Abstract:The formation of mutant p53 aggregates is caused by the exposure of the adhesion sequences wrapped in the hydrophobic core of p53 after mutation. After exposure, the adhesion sequences will quickly nucleate and assemble to form amorphous fibrils. The mutant p53 aggregates can not only inactivate wild type p53 (Wt-p53) in a dominant-negative effect manner, but also exhibit gain-of-function (GOF) characteristic to promote the development and progression of tumors. Abnormal aggregation of mutant p53 has been found in various tumors, such as ovarian cancer, colon cancer and prostate cancer. The mutant p53 aggregates are significantly correlated with tumor metastasis, drug resistance and poor prognosis. Therefore, p53 aggregation is considered as a potential therapeutic target. The discovery of small molecule compounds targeting mutated p53 aggregates, which can inhibit the exposure of adhesion sequences in the hydrophobic core of p53 and restores the function of p53, is becoming a promising strategy in cancer therapy. In this review, we summarized the mechanism of p53 aggregation and the potential therapeutic strategies.

Abstract:In recent years, tumor immunotherapy has become a hot spot in the field of cancer treatment. Among them, nanovaccines combining tumor vaccines and nanotechnology provide new ideas for tumor immunotherapy. Nanovaccine can realize the co-loading of vaccine and adjuvant. The intelligent nanocarriers further realize the effective targeted delivery of antigen, promote the uptake and presentation of antigen, specifically activate antigen-specific immune response and effectively kill tumor cells. This article reviews the principles, advantages, types of nano materials, and clinical efficacy of nanovaccine to provide a more reliable reference for the design of nano-vaccine in the later stage.

Abstract:Pannexin1(PANX1) is a channel protein which can be penetrated by many ions and molecules including ATP. It plays important roles in many physiological phenomena such as apoptosis and inflammation, and is considered as a potential therapeutic target. It can be activated by many different stimuli such as extracellular potassium, phosphorylation, protease cleavage, and intracellular calcium. Also its electrophysiological characteristic is complicated. Its characteristics as an ion channel need to be investigated in details. With the development of cryoelectron microscopy in recent years, the study of ion channels has reached a new stage, and the structure of PANX1 protein has been elucidated, including the activation mechanism, ion pathway and blocking mechanism of small molecule inhibitors. It is a heptamer rather than a hexamer as previously suspected. In addition to the main pore responsible for molecules like ATP, there are also side tunnels responsible for ion conducting. But still there are many problems remain unsolved. Cryo-EM structures didn’t show how C-tail exist in main pore of channel. This paper will introduce some basic characteristics of PANX1, and analyze the problems encountered in current studies, in order to put forward the key research objectives for future work.

Abstract:Heterogeneous nuclear ribonucleoproteins (hnRNPs) are a family of multifunctional RNA-binding proteins that bind to nascent transcripts synthesized by RNA polymerase II and participate in the regulation of transcript stabilization and maturation in the form of complexes. hnRNP A1 is an important member of this protein family and is not only widely involved in the regulation of alternative splicing of genes related to cancer and neurological diseases, but also plays an important role in viral infection, cellular aging and stress recovery. Besides, as hnRNP A1 is a typical RNA-specific binding protein, the rules of identifying specific sequences through dynamic three-dimensional structures have also been revealed in the regulation of transcription and alternative splicing. This review summarizes the research progress of hnRNP A1 in recent years, providing references for the further exploring its function in disease development.

Abstract:Identifying the objective biological markers is one of the most important scientific goals in psychiatric research. Recently, neuroelectrophysiological studies incorporating evidence-based medicine has provided an important approach and achieved abundant results to achieve this goal. However, there are still many controversies among current evidences, and it is difficult to reach a consensus. This article comprehensively summarized the results of psychiatric studies on mental disorders which combined the method of evidence-based medicine represented by meta-analysis and the neuroelectrophysiological technique represented by electroencephalography (EEG). To systematically analyze and summarize the neurocognitive dysfunction of mental disorders and high-risk groups, event-related potential (ERP) components are divided into early and late components including different cognitive activities such as perception processing, cognitive control, emotional response, and social cognition. Evidence based on quantitative EEG analysis are also discussed. We found that schizophrenia has defects in most of cognitive processes including perception, emotion and sociality, which indexed by amplitude reduction in most of the early and late components including P50, MMN, P300 and LPP. Attention deficit/hyperactivity disorder (ADHD) has defects in cognitive control indexed by amplitude reduction in the early and late components including the ERN and Pe. Anxiety and obsessive-compulsive disorder have defects in early cognitive control, while autism spectrum disorder (ASD) has defects in early perceptual processing and social cognition indexed by amplitude reduction of N170 and FN. In addition, abnormal P300 reflexing the impaired cognitive processing speed and attention resource allocation were found across multiple diagnosis types, which indicate that this ERP component may reflect the general cognitive deficits of mental disorders. The neuroelectrophysiological studies on evidence-based medicine for mental disorders has discovered a series of valuable ERPs or EEG objective marker features, but these features still cannot be directly used in the diagnosis of personalized medicine, until these features have been identified as objective biomarkers with high accuracy and specificity in further research and clinical practice. Future research can use multi-center database to seek the electrophysiological objective markers for mental disorders, and the integrated research combining advanced technologies including multi-modal psychoradiology and artificial intelligence methods including machine learning can further enhance the reliability and validity of biological markers of mental disorders.

Abstract:White matter, which constituted the anatomical connections between brain regions, accounted for approximately 50% of the human brain. The crucial role of the intact white matter connections for normal brain function has been described by extensive lesion and anatomic studies. Although traditional structural techniques, such as diffusion tensor imaging (DTI), can successfully explore the white matter architecture, they failed to uncover neural activity and dynamics occurring in white matter. Blood oxygen level dependent functional magnetic resonance imaging (BOLD-fMRI) is a noninvasive technique to map brain activation and connectivity. Previous BOLD-fMRI studies primarily focused on spontaneous activity in gray matter rather than that in white matter, since white matter fMRI activation remained controversial. However, the evidence is accumulating for fMRI activation in white matter. This paper reviewed former researches on spontaneous activity in white matter, including physiological bases, neurovascular and neurometabolic coupling, brain activation, and brain connectivity. Despite the differences observed in vascular density between gray matter and white matter, BOLD effects in white matter were reported to be related to neural activity. Robust BOLD activations were detected in the posterior limb of internal capsule, anterior corpus callosum, etc. The power spectrum of resting-state white matter BOLD signals was associated with white matter density and fraction anisotropy (FA) rather than random distribution as noise. Besides, regarding to the functional connectivity of white matter, it was well established that white matter manifested an intrinsic functional organization as interacting networks of functional modules. Moreover, the functional networks of white matter were closely related to that of gray matter and white matter tracts. Several brain disorders, such as mild cognitive impairment, schizophrenia, Alzheimer’s and Parkinson disease, were characterized by functional connectivity abnormalities of white matter. Finally, the recommendations and suggestions for future study were included on the neurophysiological basis of white matter BOLD-fMRI signal using multimode imaging data and the common abnormalities in white matter across multiple psychiatric disorders.

Abstract:Risk pathogenic genes prediction is important for uncovering the occurrence and development mechanism of complex diseases (i.e., cancer), improving the disease detection, prevention and treatment, and providing the targets for drug design. Traditional gene-mapping approaches, such as linkage analysis and genome-wide association studies (GWAS), often predict hundreds of candidate genes. But it is costly, time-consuming and laborious to further validate these candidate genes with biological experiments. However, the number of candidate pathogenic genes can be effectively reduced by computational and prioritization methods. Considering the excellent performance of random walk with restart (RWR) in predicting the risk pathogenic genes, in this work, we comprehensively discuss the recent progresses of predicting the risk pathogenic genes with RWR from databases related with genes and diseases, the metrics of measuring the similarity between genes/diseases, the strategies of choosing the seed genes of specific disease, and the different genes/diseases network structures. We also point out the computational problems and challenges faced in the process of pathogenic genes prediction.

Abstract:This short communication is to report the inhibitory effect of deuterium oxide (D₂O) on germination and culturability of bacterial spore. Germination was triggered by L-alanine under ambient condition and in situ monitored by Tb³⁺-dipicolinic acid assay, phase contrast microscopy and absorbance measurement. Germination kinetics were characterized by final germination level, germination half time, and germination speed. The culturability of germinated spores was evaluated by enumerating colony-forming units. Results revealed that D₂O retarded the whole germination process and reduced the culturability but didn’t affect the final germination level. We postulate that D₂O enhanced the stability of some spore-specific signaling proteins.

Abstract:The nucleolus is an important subnuclear structure in the cell, which plays an important role in the evolution of malignancies and the diagnosis of cancer. Although the nucleolus is critical, so far, there are really few fluorescent probes for the nucleolus. In this paper, salicylic acid and 1,8-diaminonaphthalene were used as carbon and nitrogen sources, and a novel fluorescent carbon nanoparticles (FCNs) were synthesized by microwave digestion system. Its physical, chemical and optical properties of FCNs were characterized and analyzed by using transmission electron microscope (TEM), dynamic light scattering instrument (DLS), Fourier infrared spectrometer, ultraviolet spectrophotometer, fluorescence spectrometer, etc. The experimental results demonstrated that the synthesized carbon nanoparticles were uniform in size and rich with amino groups on surface. Its best excitation wavelength was 348 nm, the corresponding maximum emission peak was 432 nm. Its fluorescence quantum yield was 17.8% and fluorescence lifetime was 1.13 ns. Moreover, the photostability and cytotoxicity of FCNs were investigated with illumination and MTT assays. Our results suggest that FCNs exhibit to be a really photostable and low toxic probe. To confirm the potential application of this fluorescence FCNs in bioimaging, the FCNs were designed to stain human cervical cancer HeLa cells. After incubation, we found that FCNs enable the function of selectively staining the nucleolus of living cells due to its positive chargeability. Its cellular uptake mechanism and intracellular distribution in HeLa cells were explored further by using confocal laser scanning microscopy and TEM. It was interesting to observe that more FCNs entered the cell, and lighted the nucleolus more obviously with the extension of the co-incubation time. In addition, after investigating the cells’ uptake path of FCNs, we found that FCNs were endocytosed via caveolae-mediated pathway rather than clathrin mediated pathways or macropinocytosis. Our study provided a potential probe for nucleolus and this finding is of great significance for the development of functional nanomaterials targeting subcellular organelles.

Abstract:Design of enzyme binding pocket to accommodate substrates with different chemical structure is a great challenge. Traditionally, thousands even millions of mutants have to be screened in wet-lab experiments to find a ligand-specific mutant and large amount of time and resources are consumed. To accelerate the screening process, we propose a novel workflow through integration of molecular modeling and data-driven machine learning method to generate mutant libraries with high enrichment ratio for recognition of specific substrate. We collected all the M. jannaschii tyrosyl-tRNA synthetase (Mj. TyrRS) mutants reported in the literature to compare and analyze the sequence and structural feature and difference between mutant and wild type Mj. TyrRS. Mj. TyrRS is used as an example since the sequences and structures of many unnatural amino acid specific Mj. TyrRS mutants have been reported. Based on the crystal structures of different Mj. TyrRS mutants and Rosetta modeling result, we found D158G/P is the critical residue which influences the backbone disruption of helix with residue 158-163. Our results showed that compared with random mutation, Rosetta modeling and score function calculation can elevate the enrichment ratio of desired mutants by 2-fold in a test library having 687 mutants, while after calibration by machine learning model trained using known data of Mj. TyrRS mutants and ligand, the enrichment ratio can be elevated by 11-fold. This molecular modeling and machine learning-integrated workflow is anticipated to significantly benefit to the Mj. tyrRS mutant screening and substantially reduce the time and cost of wet-lab experiments. Besides, this novel process will have broad application in the field of computational protein design.

Abstract:Molecular classification of cancer is the current frontier of cancer omics and tumor precision medicine. Although great progress has been made in molecular analysis of whole cancer, the molecular classification of cervical squamous cell carcinoma still needs more exploration. In order to find the potential subtypes of cervical squamous cell carcinoma, this paper proposed a data processing and analysis process based on the classification of cancer subtypes based on multi-omics data. Specifically, we analyzed mRNA, and microRNA (miRNA) expression data, as well as DNA methylation and copy number variation in cervical squamous cell carcinoma cases, using datasets obtained from The Cancer Genome Atlas (TCGA). Moreover, we identified molecules in each dimension, as well as integrated and clustered filtered classification features, and used them to distinguish different subtypes. The resulting key classification features were used to establish a classification model for cervical squamous cell carcinoma. The resulting key classification features were used to establish a classification model for cervical squamous cell carcinoma. Our results revealed two cervical squamous cell carcinoma subtypes, with significant differences across clinical survival levels, as well as 8 key classification features of cervical squamous cell carcinomas. These findings are expected to provide important references for early classification of cervical squamous cell carcinoma and identification of classification markers.