL can be attained at -54.55 dB. Most importantly, the EAB can attain 7.12 GHz (10.88-18.0 GHz) when the thickness is 2.38 mm, which is larger than that of the majority of MOF-derived composites. The superior MA performance is strongly related to excellent impedance matching and a higher attenuation constant. This study provides a simple strategy for synthesizing a MOF-derived Co/C composite with a wide EAB.

An overview of Twist1 in glioma progression and recurrence.

Glioma cells are characterized by high migration ability, resulting in the aggressive growth of the tumors and poor prognosis of patients. Epithelial-to-mesenchymal transition (EMT) is one of the most important steps for tumor migration and metastasis and be elevated during glioma progression and recurrence. Twist1 is a basic helix-loop-helix transcription factor and a key transcription factor involved in the process of EMT. Twist1 is related to glioma mesenchymal change, invasion, heterogeneity, self-renewal of tumor stem cells, angiogenesis, etc., and may be used as a prognostic indicator and therapeutic target for glioma patients. This paper mainly reviews the structural characteristics, regulatory mechanisms, and apparent regulation of Twist1, as well as the roles of Twist1 during glioma progression and recurrence, providing new revelations for its use as a potential drug target and glioma treatment research.

RBP7 Regulated by EBF1 Affects Th2 Cells and the Oocyte Meiosis Pathway in Bone Metastases of Bladder Urothelial Carcinoma.

BACKGROUND: Bladder urothelial carcinoma (BLCA) is a malignancy with a high incidence worldwide. One-third of patients may experience aggressive progression later on, and 70% of patients who have undergone surgical intervention will still suffer from metastasis. MATERIALS AND METHODS: RNA sequencing profiles of BLCA samples were obtained from The Cancer Genome Atlas (TCGA) database. Differential expression and univariate Cox regression analyses were performed to identify prognosis-related differentially expressed immune genes (DEIGs). Subsequently, a proportional hazards model of DEIGs was then constructed by univariate regression analysis. Differential expression and correlation analyses, CIBERSORT, Single Sample Gene Set Enrichment Analysis (ssGSEA), GSVA were conducted on transcription factors (TFs), immune cells/pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The regulation network was then constructed. Eventually, ATAC-seq, ChIP-seq, scRNA-seq, and multiple online databases were employed for further validation. RESULTS: A proportional hazards model of 31 DEIGs was constructed and risk score was calculated and proven to be a independent prognostic factor. Then 5 immune genes were characterized to be significantly correlated with bone metastasis, stage and TF expression simultaneously. 4 TFs were identified to be significantly correlated with prognosis and RBP7 expression. 5 immune cells/pathways were revealed to be significantly correlated with RBP7 expression. Only 1 KEGG pathway was identified to be significant in Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) analyses. The regulatory relationship was then constructed, in which the correlation between EBF1 and RBP7 (R = 0.677, p < 0.001), Th2 cells and RBP7 (R = 0.23, p < 0.001), the oocyte meiosis pathway and RBP7 (R = 0.14, p = 0.042) were the most statistically significant. The results were further confirmed by Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), single-cell RNA sequencing (scRNA-seq), and multiple online databases validation. CONCLUSIONS: This study revealed that the EBF1-RBP7 regulatory relationship had potential importance in the bone metastasis in BLCA through Th2 cells and the oocyte meiosis pathway.

Gender-specific lncRNA-miRNA-mRNA regulatory network to reveal potential genes for primary open-angle glaucoma.

BACKGROUND: Investigation of biomarkers may facilitate understanding the mechanisms of primary open-angle glaucoma (POAG) and developing therapeutic targets. This study aimed to identify potential genes based on competing endogenous RNA (ceRNA) network for POAG. METHODS: Based on long noncoding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs (mRNAs) from the Gene Expression Omnibus (GEO) database, we identified differential expressed lncRNAs (DELs), differential expressed miRNAs (DEMis) and differential expressed mRNAs (DEMs) and then constructed a ceRNA network. Through weighted gene co-expression network analysis (WGCNA), we identified gender-specific genes for gender-associated ceRNA network construction, followed by the protein-protein interaction (PPI) network and functional enrichment analysis to screen hub genes and reveal their functions. The expression levels of hub genes were measured in steroid-induced ocular hypertension (SIOH) mice. RESULTS: A total of 175 DELs, 727 DEMs and 45 DEMis were screened between control and POAG samples. Seven modules were identified through WGCNA and one module was associated with gender of POAG patients. We discovered 41 gender-specific genes for gender-associated ceRNA construction and then identified 8 genes (NAV3, C1QB, RXRB, P2RY4, ADAM15, VAV3, ZNF207 and TOP1), which were enriched in cell cycle-related pathways and immune-related pathways. C1QB, RXRB, Top1 and ZNF207 were highly interacted with other proteins. The expression levels of NAV3 and C1QB were downregulated in SIOH, while the levels of RXRB, P2RY4, ADAM15, VAV3, ZNF207 and TOP1 were upregulated in SIOH. CONCLUSION: This study identifies hub genes associated with the pathogenesis of gender-specific POAG and provides potential biomarkers for POAG.

Allelic variations of ClACO gene improve nitrogen uptake via ethylene-mediated root architecture in watermelon.

KEY MESSAGE: The ClACO gene encoding 1-aminocyclopropane-1-carboxylate oxidase enabled highly efficient 15N uptake in watermelon. Nitrogen is one of the most essential nutrient elements that play a pivotal role in regulating plant growth and development for crop productivity. Elucidating the genetic basis of high nitrogen uptake is the key to improve nitrogen use efficiency for sustainable agricultural productivity. Whereas previous researches on nitrogen absorption process are mainly focused on a few model plants or crops. To date, the causal genes that determine the efficient nitrogen uptake of watermelon have not been mapped and remains largely unknown. Here, we fine-mapped the 1-aminocyclopropane-1-carboxylate oxidase (ClACO) gene associated with nitrogen uptake efficiency in watermelon via bulked segregant analysis (BSA). The variations in the ClACO gene led to the changes of gene expression levels between two watermelon accessions with different nitrogen uptake efficiencies. Intriguingly, in terms of the transcript abundance of ClACO, it was concomitant with significant differences in ethylene evolutions in roots and root architectures between the two accessions and among the different genotypic offsprings of the recombinant BC2F1(ZJU132)-18. These findings suggest that ethylene as a negative regulator altered nitrogen uptake efficiency in watermelon by controlling root development. In conclusion, our current study will provide valuable target gene for precise breeding of 'green' watermelon varieties with high-nitrogen uptake efficiencies.

Multicenter evaluation of a simple and sensitive nucleic acid self-testing for SARS-CoV-2.

A rapid and accurate COVID-19 diagnosis is a prerequisite for blocking the source of infection as soon as possible and taking the appropriate medical action. Herein, we developed GeneClick, a device for nucleic acid self-testing of SARS-CoV-2, consisting of three modules: a sampling kit, a microfluidic chip-based disposable cartridge, and an amplification reader. In addition, we evaluated the clinical performance of GeneClick using 2162 nasal swabs collected at three medical institutions, using three commercial RT-qPCR kits and an antigen self-test as references. Compared to RT-qPCR, the sensitivity and specificity of the GeneClick assay were 97.93% and 99.72%, respectively, with a kappa value of 0.979 (P â€‹< â€‹0.01). Of the 2162 samples, 2076 were also tested for SARS-CoV-2 antigens. Among the 314 positive samples identified by GeneClick assay, 63 samples were undetected by antigen tests. Overall, the GeneClick nucleic acid self-test demonstrated higher accuracy than the antigen-based detection. Based on the additional features, including simple operation, affordable price, portable device, and reliability of smartphone APP-driven sampling and result reporting, GeneClick offers a powerful tool for field-based SARS-CoV-2 detection in primary healthcare institutions or at-home use.

Pan-genome analysis sheds light on structural variation-based dissection of agronomic traits in melon crops.

Sweetness and appearance of fresh fruits are key palatable and preference attributes for consumers and are often controlled by multiple genes. However, fine-mapping the key loci or genes of interest by single genome-based genetic analysis is challenging. Herein, we present the chromosome-level genome assembly of 1 landrace melon accession (Cucumis melo ssp. agrestis) with wild morphologic features and thus construct a melon pan-genome atlas via integrating sequenced melon genome datasets. Our comparative genomic analysis reveals a total of 3.4 million genetic variations, of which the presence/absence variations (PAVs) are mainly involved in regulating the function of genes for sucrose metabolism during melon domestication and improvement. We further resolved several loci that are accountable for sucrose contents, flesh color, rind stripe, and suture using a structural variation (SV)-based genome-wide association study. Furthermore, via bulked segregation analysis (BSA)-seq and map-based cloning, we uncovered that a single gene, (CmPIRL6), determines the edible or inedible characteristics of melon fruit exocarp. These findings provide important melon pan-genome information and provide a powerful toolkit for future pan-genome-informed cultivar breeding of melon.

Chronic hypotony management using endoscopy-assisted vitrectomy after severe ocular trauma or vitrectomy.

AIM: To report outcomes of endoscopy-assisted vitrectomy (EAV) in patients with chronic hypotony following severe ocular trauma or vitrectomy. METHODS: This was a retrospective, noncomparative case series. Ciliary bodies were evaluated using ultrasound biomicroscopy pre-operatively and direct visualisation intraoperatively. All selected individuals (seven patients/seven eyes) underwent EAV. Removal of ciliary membrane and traction, gas/silicone oil tamponade (GT/SOT), and scleral buckling (SB) were performed in selected eyes. Outcome measurements mainly included intraocular pressure (IOP) and best-corrected visual acuity (BCVA). RESULTS: Seven eyes from 7 male aphakic patients with a mean age of 45 (range, 20-68)y were included in this study; the average follow-up time was 12 (9-15)mo. GT was performed in 2 eyes; membrane peeling (MP) and SOT in 2 eyes; and MP, SOT, and SB in 3 eyes. The mean pre- and post-operative IOP were 4.5 (range, 4.0±0.11 to 4.8±0.2) mm Hg and 9.9 (range, 5.6±0.17 to 12.1±0.2) mm Hg at 52wk (12mo), respectively. BCVA improved in six eyes; one eye still showed light perception, and no bulbi phthisis was observed. CONCLUSION: Endoscopy offers improved judgment and recognition and has an improved prognosis for chronic hypotony. Therefore, endoscopy can be an effective and promising operative technique for chronic traumatic hypotony management.

A rapid and highly sensitive multiple detection of human adenovirus type 3, type 7 and respiratory syncytial virus by recombinase-aided reverse transcription PCR.

BACKGROUND: Polymerase chain reaction (PCR) has been widely used for many pathogen detection. However, PCR technology still suffers from long detection time and insufficient sensitivity. Recombinase-aided amplification (RAA) is a powerful nucleic acid detection tool with high sensitivity and amplification efficiency, but its complex probes and inability of multiplex detection hinder the further application of this technology. METHODS: In this study, we developed and validated the multiplex reverse transcription recombinase-aided PCR (multiplex RT-RAP) assay for human adenovirus 3 (HADV3), human adenovirus 7 (HADV7), and human respiratory syncytial virus (HRSV) within 1 h with Human RNaseP protein as a reference gene to monitor the whole process. RESULTS: Using recombinant plasmids, the sensitivity of multiplex RT-RAP for the detection of HADV3, HADV7, and HRSV was 18, 3, and 18 copies per reaction, respectively. The multiplex RT-RAP showed no cross-reactivity with other respiratory viruses, demonstrating its good specificity. A total of 252 clinical specimens were tested by multiplex RT-RAP and the results were found to be consistent with those of corresponding RT-qPCR assays. After testing serial dilutions of selected positive specimens, the detection sensitivity of multiplex RT-RAP was two to eightfold higher than that of corresponding RT-qPCR. CONCLUSION: We conclude the multiplex RT-RAP is a robust, rapid, highly sensitive, and specific assay with the potential to be used in the screening of clinical samples with low viral load.

CRISPR/Cas9-mediated genome editing of gustatory receptor NlugGr23a causes male sterility in the brown planthopper Nilaparvata lugens.

Gustatory receptors (Grs) have an essential role in chemical recognition so as to evaluate food quality. Insect Grs also participate in non-gustatory functions, such as olfaction, temperature sensing, and mating. In this study, we knocked out NlugGr23a, a putative fecundity-related Gr, using the CRISPR/Cas9 system in the brown planthopper Nilaparvata lugens, a serious insect pest of rice. Surprisingly, homozygous NlugGr23a mutant (NlugGr23a-/-) males were sterile but their sperm were motile and morphologically normal. DAPI staining of mutant sperm inseminated eggs showed that most of NlugGr23a-/- sperm failed to fertilize eggs, even if they were capable of entering into the egg as a result of their arrested development prior to male pronucleus formation. Immunohistochemistry demonstrated the expression of NlugGr23a in testis. Moreover, prior mating by NlugGr23a-/- males suppressed female fertility. To our knowledge, it is the first report that a chemoreceptor is implicated in male sterility and provides a potential molecular target for genetic pest control alternatives.

COVID-19 and employee job performance trajectories: The moderating effect of different sources of status.

This study investigates the impact of the COVID-19 pandemic on employee job performance trajectories, and further examines the moderating effects of different sources of status. Drawing from event system theory (EST), we propose that employee job performance decreases upon COVID-19 onset, but gradually increases during the postonset period. Furthermore, we argue that status from society, occupation, and workplace functions to moderate such performance trajectories. We test our hypotheses with a unique dataset of 708 employees that combines survey responses and job performance archival data over 21 consecutive months (10,808 observations) spanning the preonset, onset, and postonset periods of the initial encounter with COVID-19 in China. Utilizing discontinuous growth modeling (DGM), our findings indicate that the onset of COVID-19 created an immediate decrease in job performance, but such decrease was weakened by higher occupation and/or workplace status. However, the postonset period resulted in a positive employee job performance trajectory, which was strengthened for employees with lower occupational status. These findings enrich our understanding of COVID-19's impact on employee job performance trajectories, highlight the role of status in moderating such changes over time, and also provide practical implications to understand employee performance when facing such a crisis.

Sequencing technology as a major impetus in the advancement of studies into rheumatism: A bibliometric study.

Background: Rheumatism covers a wide range of diseases with complex clinical manifestations and places a tremendous burden on humans. For many years, our understanding of rheumatism was seriously hindered by technology constraints. However, the increasing application and rapid advancement of sequencing technology in the past decades have enabled us to study rheumatism with greater accuracy and in more depth. Sequencing technology has made huge contributions to the field and is now an indispensable component and powerful tool in the study of rheumatism. Methods: Articles on sequencing and rheumatism, published from 1 January 2000 to 25 April 2022, were retrieved from the Web of Science™ (Clarivate™, Philadelphia, PA, USA) database. Bibliometrix, the open-source tool, was used for the analysis of publication years, countries, authors, sources, citations, keywords, and co-words. Results: The 1,374 articles retrieved came from 62 countries and 350 institutions, with a general increase in article numbers during the last 22 years. The leading countries in terms of publication numbers and active cooperation with other countries were the USA and China. The most prolific authors and most popular documents were identified to establish the historiography of the field. Popular and emerging research topics were assessed by keywords and co-occurrence analysis. Immunological and pathological process in rheumatism, classification, risks and susceptibility, and biomarkers for diagnosis were among the hottest themes for research. Conclusions: Sequencing technology has been widely applied in the study of rheumatism and propells research in the area of discovering novel biomarkers, related gene patterns and physiopathology. We suggest that further efforts be made to advance the study of genetic patterns related to rheumatic susceptibility, pathogenesis, classification and disease activity, and novel biomarkers.

Pan-cancer analysis reveals signal transducer and activator of transcription (STAT) gene family as biomarkers for prognostic prediction and therapeutic guidance.

Background: The signal transducer and activator of transcription (STAT) gene family have been widely found to regulate cell proliferation, differentiation, apoptosis, and angiogenesis through complex signaling pathways, and thus impacting tumor formation and development in different types of tumor. However, the roles of STATs on prognostic prediction and therapeutic guidance in pan-cancer remain unexplored. Materials and Methods: The dataset of 33 types of TCGA tumor, para-carcinoma and normal tissues, was obtained from the UCSC Xena database, including the gene expression profiles in the formats of FPKM value, demographic characteristics, clinical information, and survival data of STATs. Differential expression and co-expression analyses, WGCNA, clinical relevance analysis, immune subtype analysis, tumor stemness analysis, tumor purity analysis, immune infiltration analysis, immunotherapy related analysis, tumor mutation related analysis, and drug sensitivity analysis were performed by R software. Results: Differential expression of STAT1 was found between normal and BRCA tissues (p < 0.001, log2FC = 0.895). Additionally, the strongest correlation among STATs lied between STAT1 and STAT2 (correlation coefficient = 0.6). Moreover, high expression levels of STAT1 (p = 0.031) were revealed to be notably correlated with poor prognosis in KIRP. In addition, STAT1 expressed the highest value in immune subtypes C1, C2, C3, and C6 in LUAD. What's more, strong negative correlations were demonstrated between expression of STAT6 and mDNAss and mRNAss of TGCT. Additionally, STAT4 expression was characterized to be significantly negatively correlated with tumor purity of the majority of cancer types. Moreover, STAT1 and STAT3 were shown to be generally high-expressed in pan-cancer myeloid cells, and STATs all had positive correlation with the infiltration of the majority of immune cells. In addition, STATs were revealed to be closely linked with immunotherapy response. What's more, STAT4 expression was identified to have a strong negative correlation with TMB value in DLBC. Last but not least, positive correlations were accessed between STAT5 and sensitivity of Nelarabine (cor = 0.600, p < 0.001). Conclusion: In the present study, we identified STATs as biomarkers for prognostic prediction and therapeutic guidance in pan-cancer. Hopefully our findings could provide a valuable reference for future STATs research and clinical applications.

Oxalic Acid Inhibits Feeding Behavior of the Brown Planthopper via Binding to Gustatory Receptor Gr23a.

Plants produce diverse secondary compounds as natural protection against microbial and insect attack. Most of these compounds, including bitters and acids, are sensed by insect gustatory receptors (Grs). Although some organic acids are attractive at low or moderate levels, most acidic compounds are potentially toxic to insects and repress food consumption at high concentrations. At present, the majority of the reported sour receptors function in appetitive behaviors rather than aversive taste responses. Here, using two different heterologous expression systems, the insect Sf9 cell line and the mammalian HEK293T cell line, we started from crude extracts of rice (Oryza sativa) and successfully identified oxalic acid (OA) as a ligand of NlGr23a, a Gr in the brown planthopper Nilaparvata lugens that feeds solely on rice. The antifeedant effect of OA on the brown planthopper was dose dependent, and NlGr23a mediated the repulsive responses to OA in both rice plants and artificial diets. To our knowledge, OA is the first identified ligand of Grs starting from plant crude extracts. These findings on rice-planthopper interactions will be of broad interest for pest control in agriculture and also for better understanding of how insects select host plants.

A bibliometric analysis of the role of microbiota in trauma.

Introduction: Over the last several decades, the gut microbiota has been implicated in the formation and stabilization of health, as well as the development of disease. With basic and clinical experiments, scholars are gradually understanding the important role of gut microbiota in trauma, which may offer novel ideas of treatment for trauma patients. In this study, we purposed to summarize the current state and access future trends in gut microbiota and trauma research. Methods: We retrieved relevant documents and their published information from the Web of Science Core Collection (WoSCC). Bibliometrix package was responsible for the visualized analysis. Results: Totally, 625 documents were collected and the number of annual publications kept increasing, especially from 2016. China published the most documents while the USA had the highest local citations. The University of Colorado and Food & Function are respectively the top productive institution and journal, as PLOS One is the most local cited journal. With the maximum number of articles and local citations, Deitch EA is supported to be the most contributive author. Combining visualized analysis of keywords and documents and literature reading, we recognized two key topics: bacteria translocation in trauma and gut microbiota's effect on inflammation in injury, especially in nervous system injury. Discussion: The impact of gut microbiota on molecular and pathological mechanism of inflammation is the focus now. In addition, the experiments of novel therapies based on gut microbiota's impact on trauma are being carried out. We hope that this study can offer a birds-eye view of this field and promote the gradual improvement of it.

Global trends in research of fibroblasts associated with rheumatoid diseases in the 21st century: A bibliometric analysis.

Background: Rheumatoid Diseases (RDs) are a group of systemic auto-immune diseases that are characterized by chronic synovitis, and fibroblast-like synoviocytes (FLSs) play an important role in the occurrence and progression of synovitis. Our study is the first to adopt bibliometric analysis to identify the global scientific production and visualize its current distribution in the 21st century, providing insights for future research through the analysis of themes and keywords. Methods: We obtained scientific publications from the core collection of the Web of Science (WoS) database, and the bibliometric analysis and visualization were conducted by Biblioshiny software based on R-bibliometrix. Results: From 2000 to 2022, a total of 3,391 publications were reviewed. China is the most prolific country (n = 2601), and the USA is the most cited country (cited 7225 times). The Center of Experimental Rheumatology at University Hospital Zürich supported the maximum number of articles (n = 40). Steffen Gay published 85 records with 6263 total citations, perhaps making him the most impactful researcher. Arthritis and Rheumatism, Annals of Rheumatic Diseases, and Rheumatology are the top three journals. Conclusion: The current study revealed that rheumatoid disease (RD)-related fibroblast studies are growing. Based on the bibliometric analysis, we summarized three important topics: activation of different subsets of fibroblasts; regulation of fibroblast function; and in vitro validation of existing discoveries. They are all valuable directions, which provide reference and guidance for researchers and clinicians engaged in the research of RDs and fibroblasts.

Ligand dose-dependent activation of signaling pathways through the gustatory receptor NlGr11 linked to feeding efficacy in Nilaparvata lugens.

Insects often face both conditions with sufficient nutrients and conditions of undernutrition in the field. Through gustatory receptors, insects sense nutrients and regulate their physiological functions such as feeding and reproduction. However, it remains unclear whether signaling pathways activated by gustatory receptors depend on the concentration of nutrients and whether the difference in signaling pathways directly affects insects' physiological functions. Herein, we found that a sugar gustatory receptor, NlGr11, from the brown planthopper (BPH), Nilaparvata lugens, activated G protein-coupled signaling and ionotropic pathways when bound to high galactose concentration. BPHs subsequently demonstrated longer feeding times, feeding loads, and higher vitellogenin (NlVg) expression than BPHs exposed to high galactose concentrations, which only activated the ionotropic pathway. For the first time, our findings link plant nutrient conditions, signaling pathways activated by nutrients, and their gustatory receptors, and nutrient dose-dependent feeding efficacy and vitellogenin (Vg) expression in an insect. This will help us to better understand the molecular mechanism for insect feeding strategies on plants at different stages of nutritional conditions.