Osteosarcoma is the most common primary malignant bone tumor in adolescents and children and prone to develop lung metastasis. Its prognosis has been virtually unimproved over the last few decades, especially in patients with metastases, who suffer from a dismal survival. Recently, increasing attention has been devoted to monocarboxylate transporters-related (MCTs) metabolic reprogramming. However, the role of MCT1 and MCT4 in osteosarcoma progression and the underlying mechanisms remain to be further elucidated.

As the main bioactive substance of Ganoderma lucidum, Ganoderma lucidum polysaccharide (GLP) has anti-inflammatory, antibacterial, and other biological activities. Studies have shown that GLP can regulate the expression of multiple inflammatory cytokines in different inflammatory models and diseases as part of the anti-infection immune response. We extracted crude Changbai Mountain Ganoderma lucidum polysaccharides (CGLPs), analyzed their physical and chemical properties, and then applied them to the periodontitis model to verify whether they have an inhibitory effect on mouse periodontitis. CGLP was determined to be a heteropolysaccharide with dextran as the main component. Its molecular weight was 17.40 kDa. In vivo experiments in mice showed that CGLP can inhibit the alveolar bone loss and reduced inflammation caused of periodontitis by regulating the expression of the inflammatory factors IL-1β, TNF-α, and IL-10 in a concentration-dependent manner.

The outcomes of patients with diffuse large B-cell lymphoma (DLBCL) vary widely, and about 40% of them could not be cured by the standard first-line treatment, R-CHOP, which could be due to the high heterogeneity of DLBCL. Here, we aim to construct a prognostic model based on the genetic signature of metabolic heterogeneity of DLBCL to explore therapeutic strategies for DLBCL patients. Clinical and transcriptomic data of one training and four validation cohorts of DLBCL were obtained from the GEO database. Metabolic subtypes were identified by PAM clustering of 1,916 metabolic genes in the 7 major metabolic pathways in the training cohort. DEGs among the metabolic clusters were then analyzed. In total, 108 prognosis-related DEGs were identified. Through univariable Cox and LASSO regression analyses, 15 DEGs were used to construct a risk score model. The overall survival (OS) and progression-free survival (PFS) of patients with high risk were significantly worse than those with low risk (OS: HR 2.86, 95%CI 2.04-4.01, p < 0.001; PFS: HR 2.42, 95% CI 1.77-3.31, p < 0.001). This model was also associated with OS in the four independent validation datasets (GSE10846: HR 1.65, p = 0.002; GSE53786: HR 2.05, p = 0.02; GSE87371: HR 1.85, p = 0.027; GSE23051: HR 6.16, p = 0.007) and PFS in the two validation datasets (GSE87371: HR 1.67, p = 0.033; GSE23051: HR 2.74, p = 0.049). Multivariable Cox analysis showed that in all datasets, the risk model could predict OS independent of clinical prognosis factors (p < 0.05). Compared with the high-risk group, patients in the low-risk group predictively respond to R-CHOP (p = 0.0042), PI3K inhibitor (p < 0.05), and proteasome inhibitor (p < 0.05). Therefore, in this study, we developed a signature model of 15 DEGs among 3 metabolic subtypes, which could predict survival and drug sensitivity in DLBCL patients.

The rise of global temperature causes the degradation of the substantial reserves of carbon (C) stored in tundra soils, in which microbial processes play critical roles. Viruses are known to influence the soil C cycle by encoding auxiliary metabolic genes and infecting key microorganisms, but their regulation of microbial communities under climate warming remains unexplored. In this study, we evaluated the responses of viral communities for about 5 years of experimental warming at two depths (15 to 25 cm and 45 to 55 cm) in the Alaskan permafrost region. Our results showed that the viral community and functional gene composition and abundances (including viral functional genes related to replication, structure, infection, and lysis) were significantly influenced by environmental conditions such as total nitrogen (N), total C, and soil thawing duration. Although long-term warming did not impact the viral community composition at the two depths, some glycoside hydrolases encoded by viruses were more abundant at both depths of the warmed plots. With the continuous reduction of total C, viruses may alleviate methane release by altering infection strategies on methanogens. Importantly, viruses can adopt lysogenic and lytic lifestyles to manipulate microbial communities at different soil depths, respectively, which could be one of the major factors causing the differences in microbial responses to warming. This study provides a new ecological perspective on how viruses regulate the responses of microbes to warming at community and functional scales. IMPORTANCE Permafrost thawing causes microbial release of greenhouse gases, exacerbating climate warming. Some previous studies examined the responses of the microbial communities and functions to warming in permafrost region, but the roles of viruses in mediating the responses of microbial communities to warming are poorly understood. This study revealed that warming induced changes in some viral functional classes and in the virus/microbe ratios for specific lineages, which might influence the entire microbial community. Furthermore, differences in viral communities and functions, along with soil depths, are important factors influencing microbial responses to warming. Collectively, our study revealed the regulation of microbial communities by viruses and demonstrated the importance of viruses in the microbial ecology research.

Sugarcane is the major sugar-producing crop worldwide, and hybrid F1 populations are the primary populations used in breeding. Challenged by the sugarcane genome's complexity and the sucrose yield's quantitative nature, phenotypic selection is still the most commonly used approach for high-sucrose yield sugarcane breeding. In this study, a hybrid F1 population containing 135 hybrids was constructed and evaluated for 11 traits (sucrose yield (SY) and its related traits) in a randomized complete-block design during two consecutive growing seasons. The results revealed that all the traits exhibited distinct variation, with the coefficient of variation (CV) ranging from 0.09 to 0.35, the Shannon-Wiener diversity index (H') ranging between 2.64 and 2.98, and the broad-sense heritability ranging from 0.75 to 0.84. Correlation analysis revealed complex correlations between the traits, with 30 trait pairs being significantly correlated. Eight traits, including stalk number (SN), stalk diameter (SD), internode length (IL), stalk height (SH), stalk weight (SW), Brix (B), sucrose content (SC), and yield (Y), were significantly positively correlated with sucrose yield (SY). Cluster analysis based on the 11 traits divided the 135 F1 hybrids into three groups, with 55 hybrids in Group I, 69 hybrids in Group II, and 11 hybrids in Group III. The principal component analysis indicated that the values of the first four major components' vectors were greater than 1 and the cumulative contribution rate reached 80.93%. Based on the main component values of all samples, 24 F1 genotypes had greater values than the high-yielding parent 'ROC22' and were selected for the next breeding stage. A rapid sucrose yield estimation equation was established using four easily measured sucrose yield-related traits through multivariable linear stepwise regression. The model was subsequently confirmed using 26 sugarcane cultivars and 24 F1 hybrids. This study concludes that the sugarcane F1 population holds great genetic diversity in sucrose yield-related traits. The sucrose yield estimation model, ySY=2.01xSN+8.32xSD+0.79xB+3.44xSH-47.64, can aid to breed sugarcane varieties with high sucrose yield.

Natural gas has become a global energy consumption hotspot because of its large reserves and clean combustion. Due to soil corrosion, construction damage, and natural disasters, leakage accidents of buried natural gas pipelines often occur. In this paper, the steady simulation method was used to study the methane invasion limit state (MILS) and the methane invasion limit distance (MILD) under the conditions of hardened surface ground (HSG), unhardened surface ground (UHSG), and semihardened surface ground (SHSG), and the transient simulation of methane invasion distance (MID) under the condition of HSG with the largest MILD was carried out. The results showed that regardless of ground conditions, with the increase of leakage time, the diffusion range of methane in soil will not increase all the time, and there was a limit state (MILS). The distribution range and concentration of methane in the soil under HSG condition were the largest, followed by the SHSG condition, and the UHSG condition was the smallest. When the ground condition changed from UHSG to HSG, the MILD increased from 3.41 to 9.32 m. The HSG condition will increase the MILD and the range of dangerous areas. The buried depth of the pipeline had a serious impact on the MILD. When the buried depth of the pipeline increased from 0.3 to 1.5 m, the MILD increased from 1.75 to 3.49 m under the condition of UHSG and exceeded 10 m under the condition of HSG. The average error of the MID prediction model was 2.37% under the condition of HSG, which can accurately predict the leakage of buried pipeline. The MID provides a reference for the layout of urban underground gas leakage monitoring points. The MILD can provide guidance for the safe distance between natural gas pipeline and structures in the design code of natural gas pipeline.

The ability to deactivate CRISPR-Cas systems on demand would improve the safety and applicability of genome editing. Here, we detail a protocol using photocleavable guide RNAs (pcRNAs) to deactivate CRISPR-Cas9 inside cells. We verify that deactivation is both rapid and complete by checking for insertion-deletion (indel) mutations using Sanger sequencing. This protocol will be useful for researchers interested in using pcRNAs to improve genome editing specificity, characterize the timescales of genome editing, and study cellular DNA damage responses. For complete details on the use and execution of this protocol, please refer to Zou et al. (2021).

Governments around the world have implemented non-pharmaceutical interventions to limit the transmission of COVID-19. While lockdowns and physical distancing have proven effective for reducing COVID-19 transmission, there is still limited understanding of how NPI measures are reflected in indicators of human mobility. Further, there is a lack of understanding about how findings from high-income settings correspond to low and middle-income contexts.

The genus Paris is an excellent source of steroidal saponins that exhibit various bioactivities. Paris mairei is a unique species and has been widely used as folk medicine in Southwest China for a long time. With the help of chemical methods and modern spectra analysis, five new steroidal saponins, pamaiosides A-E (1-5), along with five known steroidal saponins 6-10, were isolated from the rhizomes of Paris mairei. The cytotoxicity of all the new saponins was evaluated against human pancreatic adenocarcinoma PANC-1 and BxPC3 cell lines.

Epithelial-mesenchymal transition (EMT) confers migratory and invasiveness abilities on cancer cells, as well as leading to changes in biomechanical properties and cytoskeletal structure. Cell mechanical properties are considered to be promising label-free markers for diagnosis of cancer metastasis. In this work, cell compressibility, a novel and important parameter of cell mechanical properties, was measured directly and quickly using a specially designed acoustofluidic microdevice. The compressibilities of cells with different metastatic potentials were investigated. Based on a comparison of the measurement results, non-metastatic cells exhibited lower compressibility than metastatic cells. The correlation between cell compressibility and EMT status was further studied; the results showed that the acquisition of mesenchymal status was accompanied by an increase in cell compressibility. These findings imply strong correlations among cell compressibility, EMT status, and invasiveness. Therefore, cell compressibility represents a novel biomechanical marker for evaluating malignant transformation and metastasis of cancer.

The relationship between prenatal exposure to sulfur dioxide (SO2) and childhood wheezing and asthma is unclear.

The median survival time of patients with advanced gastric cancer (GC) who received radiotherapy and chemotherapy was <1 year. Epithelial-mesenchymal transformation (EMT) gives GC cells the ability to invade, which is an essential biological mechanism in the progression of GC. The long non-coding RNA (lncRNA)-based competitive endogenous RNA (ceRNA) system has been shown to play a key role in the GC-related EMT process. Although the AKT pathway is essential for EMT in GC, the relationship between AKT3 subtypes and EMT in GC is unclear. Here, we evaluated the underlying mechanism of ceRNA involving NR2F1-AS1/miR-190a/PHLDB2 in inducing EMT by promoting the expression and phosphorylation of AKT3. The results of bioinformatics analysis showed that the expression of NR2F1-AS1/miR-190a/PHLDB2 in GC was positively associated with the pathological features, staging, poor prognosis, and EMT process. We performed cell transfection, qRT-PCR, western blot, cell viability assay, TUNEL assay, Transwell assay, cell morphology observation, and double luciferase assay to confirm the regulation of NR2F1-AS1/miR-190a/PHLDB2 and its effect on EMT transformation. Finally, GSEA and GO/KEGG enrichment analysis identified that PI3K/AKT pathway was positively correlated to NR2F1-AS1/miR-190a/PHLDB2 expression. AKT3 knockout cells were co-transfected with PHLDB2-OE, and the findings revealed that AKT3 expression and phosphorylation were essential for the PHLDB2-mediated EMT process. Thus, our results showed that NR2F1-AS1/miR-190a/PHLDB2 promoted the phosphorylation of AKT3 to induce EMT in GC cells. This study provides a comprehensive understanding of the underlying mechanism involved in the EMT process as well as the identification of new EMT markers.

To evaluate the effects of anatase and rutile TiO2 nanoparticles (NPs) on the growth and development of bones in young rats and explore their possible mechanisms.

Pancreatic ductal adenocarcinoma (PDAC) is a type of malignant tumor with a five-year survival rate of less than 10%. Gemcitabine (GEM) is the most commonly used drug for PDAC chemotherapy. However, a vast majority of patients with PDAC develop resistance after GEM treatment.

Automatic electrocardiogram (ECG) classification is a promising technology for the early screening and follow-up management of cardiovascular diseases. It is, by nature, a multi-label classification task owing to the coexistence of different kinds of diseases, and is challenging due to the large number of possible label combinations and the imbalance among categories. Furthermore, the task of multi-label ECG classification is cost-sensitive, a fact that has usually been ignored in previous studies on the development of the model. To address these problems, in this work, we propose a novel deep learning model-based learning framework and a thresholding method, namely category imbalance and cost-sensitive thresholding (CICST), to incorporate prior knowledge about classification costs and the characteristic of category imbalance in designing a multi-label ECG classifier. The learning framework combines a residual convolutional network with a class-wise attention mechanism. We evaluate our method with a cost-sensitive metric on multiple realistic datasets. The results show that CICST achieved a cost-sensitive metric score of 0.641 ± 0.009 in a 5-fold cross-validation, outperforming other commonly used thresholding methods, including rank-based thresholding, proportion-based thresholding, and fixed thresholding. This demonstrates that, by taking into account the category imbalance and predefined cost information, our approach is effective in improving the performance and practicability of multi-label ECG classification models.

One key task in virtual screening is to accurately predict the binding affinity (△G) of protein-ligand complexes. Recently, deep learning (DL) has significantly increased the predicting accuracy of scoring functions due to the extraordinary ability of DL to extract useful features from raw data. Nevertheless, more efforts still need to be paid in many aspects, for the aim of increasing prediction accuracy and decreasing computational cost. In this study, we proposed a simple scoring function (called OnionNet-2) based on convolutional neural network to predict △G. The protein-ligand interactions are characterized by the number of contacts between protein residues and ligand atoms in multiple distance shells. Compared to published models, the efficacy of OnionNet-2 is demonstrated to be the best for two widely used datasets CASF-2016 and CASF-2013 benchmarks. The OnionNet-2 model was further verified by non-experimental decoy structures from docking program and the CSAR NRC-HiQ data set (a high-quality data set provided by CSAR), which showed great success. Thus, our study provides a simple but efficient scoring function for predicting protein-ligand binding free energy.

To investigate the effect of liraglutide on the browning of white fat and the suppression of obesity via regulating microRNA (miR)-27b in vivo and in vitro.

Persistent cough and large amounts of purulent sputum affects many bronchiectasis patients. No studies have evaluated the efficacy and safety of bronchoscopic airway clearance therapy and bronchoalveolar lavage (B-ACT) for non-cystic fibrosis bronchiectasis patients with acute exacerbation.

Pulmonary mesenchymal stem cells (PMSCs) have great potential in lung tissue repair and regeneration, which have been isolated from some mammalian species, including mice, bovine and pig. However, the isolation, characteristics and differentiation potential of rat PMSCs have not been reported. In this study, we successfully isolated PMSCs from Sprague-Dawley rat fetal lung tissue in vitro for the first time and attempted to evaluate its multilineage differentiation potentials. The cultured PMSCs showed typical spindle-shaped morphology and high proliferative potential, and could be passaged for at least 13 passages and maintained high hereditary stability with more than 93.6 % of cells were diploid (2n = 42) by G-banding analysis. Furthermore, the PMSCs could express mesenchymal markers Sca-1, CD29, CD44, CD73 and CD90, but not hematopoietic markers CD34 and CD45. Besides, the expression of cell markers of AT2 (SFTPC), AT1 (PDPN) and macrophage (CD11b) were also negative. Cell cycle examination revealed majority of the PMSCs were in G0/G1 phase, which are similar with previously reported pig PMSCs. In addition, the PMSCs were multipotent and could differentiated into osteocytes, adipocytes, hepatocytes and neurons in vitro. Together, the present study demonstrated the stemness and multi-differentiation potentials of rat PMSCs, which conferred a potential regenerative cell resource for cell regenerative therapy of lung injury.

Hepatitis C virus (HCV) has a high rate of genetic variability, with eight genotypes and 91 subtypes. The genetic diversity of HCV genotype 6 (HCV-6) is the highest with 31 subtypes, and this genotype is prevalent in Southeast Asia. In this study, we investigated 160 individuals with chronic hepatitis C in Yunnan Province, China. Using reverse transcription (RT)-PCR and Sanger sequencing, 147 cases were successfully amplified and genotyped as 3b (4.9%), 3a (19.73%), 6n (12.24%), 1b (7.48%), 2a (6.12%), 6a (2.04%), 1a (0.68%), 6v (0.68%), and 6xa (0.68%), with eight sequences remaining unclassified. Subsequently, the eight nearly full-length genomes were successfully amplified and analyzed. The eight complete coding sequences formed a phylogenetic group that was distinct from the previously assigned HCV-6 subtypes and clustered with two previously unnamed HCV-6 sequences. Furthermore, Simplot analysis showed no recombination and the p-distance was more than 15% in comparison to the 6a to 6xi subtypes. Taken together, we identified a new HCV-6 subtype, 6xj, which originated approximately in 1775 according to Bayesian analyses. Moreover, all eight individuals received follow-up assessments at 44 weeks from the beginning of their 12-week treatments of sofosbuvir/velpatasvir (after-treatment week 32). One case relapsed at after-treatment week 32. Next-generation sequencing (NGS) was conducted and showed that the treatment failure case had two suspected antiviral resistance mutations, NS5A V28M (a change of V to M at position 28) and NS5B A442V, compared with the baseline. Overall, this newly identified 6xj subtype further confirmed the high diversity of the HCV-6 genotype. The newly identified resistance-associated amino acid substitutions may help inform future clinical treatments. IMPORTANCE This study investigated the genetic diversity of hepatitis C virus (HCV), particularly in relation to genotype 6, which is prevalent in Yunnan, China, and is often difficult to treat successfully. We identified a new HCV-6 subtype, 6xj, which is an ancient strain. Moreover, all eight individuals with the novel subtype received follow-up assessments at 44 weeks from the beginning of their treatments. One case relapsed after 8 months of withdrawal. NGS was conducted and showed that the isolate from the treatment failure case had two suspected antiviral resistance mutations, NS5A V28M and NS5B A442V, compared with the baseline. Overall, this newly identified 6xj subtype further confirmed the high diversity of the HCV-6 genotype. The newly identified resistance-associated amino acid substitutions may help inform future clinical treatments. We believe that our study makes a significant contribution to the literature based on the results described above.