The 5-hydroxytryptamine 2A receptor (5-HT2A) and dopamine D3 receptor (DRD3) have been extensively studied as promising candidate genes for schizophrenia. Magnetic resonance imaging studies have ...demonstrated that schizophrenia is associated with widespread structural and functional abnormalities in the brain. Serotonin and dopamine receptors play crucial roles in the development of the human cerebral cortex and brain activity. However, how the 5-HT2A and DRD3 genes impact brain structure and function in schizophrenia remains unknown. In the present study, we investigated the main effect of disease state and the interaction effect between disease state and genotype of these two genes on cortical volume, thickness, surface area and functional connectivity density (FCD) in fifty-five drug-naïve first episode schizophrenia patients and fifty-three healthy controls. We found that the differences in local FCD (lFCD) and global FCD (gFCD) between patients and healthy controls were predominantly located in brain hub regions. The significant interaction effects of disease state and 5-HT2A and DRD3 genes on brain structure and function were mainly located in the temporal cortex. Our findings may help to improve the understanding of the relationship between 5-HT2A and DRD3 genotypes and schizophrenia pathogenesis.
•Metal-Organic Framework-derived Co9S8/C hollow polyhedra grow on three-dimensional graphene aerogel (Co9S8/C/GA).•The shuttling effect is efficiently suppressed by the polar Co9S8/C electrode.•The ...free-standing Co9S8/C/GA composite serves as an efficient sulfur host material.•The Co9S8/C/GA/S cathode exhibits excellent long-cycling stability.
Lithium-sulfur (Li-S) batteries are considered as one of the most promising candidates for next-generation energy storage systems because of their high energy density. However, rapid capacity fade and low sulfur content caused by the shuttle effect of soluble lithium polysulfides (LiPSs) and the low conductivity of sulfur hinder the practical applications of Li-S batteries. In this regard, we synthesized metal-organic framework (MOF)-derived Co9S8/C hollow polyhedra grown on three-dimensional graphene aerogel (3D GA) as an efficient sulfur host material. The highly porous, conductive and free-standing 3D GA framework enables high sulfur content (77.3 wt%). The polar Co9S8/C provides strong chemical binding to immobilize polysulfides, and suppress the shuttling effect. Significantly, the Co9S8/C/GA/S cathode exhibits excellent long cycling stability with a low capacity decay rate of 0.0473% per cycle over 400 cycles.
Summary
Flavor‐imparting volatile chemicals accumulate as fruits ripen, making major contributions to taste. The NAC transcription factor nonripening (NAC‐NOR) and DNA demethylase 2 (SlDML2) are ...essential for tomato fruit ripening, but details of the potential roles and the relationship between these two regulators in the synthesis of volatiles are lacking.
Here, we show substantial reductions in fatty acid and carotenoid‐derived volatiles in tomato slnor and sldml2 mutants. An unexpected finding is the redundancy and divergence in volatile profiles, biosynthetic gene expression, and DNA methylation in slnor and sldml2 mutants relative to wild‐type tomato fruit. Reduced transcript levels are accompanied by hypermethylation of promoters, including the NAC‐NOR target gene lipoxygenase (SlLOXC) that is involved in fatty acid‐derived volatile synthesis.
Interestingly, NAC‐NOR activates SlDML2 expression by directly binding to its promoter both in vitro and in vivo. Meanwhile, reduced NAC‐NOR expression in the sldml2 mutant is accompanied by hypermethylation of its promoter. These results reveal a relationship between SlDML2‐mediated DNA demethylation and NAC‐NOR during tomato fruit ripening.
In addition to providing new insights into the metabolic modulation of flavor volatiles, the outcome of our study contributes to understanding the genetics and control of fruit ripening and quality attributes in tomato.
Accurate classification of gliomas is critical to the selection of immunotherapy, and MRI contains a large number of radiomic features that may suggest some prognostic relevant signals. We aim to ...predict new subtypes of gliomas using radiomic features and characterize their survival, immune, genomic profiles and drug response.
We initially obtained 341 images of 36 patients from the CPTAC dataset for the development of deep learning models. Further 1812 images of 111 patients from TCGA_GBM and 152 images of 53 patients from TCGA_LGG were collected for testing and validation. A deep learning method based on Mask R–CNN was developed to identify new subtypes of glioma patients and compared the survival status, immune infiltration patterns, genomic signatures, specific drugs, and predictive models of different subtypes.
200 glioma patients (mean age, 33 years ± 19 standard deviation) were enrolled. The accuracy of the deep learning model for identifying tumor regions achieved 88.3 % (98/111) in the test set and 83 % (44/53) in the validation set. The sample was divided into two subtypes based on radiomic features showed different prognostic outcomes (hazard ratio, 2.70). According to the results of the immune infiltration analysis, the subtype with a poorer prognosis was defined as the immunosilencing radiomic (ISR) subtype (n = 43), and the other subtype was the immunoactivated radiomic (IAR) subtype (n = 53). Subtype-specific genomic signatures distinguished celllines into ISR celllines (n = 9) and control celllines (n = 13), and identified eight ISR-specific drugs, four of which were validated by the OCTAD database. Three machine learning-based classifiers showed that radiomic and genomic co-features better predicted the radiomic subtypes of gliomas.
These findings provide insights into how radiogenomic could identify specific subtypes that predict prognosis, immune and drug sensitivity in a non-invasive manner.
•Deep learning extracts radiomic features are complementary to clinical features.•Genomic signatures in radiomic subtypes are associated with immunity.•Radiogenomics machine learning models can predict radiomic subtypes.
In this study, one well-known CHM residue (Atropa belladonna L., ABL) was used to prepare biochar capable of adsorbing rhodamine B (RhB) with an ultrahigh surface area for the first time. Three ...micropore-rich ABL biochars including ABL@ZnCl2 (1866 m2/g), ABL@H3PO4 (1488 m2/g), and ABL@KOH (590 m2/g) were obtained using the one-step carbonization method with activation agents (ZnCl2, H3PO4, and KOH) via chemical activation and carbonization at 500 °C, and their adsorption performance for RhB was systematically studied with adsorption kinetics, isotherms, and thermodynamics. Through pore diffusion, π–π interaction, and hydrogen bonding, ABL biochar had excellent adsorption performance for RhB. Moreover, when C 0 was 200 mg/L, biochar dosage was 1 g/L, and the contact time was 120 min; the maximum RhB adsorption capacity and removal efficiency on ABL@ZnCl2 and ABL@H3PO4 were 190.63 mg/g, 95% and 184.70 mg/g, 92%, respectively, indicating that it was feasible to prepare biochar from the ABL residue for RhB adsorption. The theoretical maximum adsorption capacities of ABL@ZnCl2 and ABL@H3PO4 for RhB were 263.19 mg/g and 309.11 mg/g at 25 °C, respectively. Furthermore, the prepared biochar showed good economic applicability, with pay back of USD 972/t (ABL@ZnCl2) and USD 987/t (ABL@H3PO4), respectively. More importantly, even after five cycles, ABL@H3PO4 biochar still showed great RhB removal efficiency, suggesting that it had a good application prospect and provided a new method for the resource utilization of traditional CHM residues. Additionally, pore diffusion, π–π interactions, and hydrogen bonding all play roles in the physical adsorption of RhB on ABL biochar. π–π interactions dominated in the early stage of RhB adsorption on ABL@H3PO4, while pore diffusion played a crucial role in the whole adsorption process on both adsorbents.
Listeria monocytogenes is an important foodborne pathogen, and is ubiquitously distributed in the natural environment. Cattle and sheep, as natural hosts, can transmit L. monocytogenes to related ...meat and dairy products. In this study, the prevalence, distribution, and transmission characteristics of Listeria were analysed by investigating 5214 samples of cattle and sheep in farm and slaughtering environments in China. A low contamination incidence of L. monocytogenes (0.5%, 20/4430) was observed in farm environment, but there was a high contamination incidence in slaughtering environment (9.4%, 74/784). The incidence of L. innocua in cattle and sheep farm and slaughtering environments is more common and significantly higher (9.7%, 508/5214) than that of L. monocytogenes (1.8%, 94/5214). The distinct molecular and genetic characteristics of Listeria by PFGE and MLST indicated that L. monocytogenes and L. innocua were gradually transmitted from the farm and slaughtering environments to end products, such as beef and mutton along the slaughtering chain. The ST7, ST9, ST91, and ST155 found in our study were associated with the human listeriosis cases in China. In addition, the findings of virulence markers (inlC, inlJ, LIPI-3, LIPI-4, and ECIII) concerned with the pathogenesis of human listeriosis and antibiotics resistance of L. monocytogenes in this study implies a potential public health risk. This study fills the gap in the epidemiology of beef cattle and sheep that carry Listeria in farm and slaughtering environments in major cattle and sheep producing areas in China.
Supplementation with N2-NBW effectively alleviated the obesity-associated markers in the high-fat diet fed mice.
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•Effects of nanobubble water (NBW) on the process of high-fat diet ...(HFD) induced obesity was investigated for the first time.•Supplementation with nitrogen NBW alleviated the obesity-associated markers in the HFD fed mice.•The effects of NBW on ameliorating obesity were mainly achieved by modulating the gut microbiota in mice.
This study aims to investigate the effects of nanobubble water (NBW) on the process of obesity in mice under high-fat diet (HFD). In the experimental groups, HFD feeding mice were supplemented with nitrogen NBW (HFD-N2) or hydrogen NBW (HFD-H2), while the mice fed with standard diet (SD-C) or HFD (HFD-C) supplementation with deionized water were used as control groups. After ten weeks, the concentrations of total cholesterol, alanine aminotransferase and lipopolysaccharide in the mice serum of the HFD-N2 group were significantly lower than those in the HFD-C group. 16S rRNA gene sequencing analysis of the community structures of fecal flora showed that supplementation with N2-NBW to the HFD fed mice could decrease the ratio of Firmicutes to Bacteroidetes. In conclusion, these results demonstrate that supplementation with N2-NBW potentially alleviates the development of obesity in HFD fed mice.
To explore the difference in tumor-infiltrating lymphocytes (TILs) and programmed death-ligand (PD-L1) in primary hepatocellular carcinoma (HCC) and its adjacent tissues, and to evaluate their effect ...on HCC prognosis.
Liver cancer and paracancerous tissue samples were collected from 72 patients who underwent radical hepatectomy between December 15, 2017 and January 9, 2019. Flow cytometry was used to detect the distribution of TILs and PD-L1, analyze the correlation between the expression of CD8/CD3 and PD-L1 and clinical-pathological parameters, and evaluate their effect on the prognosis of HCC patients.
The distribution proportion of CD3+T cells, CD4+T cells, and PD-L1 in liver cancer were significantly higher than in paracancerous tissues, while the distribution proportion of CD8+T cells was significantly lower (all P<0.05). In HCC, the distribution proportion of CD8+T cells was related to tumor size and stage, while the PD-L1 expression was related to the tumor stage only (all P < 0.05). Univariate analysis showed that tumor differentiation, TNM stage, expression of CD8/CD3, and PD-L1 in tumor tissue were related to disease-free survival (DFS)(P < 0.05); multivariate Cox regression analysis showed that tumor differentiation, TNM stage, CD8/CD3, and PD-L1 expression were independent influencing factors of postoperative DFS (P < 0.05). Kaplan-Meier survival curve analysis showed that the DFS of CD8/CD3 high expression group was significantly higher than that of the low expression group, and the DFS of PD-L1 low expression group was significantly higher than that of the high expression group (all P < 0.05).
There are significant differences in the distribution of TILs and PD-L1 in HCC and paracancerous tissues. The expression of CD8/CD3 and PD-L1 in tumor-infiltrating lymphocytes in HCC may help evaluate the immunological indexes of prognosis after radical resection of HCC and to further the study of immunotherapy in patients with HCC.
Objective
There is substantial heterogeneity among the phenotypes of patients with anti–melanoma differentiation–associated gene 5 antibody–positive (anti‐MDA5+) dermatomyositis (DM), hindering ...disease assessment and management. This study aimed to identify distinct phenotype groups in patients with anti‐MDA5+ DM and to determine the utility of these phenotypes in predicting patient outcomes.
Methods
A total of 265 patients with anti‐MDA5+ DM were retrospectively enrolled in the study. An unsupervised hierarchical cluster analysis was performed to characterize the different phenotypes.
Results
Patients were stratified into 3 clusters characterized by markedly different features and outcomes. Cluster 1 (n = 108 patients) was characterized by mild risk of rapidly progressive interstitial lung disease (RPILD), with the cumulative incidence of non‐RPILD being 85.2%. Cluster 2 (n = 72 patients) was characterized by moderate risk of RPILD, with the cumulative incidence of non‐RPILPD being 73.6%. Patients in cluster 3 (n = 85 patients), which was characterized by a high risk of RPILD and a cumulative non‐RPILD incidence of 32.9%, were more likely than patients in the other 2 subgroups to have anti–Ro 52 antibodies in conjunction with high titers of anti‐MDA5 antibodies. All‐cause mortality rates of 60%, 9.7%, and 3.7% were determined for clusters 3, 2, and 1, respectively (P < 0.0001). Decision tree analysis led to the development of a simple algorithm for anti‐MDA5+ DM patient classification that included the following 8 variables: age >50 years, disease course of <3 months, myasthenia (proximal muscle weakness), arthritis, C‐reactive protein level, creatine kinase level, anti–Ro 52 antibody titer, and anti‐MDA5 antibody titer. This algorithm placed patients in the appropriate cluster with 78.5% accuracy in the development cohort and 70.0% accuracy in the external validation cohort.
Conclusion
Cluster analysis identified 3 distinct clinical patterns and outcomes in our large cohort of anti‐MDA5+ DM patients. Classification of DM patients into phenotype subgroups with prognostic values may help physicians improve the efficacy of clinical decision‐making.
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