Novel insights on ecological responses of short- and long-chain perfluorocarboxylic acids in constructed wetlands coupled with modified basalt fiber bio-nest.

The first investigation based on constructed wetlands coupled with modified basalt fiber bio-nest (MBF-CWs) was performed under exposure of short- and long-chain perfluorocarboxylic acids (PFCAs). In general, both perfluorooctanoic acid (PFOA) and perfluorobutanoic acid (PFBA) caused significant decline of chemical oxygen demand removal by 10.83 % and 4.73 %. However, only PFOA led to marked inhibition on total phosphorus removal by 12.51 % in whole duration. Suppression of removal performance resulted from side impacts on microbes by PFOA. For instance, activities of key enzymes like dehydrogenase (DHA), urease (URE), and phosphatase (PST) decreased by 52.77 %, 40.70 %, and 56.94 % in maximum under PFOA stress, while URE could alleviate over time. By contrast, distinct inhibition was only found on PST in later phases with PFBA exposure. PFCAs had adverse influence on alpha diversity of MBF-CWs, particularly long-chain PFOA. Both PFCAs caused enrichment of Proteobacteria, owing to increase of Gammaproteobacteria and Plasticicumulans by 22.04-35.79 % and 22.91-219.77 %. Nevertheless, some dominant phyla (like Bacteroidota and Acidobacteriota) and genera (like SC-I-84, Thauera, Subgroup_10, and Ellin6067) were only suppressed by PFOA, causing more hazards to microbial decontamination than PFBA did. As for plants, chlorophyll contents tend to decrease with PFOA treatment. Whereas, higher antioxidase activities and more lipid peroxidation products were uncovered in PFOA group, demonstrating more reactive oxygen species brought by long-chain PFCAs. This work offered new findings about ecological effects of MBF-CWs under PFCAs exposure, evaluating stability and sustainability of MBF-CW systems to treat sewage containing complex PFCAs.

Bioelectricity drives transformation of nitrogen and perfluorooctanoic acid in constructed wetlands: Performances and mechanisms.

In this study, constructed wetland-microbial fuel cell (CW-MFC) filled with modified basalt fiber (MBF) via iron modification was utilized for treating perfluorooctanoic acid (PFOA) containing sewage. Results showed the significant promotion by bioelectricity on ammonium and total nitrogen by 7.80-8.14 %. Although such enhancement was suppressed by PFOA, higher removal was still observed with closed circuit, and PFOA removal also increased by 9.05 %. Bioelectricity contributed to enrichment of bacteria involved in nitrifying (Nitrospira and Ellin6067), denitrifying (like Thauera and Dechloromonas), iron redox (Geobacter), and sulfate-reducing (Desulfobacter), aligned with up-regulated of functional genes, including amoA, narG , napA, narK, narS, nrfA, sulp and sqr. Enrichment of autohydrogenotrophic and sulfide-oxidizing autotrophic denitrifiers, and nitrate dependent iron oxidation bacteria by bioelectricity all promoted denitrification. Moreover, bioelectricity boosted relative abundance of organic compounds degradation enzymes, such as dehydrogenase, decarboxylase, and dehalogenase, supporting the enhancement on PFOA removal. Generally, PFOA was converted to short-chain perfluorocarboxylic acids (PFCAs) via decarboxylation, hydroxylation, HF elimination, hydrolysis, F- elimination, C-C bond scission, and dehydration in CW-MFC. The final PFCAs-products determined was perfluorobutyric acid. This work estimated feasibility of treating PFOA containing sewage by CM-MFC, and offered new insights on enhancing mechanisms of nitrogen and PFOA conversion.

The relationship between accelerometer-based physical activity, sedentary behavior, and seven common geriatric syndromes: a two-sample Mendelian randomization study.

Introduction: To investigate the causal associations between accelerometer-based physical activity (PA), sedentary behavior (SB), and seven common geriatric syndromes (GSs) (frailty, falls, delirium, urinary incontinence, dysphagia, hearing loss, and visual impairment) by Mendelian randomization (MR) analysis. Methods: Instrumental variables from a genome-wide association study were used for MR analysis. The exposure factors were three PA phenotypes (average acceleration, overall activity, and moderate-intensity activity) and one SB phenotype (SB). The outcome variables were seven common GSs. The inverse variance weighted (IVW) method was utilized for the primary MR analysis. Additionally, sensitivity, pleiotropy, and heterogeneity analyses were subsequently conducted to assess the robustness of the present study's findings. Results: According to the primary MR results obtained using the IVW method, genetically predicted PA (average acceleration) decreased the risk of two GSs (frailty, p = 0.01; dysphagia, p = 0.03). Similarly, overall activity decreased the risk of two GSs (frailty, p = 0.01; delirium, p = 0.03), and moderate-intensity activity reduced the risk of three GSs (urinary incontinence, p = 0.04; hearing loss, p = 0.02; visual impairment, p = 0.01). Furthermore, SB was causally correlated with a greater risk for three GSs (frailty, p = 0.03; fall, p = 0.01; dysphagia, p = 0.04). Conclusion: This study provided evidence that accelerometer-based PA may be causally associated with a lower risk of GSs, while SB may increase the risk of GSs.

Modified basalt fiber filled in constructed wetland-microbial fuel cell: Comparison of performance and microbial impacts under PFASs exposure.

Basalt fiber (BF) with modification of iron (Fe-MBF) and calcium (Ca-MBF) were filled into constructed wetland-microbial fuel cell (CW-MFC) for innovative comparison of improved performance under perfluorooctanoic acid (PFOA) exposure. More enhancement on nitrogen and phosphorus removal was observed by Fe-MBF than Ca-MBF, with significant increase of ammonium (NH4+-N) removal by 3.36-5.66 % (p < 0.05) compared to control, even under PFOA stress. Markedly higher removal efficiency of PFOA by 4.76-8.75 % (p < 0.05) resulted from Fe-MBF, compared to Ca-MBF and control BF groups. Besides, superior electrochemical performance was found in Fe-MBF group, with maximum power density 28.65 % higher than control. Fe-MBF caused higher abundance of dominant microbes on electrodes ranged from phylum to family. Meanwhile, ammonia oxidizing bacteria like Nitrosomonas was more abundant in Fe-MBF group, which was positively correlated to NH4+-N and total nitrogen removal. Some other functional genera involved in denitrification and phosphorus-accumulation were enriched by Fe-MBF on electrodes and MBF carrier, including Dechloromonas, Candidatus_Competibacter, and Pseudomonas. Additionally, there were more biomarkers in Fe-MBF group, like Pseudarcobacter and Acidovorax, conducive to nitrogen and iron cycling. Most functional genes of nitrogen, carbon, and sulfur metabolisms were up-regulated with Fe-MBF filling, causing improvement on nitrogen removal.

Natural ventilation cooling effectiveness classification for building design addressing climate characteristics.

The evaluation of natural ventilation potential for effective sustainable options and innovative green building design strategies is of great interest to architects, researchers and governments. From a retrospective review, we found that the potential evaluation of natural ventilation (NV) cooling effectiveness in the same category based on similar meteorological uncertainty, research objectives and objects showed significant differences. Uncertainties added and uncertainty propagation (both model form uncertainties and parameter uncertainties) could result in large discrepancies between simulation outcomes and real scenarios, especially in the design performance modeling (DPM) phase. In this conceptual design stage, a few parameters are available and therefore decisive. It is necessary to review and identify the key performance indicators and explore the extent to which deviations are caused by inconsistencies or biases in model information. As a basis for more concrete research, we propose statistical tests based on quantitative evaluations to explore the rule of natural ventilation potential volatility and identify whether there is a significant potential improvement resulting from the critical parameter enhancement with the optimal relationship. The showcase is applied in China, where there has been a significant amount of criticism regarding the current building climate zoning due to the perceived coarseness of the system and where there has been an active exploration into the possibility of redefining building climate zoning with a view toward improving its accuracy and effectiveness.

Innovative application of basalt fibers as biological carrier in constructed wetland-microbial fuel cell for improvement of performance under perfluorooctanoic acid exposure.

Basalt fiber (BF) was filled in constructed wetland-microbial fuel cell (CW-MFC) as bio-carrier for enhancement of operation performance under perfluorooctanoic acid (PFOA) exposure. In this study, although PFOA caused significant decline of ammonium removal by 7.5-7.7 %, slight promotion on nitrogen and phosphorus removal was observed with BF filling, compared to control. PFOA removal also increased by 1.7-3.4 % in BF filling group. Besides, improved electrochemical performance was discovered with BF filling, in which the highest power density increased by 86.6 % than control, even under PFOA stress. Enhanced stability and performance of CW-MFC resulted from stimulation of functional bacteria on electrodes like Dechloromonas, Thauera, Zoogloea, Gemmobacter, and Pseudomonas, which were further enriched on BF carrier. Higher abundance of nitrogen metabolism and related genes on electrodes and BF carrier was also discovered with BF filling. This study offered new findings on application of BF in CW-MFC systems with PFOA exposure.

Evaluation of CYP2C19 Genetic Variant and Its Lack of Association with Valproic Acid Plasma Concentrations Among Zhuang and Han Schizophrenia Patients in Guangxi.

Purpose: To investigate the CYP2C19 genotype distribution and allelic frequency among the Zhuang and Han schizophrenic populations in Guangxi, examine the correlation between CYP2C19 genetic variants and standardized blood levels of Valproic Acid (VPA) in schizophrenic patients, and evaluate the effects of age, gender, and Body Mass Index (BMI) on standardized VPA blood concentrations. Patients and Methods: Between February and December 2022, 192 Zhuang and Han schizophrenia patients treated with VPA were studied. Steady-state VPA concentrations were determined using homogeneous enzyme immunoassays, and CYP2C19 *1, *2, and *3 loci via q-PCR. CYP2C19 genotype distributions between Zhuang and Han groups in Nanning were compared using chi-square tests and contrasted with other ethnicities. Non-parametric tests analyzed VPA variations, identifying critical factors through multivariate stepwise regression. Results: The study identified five CYP2C19 genotypes at the *2 and *3 loci, with the *3/*3 genotype absent in both cohorts. The CYP2C19 distribution in Guangxi Zhuang and Han mirrors, yet diverges significantly from Hui and Kazakh groups. Among 192 subjects, VPA blood levels remained consistent across metabolic types and ages 18-60 but varied significantly by gender. Multivariate analysis revealed gender and BMI as significant factors, overshadowing CYP2C19 genotype and age. Conclusion: In Guangxi, CYP2C19 genetic variants in Zhuang and Han schizophrenia patients demonstrate statistically indistinguishable allelic and metabolic distributions. Gender and BMI can influence standardized VPA blood concentrations in schizophrenia patients. However, in our study cohort, the CYP2C19 genotype and age are not the primary determinants of standardized VPA blood levels.

Near telomere-to-telomere genome of the model plant Physcomitrium patens.

The model plant Physcomitrium patens has played a pivotal role in enhancing our comprehension of plant evolution and development. However, the current genome harbours numerous regions that remain unfinished and erroneous. To address these issues, we generated an assembly using Oxford Nanopore reads and Hi-C mapping. The assembly incorporates telomeric and centromeric regions, thereby establishing it as a near telomere-to-telomere genome except a region in chromosome 1 that is not fully assembled due to its highly repetitive nature. This near telomere-to-telomere genome resolves the chromosome number at 26 and provides a gap-free genome assembly as well as updated gene models to aid future studies using this model organism.

Bacterial Colonization in the Airways and Intestines of Twin and Singleton Preterm Neonates: A Single-Center Study.

Limited studies have investigated the microbial colonization of the airways and intestines in preterm neonates. We studied the composition of intestinal and airway bacterial colonies in several preterm twin pairs and singletons to explore the dominant bacteria, assess their variability, and predict their phenotypic and metabolic functions. In this descriptive study, we collected sputum and fetal stool specimens from 10 twin pairs (20 cases) and 20 singleton preterm neonates. These specimens were analyzed using 16S rRNA deep sequencing to study the alpha and beta diversities and community structures of airway and intestinal bacteria and predict their metabolic functions. Specimens from twins and singleton neonates had distinct aggregations of intestinal and airway bacteria but showed similarities and high microbial diversities during initial colonization. The top five phyla were Proteobacteria, Firmicutes, Actinobacteriota, Bacteroidota, and Cyanobacteria. The top ten genera were Streptococcus, Acinetobacter, Ralstonia, Staphylococcus, Comamonas, Enterococcus, Stenotrophomonas, Dechlorosoma, Sphingopyxis, and Rothia. Potentially pathogenic and highly stress-tolerant Gram-negative bacteria were predominant in the intestinal flora. A considerable proportion of colonies recovered from the airway and intestines of preterm neonates were functional bacteria. The richness of the intestinal and airway flora was not significantly different between twins and singletons, and the flora clustered together. Both intestinal and airway bacteria of twins and singletons were similar. The species involved in initial colonization were similar but different in proportions; therefore, changes in microbial structure and richness may not be attributed to these species.

The heterogeneous driving forces behind carbon emissions change in 30 selective emerging economies.

Emerging economies are predicted to be future emission hotspots due to expected levels of urbanization and industrialization, and their CO2 emissions are receiving more scrutiny. However, the driving forces underlying dynamic change in emissions are poorly understood, despite their crucial role in developing targeted mitigating pathways. We firstly compile energy-related emissions of 30 selective emerging economies from 2010 to 2018. Then, three growth patterns of emissions in these economies have been identified through emission data, which imply different low-carbon pathways. Most emerging economies saw an increase of varying degrees in emissions, driven by economic growth and partly offset by better energy efficiency and improvements in energy mixes. Furthermore, the industrial structure was another factor that slowed emissions, especially in Latin America and the Caribbean. Our research contributes to the heterogeneous exploration of CO2 emissions produced by energy among sectors and the creation of low-carbon development pathways in emerging economies.

A pilot study exploring the association of bronchial bacterial microbiota and recurrent wheezing in infants with atopy.

Background: Differences in bronchial microbiota composition have been found to be associated with asthma; however, it is still unclear whether these findings can be applied to recurrent wheezing in infants especially with aeroallergen sensitization. Objectives: To determine the pathogenesis of atopic wheezing in infants and to identify diagnostic biomarkers, we analyzed the bronchial bacterial microbiota of infants with recurrent wheezing and with or without atopic diseases using a systems biology approach. Methods: Bacterial communities in bronchoalveolar lavage samples from 15 atopic wheezing infants, 15 non-atopic wheezing infants, and 18 foreign body aspiration control infants were characterized using 16S rRNA gene sequencing. The bacterial composition and community-level functions inferred from between-group differences from sequence profiles were analyzed. Results: Both α- and ß-diversity differed significantly between the groups. Compared to non-atopic wheezing infants, atopic wheezing infants showed a significantly higher abundance in two phyla (Deinococcota and unidentified bacteria) and one genus (Haemophilus) and a significantly lower abundance in one phylum (Actinobacteria). The random forest predictive model of 10 genera based on OTU-based features suggested that airway microbiota has diagnostic value for distinguishing atopic wheezing infants from non-atopic wheezing infants. PICRUSt2 based on KEGG hierarchy (level 3) revealed that atopic wheezing-associated differences in predicted bacterial functions included cytoskeleton proteins, glutamatergic synapses, and porphyrin and chlorophyll metabolism pathways. Conclusion: The differential candidate biomarkers identified by microbiome analysis in our work may have reference value for the diagnosis of wheezing in infants with atopy. To confirm that, airway microbiome combined with metabolomics analysis should be further investigated in the future.

Challenges of carbon emission reduction by the workshop education pattern.

The COVID-19 pandemic has forced many conferences and educational events to shift from in-person to online, significantly reducing the carbon footprint associated with these activities. Workshops are a common pattern of thematic learning at the university level, usually involving a series of activities, such as gathering, learning, and dining, for participants from different regions. However, unlike a three-day conference, workshops usually last for seven days or more, resulting in a non-negligible carbon footprint. To resolve this challenge, we have developed a model that provides recommendations for minimizing the carbon footprint of workshops. Using data from the DigitalFUTURES International Workshop on architecture education at Tongji University in China, we calculated the carbon footprint of scenarios with varying workshop durations, participation modes, and transportation methods. Our results show that online workshops can reduce the carbon footprint by up to 88% compared to in-person workshops. Hybrid workshops, which combine online and in-person participation, can also lead to significant carbon reductions, with a 46% online participation rate resulting in an 82% reduction in carbon footprint. However, we recommend that in-person participation be maintained to ensure efficient learning and effective communication. Our work provides a sustainable solution for organizing future workshops with a reduced carbon footprint.

Identification of potential biomarkers for papillary thyroid carcinoma by comprehensive bioinformatics analysis.

To perform bioinformatics analysis on the papillary thyroid carcinoma (PTC) gene chip dataset to explore new biological markers for PTC. The gene expression profiles of GSE3467 and GSE6004 chip data were collected by GEO2R, and the differentially expressed genes (DEGs) were selected for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Protein-protein interaction (PPI) relationship analysis was achieved using STRING, and the hub genes were obtained using the Cytoscape software. GEPIA was used to validate the expressions of the hub genes in the normal and tumor tissues and to conduct survival analyses. Pertinent genetic pathology results were fetched using the HPA database. Finally, the key genes were clinically verified by reverse transcription-polymerase chain reaction. 97 genes were jointly up-regulated and 107 genes were jointly down-regulated in GSE3467 and GSE6004. GO function enrichment analysis revealed that the DEGs were involved in the regulation of calcium ion transport into cytosol, integrin binding, and cell adhesion molecule binding. KEGG pathway enrichment analysis indicated that the DEGs were chiefly associated with thyroid cancer and non-small cell lung cancer. According to the PPI network, 30 key target genes were identified. Only the expressions of ANK2, TLE1, and TCF4 matched between the normal and tumor tissues, and were associated with disease prognosis. When compared with the normal thyroid tissues, the protein and mRNA expressions of ANK2, TLE1, and TCF4 were down-regulated in PTC. Significant differences exist in overall gene expression between the thyroid tissues of patients with PTC and those of healthy people. Furthermore, the differential genes ANK2, TLE1, and TCF4 are expected to be reliable molecular markers for the mechanism study and diagnosis of PTC.

Vision transformer-based weakly supervised histopathological image analysis of primary brain tumors.

Diagnosis of primary brain tumors relies heavily on histopathology. Although various computational pathology methods have been developed for automated diagnosis of primary brain tumors, they usually require neuropathologists' annotation of region of interests or selection of image patches on whole-slide images (WSI). We developed an end-to-end Vision Transformer (ViT) - based deep learning architecture for brain tumor WSI analysis, yielding a highly interpretable deep-learning model, ViT-WSI. Based on the principle of weakly supervised machine learning, ViT-WSI accomplishes the task of major primary brain tumor type and subtype classification. Using a systematic gradient-based attribution analysis procedure, ViT-WSI can discover diagnostic histopathological features for primary brain tumors. Furthermore, we demonstrated that ViT-WSI has high predictive power of inferring the status of three diagnostic glioma molecular markers, IDH1 mutation, p53 mutation, and MGMT methylation, directly from H&E-stained histopathological images, with patient level AUC scores of 0.960, 0.874, and 0.845, respectively.

Sensitivity enhancement of far-detuned RF field sensing based on Rydberg atoms dressed by a near-resonant RF field.

Rydberg-atom electrometers promise traceable standards for RF electrometry by enabling stable and uniform measurement. In this Letter, we propose an approach to increase the sensitivity of the Rydberg-atom electrometer for far-detuned RF field sensing. The key physical mechanism is the addition of a new ingredient-a local RF field near-resonant with a Rydberg transition-so that the far-detuned field can be detected by the shift of an Autler-Townes (AT) splitting peak, which can be dozens of times larger than the AC Stark shift of the electromagnetic induced transparency (EIT) signal without the near-resonant field. The method enables us to measure far-detuned fields with higher sensitivities, including sub-GHz RF fields (even DC electric fields) which are rarely involved in the existing sensitivity enhancement methods.

Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients.

Glioma is the most common and fatal primary brain tumor in humans. A significant role for long non-coding RNA (lncRNA) in glioma is the regulation of gene expression and chromatin recombination, and immunotherapy is a promising cancer treatment. Therefore, it is necessary to identify necroptosis-related lncRNAs in glioma. In this study, we collected and evaluated the RNA-sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA, https://www.ncbi.nlm.nih.gov/, Data Release 32.0, March 29, 2022) glioma patients, and necroptosis-related lncRNAs were screened. Cox regression and least absolute shrinkage and selection operator (LASSO) analysis were performed to construct a risk score formula to explore the different overall survival between high- and low-risk groups in TCGA. Gene Ontology (GO) and pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes (KEGG)) were performed to identify the function of screened genes. The immune correlation analysis showed that various immune cells and pathways positively associated with a patient's risk score. Furthermore, the analysis of the tumor microenvironment indicated many immune cells and stromal cells in the tumor microenvironment of glioma patients. Six necroptosis-related lncRNAs were concerned to be involved in survival and adopted to construct the risk score formula. The results showed that patients with high-risk scores held poor survival in TCGA. Compared with current clinical data, the area under the curve (AUC) of different years suggested that the formula had better predictive power. We verified that necroptosis-related lncRNAs play a significant role in the occurrence and development of glioma, and the constructed risk model can reasonably predict the prognosis of glioma. The results of these studies added some valuable guidance to understanding glioma pathogenesis and treatment, and these necroptosis-related lncRNAs may be used as biomarkers and therapeutic targets for glioma prevention.

Bacterial composition and colony structure of the lower respiratory tract in infants and children with recurrent wheezing: a case-control study.

BACKGROUND: The bacterial load of the human lower respiratory tract is at least several times lower than that of the other parts of the body. This study aimed to identify the bacterial composition and colony structure of the lower respiratory tract in infants and children with recurrent wheezing compared with those of children with a bronchial foreign body and clarify whether the length of wheezing in infants can contribute to differences in the lower respiratory tract's bacterial colony structure. METHODS: We collected specimens of alveolar lavage fluid from 48 infants and children who underwent fiberoptic bronchoscopy and were divided into groups: A1 (multiple wheezing: wheezing more than three times in < 1 month), A2 (persistent wheezing: > 1 month), and B (bronchial foreign body; control group). We analyzed the bacterial community structure of alveolar lavage fluid using high-throughput sequencing. The richness and diversity of the microbial communities were assessed by α and ß diversity analyses. RESULTS: A total of 6,644 operational taxonomic units (OTUs) were obtained based on the Illumina Nova sequencing platform and clustered according to those that met the 97% identity threshold, followed by species annotation of the OTU sequences. In the annotation results, 2,608 (39.25%) OTUs were annotated at the genus level. At the genus level, Sphingomonas and Phyllobacterium were significantly higher in group A1 than in group B. There were significantly more Phyllobacterium in group A2 than in group B. Prevotella, Neisseria, and Haemophilus were higher in group B than in groups A1 and A2. The differences in the between-group α and ß diversity analyses were statistically significant. The microbial diversity in groups A1 and A2 was significantly less than that in group B, but there was no statistical difference in bacterial community diversity between groups A1 and A2. CONCLUSION: Recurrent wheezing in infants and children is more likely due to alterations in the overall bacterial microecology and disruption of host respiration and immune homeostasis than the effects of a single bacterium.

Pulmonary lymphomatoid granulomatosis in a 4-year-old girl: A case report.

BACKGROUND: Pulmonary lymphomatoid granulomatosis (PLG) is a lymphoproliferative disease associated with Epstein-Barr viral infection occurring mainly in adults and rarely in children. It is characterized by multiple pulmonary nodules. Its diagnosis depends on lung biopsy findings. Most patients are immunodeficient, and it commonly presents in children undergoing chemotherapy for leukemia. We report the case of a child with PLG caused by a mutation in the macrophage-expressed gene 1 (MPEG1), suggesting possible PLG occurrence in children undergoing treatment for pulmonary nodular lesions. CASE SUMMARY: This study reports a case of PLG without apparent immunodeficiency, suggesting the possibility of this disease occurrence during the treatment of pulmonary nodular lesions in children. Initially, the cause was assumed to be an atypical pathogen. Following conventional anti-infective treatment, chest computed tomography findings revealed that there were still multiple nodules in the lungs. Additionally, the patient was found to be infected with the Epstein-Barr virus. Histopathological examination of the resected lung revealed lymphoproliferative lesions with necrosis. Small lymphocytes, plasma cells, and histiocytes were observed in the background, although Reed-Sternberg cells were absent. Immunohistochemical staining [CD20(+), CD30(+), and CD3(+)] and EBV-encoded small RNA1/2 in situ hybridization of small lymphocytes revealed approximately 200 cells/high-power field. Whole exon sequencing of the patient revealed a mutation in the MPEG1. The patient was eventually diagnosed with PLG and transferred to the Department of Pediatric Oncology for bone marrow transplantation. CONCLUSION: As PLG is rare and fatal, it should be suspected in clinical settings when treatment of initial diagnosis is ineffective.

New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis.

BACKGROUND: Low-grade gliomas (LGG) are WHO grade II tumors presenting as the most common primary malignant brain tumors in adults. Currently, LGG treatment involves either or a combination of surgery, radiation therapy, and chemotherapy. Despite the knowledge of constitutive genetic risk factors contributing to gliomas, the role of single genes as diagnostic and prognostic biomarkers is limited. The aim of the current study is to discover the predictive and prognostic genetic markers for LGG. METHODS: Transcriptome data and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. We first performed the tumor microenvironment (TME) survival analysis using the Kaplan-Meier method. An analysis was undertaken to screen for differentially expressed genes. The function of these genes was studied by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Following which a protein-protein interaction network (PPI) was constructed and visualized. Univariate and multivariate COX analyses were performed to obtain the probable prognostic genes. The key genes were selected by an intersection of core and prognostic genes. A clinical correlation analysis of single-gene expression was undertaken. GSEA enrichment analysis was performed to identify the function of key genes. Finally, a single gene-related correlation analysis was performed to identify the core immune cells involved in the development of LGG. RESULTS: A total of 529 transcriptome data and 515 clinical samples were obtained from the TCGA. Immune cells and stromal cells were found to be significantly increased in the LGG microenvironment. The top five core genes intersected with the top 38 prognostically relevant genes and two key genes were identified. Our analysis revealed that a high expression of HLA-DRA was associated with a poor prognosis of LGG. Correlation analysis of immune cells showed that HLA-DRA expression level was related to immune infiltration, positively related to macrophage M1 phenotype, and negatively related to activation of NK cells. CONCLUSIONS: HLA-DRA may be an independent prognostic indicator and an important biomarker for diagnosing and predicting survival in LGG patients. It may also be associated with the immune infiltration phenotype in LGG.