Biology subjects

Deng, F.

Publications and source records attributed to Deng, F..

43 records · Page 3Linked to original sources

bioRxiv2020

The brain-bases of responsiveness variability under moderate anaesthesia

Anaesthesia combined with functional neuroimaging provides a powerful approach for understanding the brain mechanisms of consciousness. Although propofol is used ubiquitously in clinical interventions that reversibly suppress consciousness, it shows large inter-individual variability, and the brain bases of this variability remain poorly understood. We asked whether three networks key to conscious cognition -- the dorsal attention (DAN), executive control (ECN), and default mode (DMN) -- underlie responsiveness variability under anaesthesia. Healthy participants (N=17) were moderately anaesthetized during narrative understanding and resting state conditions inside the Magnetic Resonance Imaging scanner. A target detection task measured behavioural responsiveness. An independent behavioural study (N=25) qualified the attention demands of narrative understanding. 30% of participants were unaffected in their response times, thus thwarting a key aim of anaesthesia -- the suppression of behavioural responsiveness. Individuals with stronger functional connectivity within the DAN and ECN, between them, and to the DMN, and with larger grey matter volume in frontal regions were more resilient to anaesthesia. For the first time, we show that responsiveness variability during propofol anaesthesia relates to inherent differences in brain structure and function of the fronto-parietal networks, which can be predicted prior to sedation. Results highlight novel markers for improving awareness monitoring during clinical anaesthesia. Key pointsO_LIModerate propofol anaesthesia showed highly variable effects across individuals C_LIO_LI30% of healthy participants response times were unaffected by anaesthesia and 70% had significantly delayed, fragmented, or fully omitted responses C_LIO_LIGrey matter volume in frontal cortex and functional connectivity of the fronto-parietal networks predicted resilience to anaesthesia C_LI

neuroscience↗

bioRxiv2020

A genetically encoded GRAB sensor for measuring serotonin dynamics in vivo

Serotonin (5-HT) is a phylogenetically conserved monoamine neurotransmitter modulating a variety of processes in the brain. To directly visualize the dynamics of 5-HT, we developed a genetically encoded GPCR-Activation-Based 5-HT (GRAB5-HT) sensor with high sensitivity, selectivity, and spatiotemporal resolution. GRAB5-HT, detected 5-HT release in multiple physiological and pathological conditions in both flies and mice, and thus provides new insights into the dynamics and mechanisms of 5-HT signaling.

neuroscience↗

bioRxiv2020

Discovery of a novel coronavirus associated with the recent pneumonia outbreak in humans and its potential bat origin

Since the SARS outbreak 18 years ago, a large number of severe acute respiratory syndrome related coronaviruses (SARSr-CoV) have been discovered in their natural reservoir host, bats1-4. Previous studies indicated that some of those bat SARSr-CoVs have the potential to infect humans5-7. Here we report the identification and characterization of a novel coronavirus (nCoV-2019) which caused an epidemic of acute respiratory syndrome in humans, in Wuhan, China. The epidemic, started from December 12th, 2019, has caused 198 laboratory confirmed infections with three fatal cases by January 20th, 2020. Full-length genome sequences were obtained from five patients at the early stage of the outbreak. They are almost identical to each other and share 79.5% sequence identify to SARS-CoV. Furthermore, it was found that nCoV-2019 is 96% identical at the whole genome level to a bat coronavirus. The pairwise protein sequence analysis of seven conserved non-structural proteins show that this virus belongs to the species of SARSr-CoV. The nCoV-2019 virus was then isolated from the bronchoalveolar lavage fluid of a critically ill patient, which can be neutralized by sera from several patients. Importantly, we have confirmed that this novel CoV uses the same cell entry receptor, ACE2, as SARS-CoV.

microbiology↗

bioRxiv2020

Predicting long-term multicategory cause of death in patients with prostate cancer: random forest versus multinomial model

Patients with prostate cancer more likely die of non-cancer cause of death (COD) than prostate cancer. It is thus important to accurately predict multi-category COD in these patients. Random forest (RF), a popular machine learning model, has been shown useful for predicting binary cancer-specific deaths. However, its accuracy for predicting multi-category COD in cancer patients is unclear. We included patients in Surveillance, Epidemiology, and End Results-18 cancer registry-program with prostate cancer diagnosed in 2004 (followed-up through 2016). They were randomly divided into training and testing sets with equal sizes. We evaluated prediction accuracies of RF and conventional-statistical/multinomial models for 6-category COD by data-encoding types using the 2-fold cross-validation approach. Among 49,864 prostate cancer patients, 29,611 (59.4%) were alive at the end of follow-up, and 5,448 (10.9%) died of cardiovascular disease, 4,607 (9.2%) of prostate cancer, 3,681 (7.4%) of Non-Prostate cancer, 717 (1.4%) of infection, and 5,800 (11.6%) of other causes. We predicted 6-category COD among these patients with a mean accuracy of 59.1% (n=240, 95% CI, 58.7%-59.4%) in RF models with one-hot encoding, and 50.4% (95% CI, 49.7%-51.0%) in multinomial models. Tumor characteristics, prostate-specific antigen level, and diagnosis confirmation-method were important in RF and multinomial models. In RF models, no statistical differences were found between the accuracies of development versus cross validation phases, and those of categorical versus one-hot encoding. We here report a RF model that has an accuracy of 59.1% in predicting long-term 6-category COD among prostate cancer patients. It outperforms multinomial logistic models (absolute prediction-accuracy difference, 8.7%).

bioinformatics↗

bioRxiv2019

Low-disturbance farming regenerates healthy critical zone towards sustainable agriculture

Intensive conventional farming has degraded farmland topsoil and seriously threaten food and environment security globally. Although low-disturbance practices have been widely adapted to restore soil health, whether this measure in a long run can potentially recover the critical deep soil to meet sustainable intensification of crop production are still unclear. Here we compared soil microbiome, physicochemical parameters along 3-m deep soil profiles, and crop yield in Northeast China subjected to ten years of farming practices at 3 levels of disturbance, including conventional tillage (CT), no-tillage without stover mulching (NTNS), and no-tillage with stover mulching (NTSM). We found that low-disturbance practices (NTNS and NTSM) promoted the ability of the deep soil to retain water, nitrogen and salt-extractable organic, regenerated whole-soil microbial diversity and metabolic function, improved topsoil organic carbon stock and corn yield in the drought year, showed the potential to reduce energy consumption and greenhouse gas emissions, thus regenerating highly efficient, sustainable agriculture.

ecology↗

bioRxiv2019

Immune responses in mice induced by multi-epitope DNA vaccine and protein vaccine of Crimean-Congo Hemorrhagic Fever Virus

Crimean-Congo Hemorrhagic Fever (CCHF), caused by the CCHF virus (CCHFV), is a severe tick borne zoonosis widely distributed in over 30 countries and regions. Currently, there is no licensed vaccine available for CCHF in China. To evaluate the cellular and humoral immune responses induced by multi-epitope DNA and protein vaccine of CCHF in BALB/c mice, a multi-epitope gene (MEPX) segment with tandem including six highly conservative and immunedominant B cell epitopes was designed based on the analysis of hydrophilicity and antigenic determinant sites in amino acid sequences of nucleoprotein and glycoprotein from CCHFV strain YL04057. The single and double-copy multi-epitope gene (MEPX and MEPX2) were respectively cloned into the eukaryotic expression vector pVAX I to construct the recombinant (r) plasmid pVAX-MEPX and pVAX-MEPX2 as DNA vaccines. The results of immunofluorescence in vitro showed that the pVAX-MEPX and pVAX-MEPX2 could be expressed in 293T cells. The recombinant prokaryotic plasmid pET-32a-MEPX and pET-32a-MEPX2 constructed previously were transformed them into E. coli BL21 (DE3), and recombinant multi-epitope proteins (rMEPX and rMEPX2) were obtained and purificated by Nickel affinity chromatography. Western blot results showed that rMEPX and rMEPX2 had good antigenicity. BALB/c mice were immunized with DNA vaccine alone, protein vaccine alone, and DNA prime followed by recombinant protein boost immunization strategy, respectively. After three immunizations, MTT assay, cytokine content assay, and ELISA assay for antibody titers were used to evaluate the immune response. The proliferation of mouse specific T lymphocytes in the enhanced by pVAX-MEPX2 combined with rMEPX2 boosting group was significant, and the expression levels of serum IFN-{gamma} and IL-4 in mice were as high as 118.67 pg/mL and 135.33 pg/mL with significant difference compared to the control group (p<0.01), and serum antibody titer could reach up to 4.1x105. Double-copy multi-epitope vaccines groups (pVAX-MEPX2+ rMEPX2) generated better cellular and humoral immune responses by DNA prime-protein vaccine boost combinatorial immunization. This result could lay the foundation for the development of CCHFV multi-epitope vaccine candidates.

immunology↗

bioRxiv2016

Baseline mutation profiling of 1134 samples of circulating cell-free DNA and blood cells from healthy individuals

The molecular alteration in circulating cell-free DNA (cfDNA) in plasma can reflect the status of the human body in a timely manner. Hence, cfDNA has emerged as important biomarkers in clinical diagnostics, particularly in cancer. However, somatic mutations are also commonly found in healthy individuals, which extensively interfere with the diagnostic results in cancer. This study was designed to examine the background somatic mutations in white blood cells (WBC) and cfDNA for healthy controls based on the sequencing data from 1134 samples, to understand the patterns and origin of mutations detected in cfDNA. We determined the mutation frequencies in both the WBC and cfDNA groups of the samples by a panel of 50 cancer-associated genes which covered 20K nucleotide regions using ultra-deep sequencing with average depth >40000 folds. Our results showed that most of mutations in cfDNA originated from WBC. We also observed that NPM1 gene was the most frequently mutant gene in both WBC and cfDNA. Our study highlighted the importance of sequencing both cfDNA and WBC, to improve the sensitivity and accuracy for calling cancer-related mutations from circulating tumor DNA, and shielded light on developing the early cancer diagnosis by cfDNA sequencing.

bioinformatics↗