scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets.

Undoubtedly, single-cell RNA sequencing (scRNA-seq) has changed the research landscape by providing insights into heterogeneous, complex and rare cell populations. Given that more such data sets will become available in the near future, their accurate assessment with compatible and robust models for cell type annotation is a prerequisite. Considering this, herein, we developed scAnno (scRNA-seq data annotation), an automated annotation tool for scRNA-seq data sets primarily based on the single-cell cluster levels, using a joint deconvolution strategy and logistic regression. We explicitly constructed a reference profile for human (30 cell types and 50 human tissues) and a reference profile for mouse (26 cell types and 50 mouse tissues) to support this novel methodology (scAnno). scAnno offers a possibility to obtain genes with high expression and specificity in a given cell type as cell type-specific genes (marker genes) by combining co-expression genes with seed genes as a core. Of importance, scAnno can accurately identify cell type-specific genes based on cell type reference expression profiles without any prior information. Particularly, in the peripheral blood mononuclear cell data set, the marker genes identified by scAnno showed cell type-specific expression, and the majority of marker genes matched exactly with those included in the CellMarker database. Besides validating the flexibility and interpretability of scAnno in identifying marker genes, we also proved its superiority in cell type annotation over other cell type annotation tools (SingleR, scPred, CHETAH and scmap-cluster) through internal validation of data sets (average annotation accuracy: 99.05%) and cross-platform data sets (average annotation accuracy: 95.56%). Taken together, we established the first novel methodology that utilizes a deconvolution strategy for automated cell typing and is capable of being a significant application in broader scRNA-seq analysis. scAnno is available at https://github.com/liuhong-jia/scAnno.

Impacts of abandoned sloping farmland on soil aggregates and aggregate-associated organic carbon in karst rocky desertification areas.

Vegetation restoration after the abandonment of sloping farmland can effectively promote the sequestration of soil organic carbon (SOC), with soil aggregates playing a pivotal role. However, in abandoned farmlands in karst regions with varying degrees of rocky desertification, the relationship between soil aggregates, aggregate-associated organic carbon (AAOC), and total SOC content remains unclear. Taking abandoned sloping farmlands (5 years, 10 years, and 15 years) with different levels of rocky desertification (no rocky desertification, potential rocky desertification, slight rocky desertification, and moderate rocky desertification) in a typical karst area as research objects, this study investigated the dynamic characteristics of the particle size distribution of soil aggregates, total SOC, and AAOC. The results indicated that total SOC content in the 0-20 cm soil layer increased after abandonment in all levels of rocky desertification, peaking after 15 years. The abandoned sloping farmland with moderate desertification showed the best recovery effect. Post-abandonment vegetation restoration increased the content of 5-10 mm soil aggregates, but decreased those of 1-2 mm and < 0.25 mm aggregates. Particularly for 5-10 mm aggregates, the contribution of AAOC to total SOC significantly increased over time. Moreover, a strong correlation was observed between >1 mm aggregates and total SOC (p < 0.05). The increase in total SOC was primarily driven by the growth of AAOC in 5-10 mm aggregates. In general, vegetation restoration is an effective approach for enhancing total SOC content in abandoned sloping farmland with varying degrees of rocky desertification.

Rapid typing diagnosis and clinical analysis of subtypes A and B of human respiratory syncytial virus in children.

BACKGROUND: Human respiratory syncytial virus (HRSV) is the leading pathogens causing acute respiratory infections (ARI) in children under five years old. We aimed to investigate the distribution of HRSV subtypes and explore the relationship between viral subtypes and clinical symptoms and disease severity. METHODS: From November 2016 to April 2017, 541 children hospitalized because of ARI were included in the study. Throat swabs were collected for analysis and all samples were tested by multiplex one-step qRT-PCR for quantitative analysis and typing of HRSV. Patients' demographics, clinical symptoms as well as laboratory and imaging results were retrieved from medical records. RESULTS: HRSV was detected in 19.6% of children hospitalized due to ARI. HRSV-positive children were younger (P < 0.001), had a higher frequency of wheezing and pulmonary rales (P < 0.001; P = 0.003), and were more likely to develop bronchopneumonia (P < 0.001). Interleukin (IL) 10、CD4/CD8 (below normal range) and C-reactive protein levels between subtypes A and B groups were significantly different (P = 0.037; P = 0.029; P = 0.007), and gender differences were evident. By age-stratified analysis between subtypes A and B, we found significant differences in fever frequency and lymphocyte ratio (P = 0.008; P = 0.03) in the 6-12 months age group, while the 12. 1-36 months age group showed significant differences in fever days and count of leukocytes, platelets, levels aspartate aminotransferase, IL-6, lactate dehydrogenase and proportion CD4 positive T cells(P = 0.013; P = 0.018; P = 0.016; P = 0.037; P = 0.049; P = 0.025; P = 0.04). We also found a positive correlation between viral load and wheezing days in subtype A (P < 0.05), and a negative correlation between age, monocyte percentage and LDH concentration in subtype B (P < 0.05). CONCLUSIONS: HRSV is the main causative virus of bronchopneumonia in infants and children. The multiplex one-step qRT-PCR not only provides a rapid and effective diagnosis of HRSV infection, but also allows its typing. There were no significant differences in the severity of HRSV infection between subtypes A and B, except significant gender-specific and age-specific differences in some clinical characteristics and laboratory results. Knowing the viral load of HRSV infection can help understanding the clinical features of different subtypes of HRSV infection.

Application of bone metabolic parameters in the diagnosis of growing pains.

OBJECTIVE: The present study aimed to assess the diagnostic significance of serum bone metabolic parameters in children with growing pains (GPs). METHODS: All patients diagnosed with GP and healthy controls matched with age and gender were recruited at the outpatient clinic of Children's Hospital at Zhejiang University School of Medicine from August 2016 to August 2021. In all subjects, serum levels of calcium (Ca), phosphorus (P), procollagen type-I N-terminal (PINP), parathormone (PTH), 25-hydroxyvitamin D (25-(OH)D), osteocalcin (OC), N-terminal cross-linked telopeptides of type-I collagen (CTX), and tartrate-resistant acid phosphatase type 5b (TRACP5b) were investigated. The univariate analysis, multivariate logistic regression analysis, and receiver operating characteristic (ROC) curve were used to identify the bone metabolic parameters factors for diagnosing GP. RESULTS: We enrolled 386 children with GP and 399 healthy controls in present study. The mean age of GP group was 5.319 years, and, primarily, the subjects were preschool-age children. The gender ratio (male-to-female) was 1.27 in GP group. After adjusting for age and gender, we identified that the serum levels of Ca (p < 0.001, OR: 25.039), P (p = 0.018, OR: 2.681), PINP (p < 0.001, OR: 1.002), and PTH (p = 0.036, OR: 0.988) were independent diagnostic factors associated with GP. Area under curve (AUC) of the ROC curves was in the order: PINP (0.612) > Ca (0.599) > P (0.583) > PTH (0.541). A combination of independent diagnostic factors and multivariable logistic regression analysis provided a refined logistic regression model to improve the diagnostic potential, of which the AUC had reached 0.655. CONCLUSIONS: Serum levels of Ca, P, PINP, and PTH could be independent diagnostic factors associated with GP. The logistic model was significantly superior to bone metabolic parameters for diagnosing GP.

Single symbiotic cell transcriptome sequencing of coral.

Zooxanthellae and coral can form an intracellular symbiotic system. Yet, little is known about the molecular mechanism underlying this symbiosis. In this study, we characterized the symbiosis based on analyses of gene expression at the single-cell level. Among 9110 single coral cells, we identified 4871 symbiotic cells based on the detection of both coral and zooxanthellae gene transcripts within a single cell. Using the bioinformatics tool Seurat, symbiotic cells were further clustered into five groups, 52 genes exhibited differential expression between groups. We proposed an index called the "symbiosis index", to indicate the degree of gene expression of both species in a single symbiotic cell. Interestingly, the index differed distinctly among the five groups. The symbiosis index was highly correlated with the expression of the coral gene gfas1.m1.6761 (ANKRD40), which encodes ankyrin repeat domain-containing protein 40 and is involved in DNA replication (r = 0.76). Two metabolism-related genes, DAGLA and betaGlu, were highly expressed in cells with a high symbiosis index. Four zooxanthellae genes, PRPF19, ATRN, aAA-ATPases and AK812-SmicGene44833, exhibited substantial changes in expression levels when zooxanthellae lived within coral. A trajectory analysis suggested that cells with a higher symbiosis index may be derived from those with a lower index during coral colony development. Taken together, our results provide evidence for zooxanthellae residing within coral, forming a symbiotic system. The symbiosis index is an effective indicator of different cell groups, with lineage relationships among groups. Additionally, we identified specific genes that exhibit expression changes in the symbiotic system.

[A review on integration methods for single-cell data].

The emergence of single-cell sequencing technology enables people to observe cells with unprecedented precision. However, it is difficult to capture the information on all cells and genes in one single-cell RNA sequencing (scRNA-seq) experiment. Single-cell data of a single modality cannot explain cell state and system changes in detail. The integrative analysis of single-cell data aims to address these two types of problems. Integrating multiple scRNA-seq data can collect complete cell types and provide a powerful boost for the construction of cell atlases. Integrating single-cell multimodal data can be used to study the causal relationship and gene regulation mechanism across modalities. The development and application of data integration methods helps fully explore the richness and relevance of single-cell data and discover meaningful biological changes. Based on this, this article reviews the basic principles, methods and applications of multiple scRNA-seq data integration and single-cell multimodal data integration. Moreover, the advantages and disadvantages of existing methods are discussed. Finally, the future development is prospected.

A deconvolution method and its application in analyzing the cellular fractions in acute myeloid leukemia samples.

BACKGROUND: The identification of cell type-specific genes (markers) is an essential step for the deconvolution of the cellular fractions, primarily, from the gene expression data of a bulk sample. However, the genes with significant changes identified by pair-wise comparisons cannot indeed represent the specificity of gene expression across multiple conditions. In addition, the knowledge about the identification of gene expression markers across multiple conditions is still paucity. RESULTS: Herein, we developed a hybrid tool, LinDeconSeq, which consists of 1) identifying marker genes using specificity scoring and mutual linearity strategies across any number of cell types, and 2) predicting cellular fractions of bulk samples using weighted robust linear regression with the marker genes identified in the first stage. On multiple publicly available datasets, the marker genes identified by LinDeconSeq demonstrated better accuracy and reproducibility compared to MGFM and RNentropy. Among deconvolution methods, LinDeconSeq showed low average deviations (≤0.0958) and high average Pearson correlations (≥0.8792) between the predicted and actual fractions on the benchmark datasets. Importantly, the cellular fractions predicted by LinDeconSeq appear to be relevant in the diagnosis of acute myeloid leukemia (AML). The distinct cellular fractions in granulocyte-monocyte progenitor (GMP), lymphoid-primed multipotent progenitor (LMPP) and monocytes (MONO) were found to be closely associated with AML compared to the healthy samples. Moreover, the heterogeneity of cellular fractions in AML patients divided these patients into two subgroups, differing in both prognosis and mutation patterns. GMP fraction was the most pronounced between these two subgroups, particularly, in SubgroupA, which was strongly associated with the better AML prognosis and the younger population. Totally, the identification of marker genes by LinDeconSeq represents the improved feature for deconvolution. The data processing strategy with regard to the cellular fractions used in this study also showed potential for the diagnosis and prognosis of diseases. CONCLUSIONS: Taken together, we developed a freely-available and open-source tool LinDeconSeq ( https://github.com/lihuamei/LinDeconSeq ), which includes marker identification and deconvolution procedures. LinDeconSeq is comparable to other current methods in terms of accuracy when applied to benchmark datasets and has broad application in clinical outcome and disease-specific molecular mechanisms.

Genome organization in proximity to the BAP1 locus appears to play a pivotal role in a variety of cancers.

Cancer studies primarily focus on the characterization of the key driver genes and the underlying pathways. However, the contribution of other cancer-associated genes located in the genomic neighborhood of the driver genes could help to understand further aspects of cancer progression. Given the frequent involvement of chromosome 3 in multiple human cancers, in particular in the form of the prognostically highly relevant monosomy 3 in uveal melanoma (UM), we investigated the cumulative impact of cancer-associated genes on chromosome 3. Our analysis showed that these genes are enriched with repetitive elements with genes surrounded by distinctive repeats (MIR, hAT-Charlie, ERVL-MaLR, LINE-2, and simple/low complexity) in the promoter being more precisely associated with cancer-related pathways than the ones with major transposable elements (SINE/Alu and LINE-1). Additionally, these genes showed strong intrachromosomal chromatin interactions in 3D nuclear organization. Further investigations revealed a genomic hotspot in the vicinity of BAP1 locus, which is affected in 27 types of different cancers and contains abundant noncoding RNAs that are often expressed in a tissue-specific manner. The cross-species comparison of these cancer-associated genes revealed mostly a shared synteny in closer primates. However, near to the BAP1 locus signs of chromosomal inversions were observed during the course of evolution. To our knowledge, this is the first study to characterize the entire genomic neighborhood of cancer-associated genes located on any single chromosome. Based on our results, we hypothesize that monosomy of chromosome 3 will have important clinical and molecular consequences in the respective diseases and in particular in UM.

The antitumor effect of static and extremely low frequency magnetic fields against nephroblastoma and neuroblastoma.

Certain magnetic fields (MF) have potential therapeutic antitumor effect whereas the underlying mechanism remains undefined. In this study, a well-characterized MF was applied to two common childhood malignancies, nephroblastoma and neuroblastoma. This MF has a time-averaged total intensity of 5.1 militesla (mT), and was generated as a superimposition of a static and an extremely low frequency (ELF) MF in 50 Hertz (Hz). In nephroblastoma and neuroblastoma cell lines including G401, CHLA255, and N2a, after MF exposure of 2 h per day, the cell viability decreased significantly after 2 days. After 3 days, inhibition rates of 17-22% were achieved in these cell lines. Furthermore, the inhibition rate was positively associated with exposure time. On the other hand, when using static MF only while maintaining the same time-averaged intensity of 5.1 mT, the inhibition rate was decreased. Thus, both time and combination of ELF field were positively associated with the inhibitory effect of this MF. Exposure to the field decreased cell proliferation and induced apoptosis. Combinational use of MF together with chemotherapeutics cisplatin (DDP) was performed in both in vitro and in vivo experiments. In cell lines, combinational treatment further increased the inhibition rate compared with single use of either DDP or MF. In G401 nephroblastoma tumor model in nude mice, combination of MF and DDP resulted in significant decrease of tumor mass, and the side effect was limited in mild liver injury. MF exposure by itself did not hamper liver or kidney functions. In summary, the antitumor effect of an established MF against neuroblastoma and nephroblastoma is reported, and this field has the potential to be used in combination with DDP to achieve increased efficacy and reduce side effects in these two childhood malignancies. Bioelectromagnetics. 39:375-385, 2018. © 2018 Wiley Periodicals, Inc.

New dating of the Homo erectus cranium from Lantian (Gongwangling), China.

The Homo erectus cranium from Gongwangling, Lantian County, Shaanxi Province is the oldest fossil hominin specimen from North China. It was found in 1964 in a layer below the Jaramillo subchron and was attributed to loess (L) L15 in the Chinese loess-palaeosol sequence, with an estimated age of ca. 1.15 Ma (millions of years ago). Here, we demonstrate that there is a stratigraphical hiatus in the Gongwangling section immediately below loess 15, and the cranium in fact lies in palaeosol (S) S22 or S23, the age of which is ca. 1.54-1.65 Ma. Closely spaced palaeomagnetic sampling at two sections at Gongwangling and one at Jiacun, 10 km to the north, indicate that the fossil layer at Gongwangling and a similar fossil horizon at Jiacun were deposited shortly before a short period of normal polarity above the Olduvai subchron. This is attributed to the Gilsa Event that has been dated elsewhere to ca. 1.62 Ma. Our investigations thus demonstrate that the Gongwangling cranium is slightly older than ca. 1.62 Ma, probably ca. 1.63 Ma, and significantly older than previously supposed. This re-dating now makes Gongwangling the second oldest site outside Africa (after Dmanisi) with cranial remains, and causes substantial re-adjustment in the early fossil hominin record in Eurasia.

Discovery of an independent poor-prognosis subtype associated with tertiary lymphoid structures in breast cancer.

Introduction: Tertiary lymphoid structures (TLSs) are ectopic lymphoid formations that arise in non-lymphoid tissues due to chronic inflammation. The pivotal function of TLSs in regulating tumor invasion and metastasis has been established across several cancers, such as lung cancer, liver cancer, and melanoma, with a positive correlation between increased TLS presence and improved prognosis. Nevertheless, the current research about the clinical significance of TLSs in breast cancer remains limited. Methods: In our investigation, we discovered TLS-critical genes that may impact the prognosis of breast cancer patients, and categorized breast cancer into three distinct subtypes based on critical gene expression profiles, each exhibiting substantial differences in prognosis (p = 0.0046, log-rank test), with Cluster 1 having the best prognosis, followed by Cluster 2, and Cluster 3 having the worst prognosis. We explored the impact of the heterogeneity of these subtypes on patient prognosis, the differences in the molecular mechanism, and their responses to drug therapy and immunotherapy. In addition, we designed a machine learning-based classification model, unveiling highly consistent prognostic distinctions in several externally independent cohorts. Results: A notable marker gene CXCL13 was identified in Cluster 3, potentially pivotal in enhancing patient prognosis. At the single-cell resolution, we delved into the adverse prognosis of Cluster 3, observing an enhanced interaction between fibroblasts, myeloid cells, and basal cells, influencing patient prognosis. Furthermore, we identified several significantly upregulated genes (CD46, JAG1, IL6, and IL6R) that may positively correlate with cancer cells' survival and invasive capabilities in this subtype. Discussion: Our study is a robust foundation for precision medicine and personalized therapy, presenting a novel perspective for the contemporary classification of breast cancer.

scAnnoX: an R package integrating multiple public tools for single-cell annotation.

Background: Single-cell annotation plays a crucial role in the analysis of single-cell genomics data. Despite the existence of numerous single-cell annotation algorithms, a comprehensive tool for integrating and comparing these algorithms is also lacking. Methods: This study meticulously investigated a plethora of widely adopted single-cell annotation algorithms. Ten single-cell annotation algorithms were selected based on the classification of either reference dataset-dependent or marker gene-dependent approaches. These algorithms included SingleR, Seurat, sciBet, scmap, CHETAH, scSorter, sc.type, cellID, scCATCH, and SCINA. Building upon these algorithms, we developed an R package named scAnnoX for the integration and comparative analysis of single-cell annotation algorithms. Results: The development of the scAnnoX software package provides a cohesive framework for annotating cells in scRNA-seq data, enabling researchers to more efficiently perform comparative analyses among the cell type annotations contained in scRNA-seq datasets. The integrated environment of scAnnoX streamlines the testing, evaluation, and comparison processes among various algorithms. Among the ten annotation tools evaluated, SingleR, Seurat, sciBet, and scSorter emerged as top-performing algorithms in terms of prediction accuracy, with SingleR and sciBet demonstrating particularly superior performance, offering guidance for users. Interested parties can access the scAnnoX package at https://github.com/XQ-hub/scAnnoX.

Exploration of the role of oxidative stress-related genes in LPS-induced acute lung injury via bioinformatics and experimental studies.

During the progression of acute lung injury (ALI), oxidative stress and inflammatory responses always promote each other. The datasets analyzed in this research were acquired from the Gene Expression Omnibus (GEO) database. The Weighted Gene Co-expression Network Analysis (WGCNA) and limma package were used to obtain the ALI-related genes (ALIRGs) and differentially expressed genes (DEGs), respectively. In total, two biological markers (Gch1 and Tnfaip3) related to oxidative stress were identified by machine learning algorithms, Receiver Operator Characteristic (ROC), and differential expression analyses. The area under the curve (AUC) value of biological markers was greater than 0.9, indicating an excellent power to distinguish between ALI and control groups. Moreover, 15 differential immune cells were selected between the ALI and control samples, and they were correlated to biological markers. The transcription factor (TF)-microRNA (miRNA)-Target network was constructed to explore the potential regulatory mechanisms. Finally, based on the quantitative reverse transcription polymerase chain reaction (qRT-PCR), the expression of Gch1 and Tnfaip3 was significantly higher in ALI lung tissue than in healthy controls. In conclusion, the differences in expression profiles between ALI and normal controls were found, and two biological markers were identified, providing a research basis for further understanding the pathogenesis of ALI.

Immune microenvironment heterogeneity reveals distinct subtypes in neuroblastoma: insights into prognosis and therapeutic targets.

BACKGROUND: Neuroblastoma (NB) is a childhood cancer originating from immature nerve cells in the sympathetic nervous system. Current clinical and molecular subtyping methods for NB have limitations in providing accurate prognostic information and guiding treatment decisions. RESULTS: To overcome these challenges, we explored the microenvironment of NB based on the knowledge-based functional gene expression signatures (Fges), which revealed heterogeneous subtypes. Consensus clustering of Fges activity scores identified three subtypes (Cluster 1, Cluster 2, and Cluster 3) that demonstrated significant differences in prognosis compared to mainstream subtypes. We assessed the immune infiltration, immunogenicity, CD8T cytotoxicity, and tumor purity of these subtypes, uncovering their distinct biological functions. Cluster 1 and Cluster 2 exhibited higher immunoreactivity, while Cluster 3 displayed higher tumor purity and poor prognosis. Gene ontology annotation and pathway analysis identified immune activation in Cluster 1, epithelial-mesenchymal transition (EMT) in Cluster 2, and cell cycle processes in Cluster 3. Notably, the impact of EMT activity on prognosis may vary across NB subtypes. A classification model using XGBoost accurately predicted subtypes in independent NB cohorts, with significant prognostic differences. GPR125, CDK4, and GREB1 emerged as potential therapeutic targets in Cluster 3. CD4K inhibitors showed subtype-specific responses, suggesting tailored treatment strategies. Single-cell analysis highlighted unfavorable clinical features in Cluster 3, including high-risk classification and reduced cytotoxicity. Suppressed interactions between monocytes, macrophages, and regulatory T cells were observed, affecting immune regulation and patient prognosis. CONCLUSION: To summarize, we have identified a new independent prognostic factor in NB that underscores the significant correlation between tumor phenotype and immune contexture. These findings deepen our understanding of NB subtypes and immune cell interactions, paving the way for more effective treatment approaches.

Case Report: Intramural colonic signet ring cell carcinoma presenting as intestinal pseudo-obstruction: A case presentation and review of the literature.

Colorectal cancer (CRC) is the third most common cancer in the world. Other than adenocarcinomas, exceptional tumors of the colon and rectum represent a neglected clinical issue due to their rarity. Signet ring cell carcinoma (SRCC) is a rare subtype of CRC and has an extremely poor prognosis due to its advanced stage at diagnosis. Here we report a rare case of colorectal SRCC manifested as recurrent intestinal obstruction with a negative colonoscopy. Finally, he was diagnosed with signet ring cell carcinoma of the colon by postoperative pathology. It emphasized the special feature of intramural tumor growth without penetrating the mucosa in SRCC, which requires timely surgical intervention to avoid delay in diagnosis and treatment.

Physicochemical properties and micro-interaction between micro-nanoparticles and anterior corneal multilayer biological interface film for improving drug delivery efficacy: the transformation of tear film turnover mode.

Recently, various novel drug delivery systems have been developed to overcome ocular barriers in order to improve drug efficacy. We have previously reported that montmorillonite (MT) microspheres (MPs) and solid lipid nanoparticles (SLNs) loaded with the anti-glaucoma drug betaxolol hydrochloride (BHC) exhibited sustained drug release and thus intraocular pressure (IOP) lowering effects. Here, we investigated the effect of physicochemical particle parameters on the micro-interactions with tear film mucins and corneal epithelial cells. Results showed that the MT-BHC SLNs and MT-BHC MPs eye drops significantly prolonged the precorneal retention time due to their higher viscosity and lower surface tension and contact angle compared with the BHC solution, with MT-BHC MPs exhibiting the longest retention due to their stronger hydrophobic surface. The cumulative release of MT-BHC SLNs and MT-BHC MPs was up to 87.78% and 80.43% after 12 h, respectively. Tear elimination pharmacokinetics study further confirmed that the prolonged precorneal retention time of the formulations was due to the micro-interaction between the positively charged formulations and the negatively charged tear film mucins. Moreover, the area under the IOP reduction curve (AUC) of MT-BHC SLNs and MT-BHC MPs was 1.4 and 2.5 times that of the BHC solution. Accordingly, the MT-BHC MPs also exhibit the most consistent and long-lasting IOP-lowering effect. Ocular irritation experiments showed no significant toxicity of either. Taken together, MT MPs may have the potential for more effective glaucoma treatment.

Association of Serum Vitamin D with Active Human Cytomegalovirus Infections in Chinese Children with Systemic Lupus Erythematosus.

Vitamin D (VD) plays an important role in infectious and autoimmune diseases. We investigated the association between the serum VD levels and active human cytomegalovirus (HCMV) infections in pediatric systemic lupus erythematosus (SLE) patients. From January 2015 to June 2021, 120 children were diagnosed with SLE, and 100 healthy children were enrolled. The serum 25-hydroxyvitamin D [25(OH)D] levels were detected using ELISA. The serum anti-HCMV IgM antibodies were measured by a chemiluminescence immunoassay. Comparisons of the 25(OH)D levels between SLE patients and healthy children were performed, as well as subgroups of SLE patients with or without active HCMV infections. The serum 25(OH)D levels of SLE patients were significantly lower than those of healthy children (35.3 ± 12.9 vs. 49.3 ± 15.3, P < 0.001). The VD deficiency ratio was higher in SLE patients (89.2%) than that in healthy children (52.0%). The serum 25(OH)D levels in the positive anti-HCMV IgM group were significantly lower than those of the negative anti-HCMV IgM group (30.6 ± 12.3 vs. 38.2 ± 12.5, P < 0.001). A severe VD deficiency ratio was significantly higher in HCMV-IgM(+)-SLE patients (42.2%) than that in HCMV-IgM(-)-SLE patients (13.3%). This study suggested that the serum VD level is associated with active HCMV infections in pediatric SLE patients.

Strong Tribocatalytic Nitrogen Fixation of Graphite Carbon Nitride g-C3N4 through Harvesting Friction Energy.

Mechanical energy derived from friction is a kind of clean energy which is ubiquitous in nature. In this research, two-dimensional graphite carbon nitride (g-C3N4) is successfully applied to the conversion of nitrogen (N2) fixation through collecting the mechanical energy generated from the friction between a g-C3N4 catalyst and a stirring rod. At the stirring speed of 1000 r/min, the tribocatalytic ammonia radical (NH4+) generation rate of g-C3N4 can achieve 100.56 µmol·L-1·g-1·h-1 using methanol as a positive charge scavenger, which is 3.91 times higher than that without any scavengers. Meanwhile, ammonia is not generated without a catalyst or contact between the g-C3N4 catalyst and the stirring rod. The tribocatalytic effect originates from the friction between the g-C3N4 catalyst and the stirring rod which results in the charges transfer crossing the contact interface, then the positive and negative charges remain on the catalyst and the stirring rod respectively, which can further react with the substance dissolved in the reaction solution to achieve the conversion of N2 to ammonia. The effects of number and stirring speed of the rods on the performance of g-C3N4 tribocatalytic N2 fixation are further investigated. This excellent and efficient tribocatalysis can provide a potential avenue towards harvesting the mechanical energy in a natural environment.

Alarming antibiotics resistance of Helicobacter pylori from children in Southeast China over 6 years.

The increasing rates of antibiotic resistance in Helicobacter pylori (H. pylori) are a major concern of the decreasing eradication rate. Large-scale and long-period studies on antimicrobial susceptibility of H. pylori in children are limited. This study aimed to describe the temporal changes of antibiotic resistance among children in southeast China. Gastric biopsies obtained from children were cultured for H. pylori from 2015 to 2020. Susceptibility to clarithromycin (CLA), amoxicillin (AML), metronidazole (MTZ), furazolidone (FZD), tetracycline (TET) and levofloxacin (LEV) was tested. Data from 2012 to 2014 reported previously were obtained for comparing the change in temporal trends of antibiotic resistance. A total of 1638 (52.7%) H. pylori strains were isolated from 3111 children recruited. The resistance rates to CLA, MTZ and LEV were 32.8%, 81.7% and 22.8%, respectively. There were 52.9% strains resistant to single resistance, 28.7% to double resistance, and 9.0% to triple resistance. The total resistance rate and resistance rates to CLA, MTZ, LEV, CLA + LEV and CLA + MTZ + LEV increased annually in a linear manner. All resistant patterns except single resistance increased obviously from 2015 to 2017 and 2018 to 2020 compared to that from 2012 to 2014. Double resistance to CLA + MTZ increased significantly with age. The resistance rate to CLA and triple resistance to CLA, MTZ and LEV increased in children with prior H. pylori treatment than that from children without prior treatment. The antibiotic resistance rates of H. pylori were high in a large pediatric population in southeast China from 2015 to 2020. Individual treatment based on susceptibility test is imperative and optimal regimens should be chosen in H. pylori eradication therapy.

Oncogenic signaling pathway-related long non-coding RNAs for predicting prognosis and immunotherapy response in breast cancer.

Background: The clinical outcomes of breast cancer (BC) are unpredictable due to the high level of heterogeneity and complex immune status of the tumor microenvironment (TME). When set up, multiple long non-coding RNA (lncRNA) signatures tended to be employed to appraise the prognosis of BC. Nevertheless, predicting immunotherapy responses in BC is still essential. LncRNAs play pivotal roles in cancer development through diverse oncogenic signal pathways. Hence, we attempted to construct an oncogenic signal pathway-based lncRNA signature for forecasting prognosis and immunotherapy response by providing reliable signatures. Methods: We preliminarily retrieved RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database and extracted lncRNA profiles by matching them with GENCODE. Following this, Gene Set Variation Analysis (GSVA) was used to identify the lncRNAs closely associated with 10 oncogenic signaling pathways from the TCGA-BRCA (breast-invasive carcinoma) cohort and was further screened by the least absolute shrinkage and selection operator Cox regression model. Next, an lncRNA signature (OncoSig) was established through the expression level of the final 29 selected lncRNAs. To examine survival differences in the stratification described by the OncoSig, the Kaplan-Meier (KM) survival curve with the log-rank test was operated on four independent cohorts (n = 936). Subsequently, multiple Cox regression was used to investigate the independence of the OncoSig as a prognostic factor. With the concordance index (C-index), the time-dependent receiver operating characteristic was employed to assess the performance of the OncoSig compared to other publicly available lncRNA signatures for BC. In addition, biological differences between the high- and low-risk groups, as portrayed by the OncoSig, were analyzed on the basis of statistical tests. Immune cell infiltration was investigated using gene set enrichment analysis (GSEA) and deconvolution tools (including CIBERSORT and ESTIMATE). The combined effect of the Oncosig and immune checkpoint genes on prognosis and immunotherapy was elucidated through the KM survival curve. Ultimately, a pan-cancer analysis was conducted to attest to the prevalence of the OncoSig. Results: The OncoSig score stratified BC patients into high- and low-risk groups, where the latter manifested a significantly higher survival rate and immune cell infiltration when compared to the former. A multivariate analysis suggested that OncoSig is an independent prognosis predictor for BC patients. In addition, compared to the other four publicly available lncRNA signatures, OncoSig exhibited superior predictive performance (AUC = 0.787, mean C-index = 0.714). The analyses of the OncoSig and immune checkpoint genes clarified that a lower OncoSig score meant significantly longer survival and improved response to immunotherapy. In addition to BC, a high OncoSig score in several other cancers was negatively correlated with survival and immune cell infiltration. Conclusions: Our study established a trustworthy and discriminable prognostic signature for BC patients with similar clinical profiles, thus providing a new perspective in the evaluation of immunotherapy responses. More importantly, this finding can be generalized to be applicable to the vast majority of human cancers.